(Part 2) Reddit mentions: The best databases & big data books

You've chosen an interesting time to pick up web development! /u/GruntildaJr left an excellent guide on learning front end development, but as a back-end developer I wanted to chime in for the other half.

Learning back-end development without an internet connection will be a little more difficult, but certainly not impossible nor any more effort than a few hours of getting things configured. Nearly any web server can be hosted on your personal machine without an internet connection. Apache is my personal choice and likely one of the easiest to setup on Windows, but Nginx is a lot of fun and there's plenty of options.

Here is a fairly straight forward tutorial for setting up a local development environment on Windows. Although the writer suggests using Zend Eclipse as an editor and I would have to point you towards PHPStorm or Atom with a linter and autocomplete plugin. That said, Eclipse will serve you fine. After completing the tutorial you will have PHP, MySQL, PHPMyAdmin, and Apache set up and running. While not especially fancy, these are the basic tools to start learning the ins and outs of back-end development.

As for learning materials, I love Learning PHP, MySQL, and JavaScript and PHP The Right Way. If you want something very beginner friendly and a bit easier to read, PHP Pandas is a good option.

Of the three, PHP The Right Way will be the biggest challenge. It moves quickly and takes you the furtherest, if you haven't programmed before I wouldn't recommend starting with it but I would recommend going through it after you've gotten some experience under your belt. The O'Reilly book is good for walking through a stack of technologies and outlining how they interact to make a full website, while PHP Pandas is a more thorough dive into the language itself (and it's a lot less painful to slog through if you don't like textbooks). All three are excellent and stand well on their own. If you can only select a single one though, I'd highly recommend the O'Reilly book.

A good companion for any more formal book is the Learn X In Y Minutes PHP Page. It's a little one page cheat sheet to reference when you forget something like the syntax for a switch statement or why you should use double instead of single quotes. There's also a bunch of other languages including JavaScript and I've found them all incredibly helpful. Zeal, as mentioned by GruntildaJr is also a great asset, and it contains the pages for PHP.

There are back-end languages other than PHP along with plenty of frameworks and libraries to explore and learn. I don't want to make it sound as if PHP is your only choice, or the best choice for a back-end language. I do think that it is one of the best choices for a back-end language when you take the learning offline, though. There is a wealth of offline literature, I only linked a few books but the market is simply saturated with PHP texts. The language also stands easily on its own, and for the most part the texts treat it as such. You won't constantly be needing to "pip install" or "npm install" like you do with Python and Node.js.

I hope all of that was of some help, it can be a hump to get over that initial setup but afterwards the learning is much more rewarding. Happy developing and godspeed!

aah well if you primarily like webpage designing and management and sorts then you can start with HTML/CSS and move up to php,sql and javascript. I've seen many job openings for people efficient with the above.
Now if you want to go to the path of making apps and program then you can choose C++/Java/Python+swift(or swift alone if iOS developer is your focal point) which is very lucrative.
Personally I hated C++ and I am learning Java. I use the course book "Intro to Java Programming" by Daniel Liang which comes with a website that lets you preview examples which really helps. I've heard that python codes are easier to begin with but Java has the market. This article might help you decide what to go with. Also I have found learning html/css is very useful as many blogs and such allows you executive control over design with html/css. I am learning php and sql with the help of this book and this one which is really top notch. They require you to have prior knowledge on HTML and CSS so I'd recommend you to use codecademy to kickstart it all. They have HTML/CSS, JavaScript, python among others. I am really fond of their beautiful UI and learning process which helps a lot. At the end of the course they have where you have to build a project to complete the course which is really cool and exciting imo.
Good luck in your journey and get the 8.1, it's not bad as people make it out to be, it's kind of like OS X but windows people adore the start functionality and reporters who use mac join on the bandwagon. Also windows 7 requires cost to upgrade to 8.1 and possibly to 10 whereas 10 will most probably be free for 8.1 users. I adore the multi tasking functionality on the 8.1 and prefer it to 7.

My advice is to follow 3 tracks.

• Build relationships. Find local meetings where people building products/companies or other designers go. Such as: 1 Million Cups, Open coffee club, Creative Mornings, CoFounders Lab, StartUp Grind, local UX meetups. Pick 1 weekly and go every week. Pick 1-2 others, go when you can. Talk to the people who run the group. See if they need any help checking people. Volunteer to do that. If you get to, be friendly and chat with people on the way in. This is your tribe. Don't feel like you don't belong b/c you are young or are checking them in (or whatever other excuse your mind might come up with). This is your opportunity to find out about what people are working on. Some people will be working on something that interests you, that you have the skills to help with (eventually if not now), and have a personality you could enjoy working with. Give 100% of these people your card. Tell them you do UI/UX on contract. Ask for their card. Talk to them more at the end of the meeting if you can. Not in a sales way. But in a get to know more about them way. Then follow up with an email shortly afterward, a few days to a week. And in 6 months again if you haven't connected since. Do this every week for 2-3 years and you will have your client base and reputation in town. If you need practice to feel confident doing the networking part, then practice. Your career counseling dept at college could probably help you practice. Friends can be good practice too. Comfort with networking is critical to running your own business. Your goal should be to eventually lead a recurring meeting.
  
  
• Build your skills. First college is great for learning some things. I believe it is terrible for learning UI/UX. Studying behavioral economics would probably be the most applicable, some psychology or data science as well. UI/UX moves too fast. But here are my recommendations for becoming good at UI/UX quickly:
  
  

1. Start using Sketch app by Bohemian coding. It is the current industry standard.
   
   
2. Sign up for Subform app wait list. It will probably be the next industry standard. But is not available yet.
   
   
3. Study design systems Practice using these elements to create screens. Download the Sketch file. Then grab the elements you need and create screens to build an app (preferably to solve a simple problem you care about). Start small. Practice designing quickly. Then go back and make details precise. Eventually you should be able to build your own design system like this.
   
   
4. Study material design and iOS design.
   
   
5. For inspiration in practice, look at examples on Dribbble, Behance, and at the apps you use everyday.
   
   
6. Get feedback from friends and family on the things you have designed.
   
   
7. Read books like Inspired, Seductive Interaction Design, Sprint, Product Leadership. There are many more.
   
   
8. Understand you need to know more than design to do contract work for small businesses. Your clients may often ask for one thing but really need something different. Study business in general. Read books and magazines about business models, industry shifts, etc. Good UX designers are always balancing user needs and business model needs. There is no formula for this. It takes practice. Lots of practice. Youth and inexperience here will be a challenge. Talk to as many people in their 30s/40+s about business lessons they have learned as you can. This knowledge will help your design.
   
   
9. Don't wait for the perfect idea to practice. Practice everyday.
   
   

• Build your savings. So you can go full-time at a co-working space. This is less direct advice. But you will need to have a few months of living expenses saved so one day you can dive in. A co-working space costs a few hundred per month but this is where your client base likely lives or goes to meetings occasionally. Being part of one shows you have a professional presence. And the serendipity at these places can be off the charts. And I highly recommend not working form home only for many reasons, sanity being an important one. Also, contract work can be feast or famine. I have had a handful of weeks in the past 4 years where I have needed to complete 60 billable hours work. This is more stressful than the weeks where I only have 20 billable hours b/c I save knowing work will be up and down.
  
  ----
  
  These are things that led me to where I am today. Others may have completely different or contradictory advice. But these are my go to methods. And most of my clients in the past 2 years have come to me. I didn't call them, or post an ad. Generally they found me through a recommendation from a friend, LinkedIn, Twitter, slack group, Dribbble, or at a meeting.

As far as training goes I am a trainee myself so I don't know how much help I can provide. Since you seem pretty new to all this (with the most positive meaning) here are some points I can give you and I hope others will correct me where I am wrong.

• Learn the basics of each language. You need HTML, CSS3 and Javascript. Those cover the front end. Especially for Javascript I hear good words for this book http://eloquentjavascript.net/. That codewars site you using will help you cement the basics of the language but don't spend very long time in that.
  
  
• For back end you seem to have chosen PHP. I would complement with some knowledge of SQL. Especially data relationships, database normalization, joins etc.
  
  
• After you have the basics down then look for frameworks. Frameworks are essentially blueprints of web applications. The important decisions are made for you and you must fill your business logic. They will reduce a lot of work. These are what I know to be popular. Since I don't use them there might be other options
  
  
  
  
• HTML + CSS -> Foundation, Bootstrap
  
• Javascript -> JQuery, Angualar, React and an ocean of others. For now I think JQuery will suffice
  
• PHP -> https://laravel.com/ or maybe a CMS like drupal. I don't know which would be best. Lavarel would require more code from you but the result will be closer to your needs. Drupal is more point and clicky, maybe will get you there faster but it is a more out of the box solution. Both will abstract a lot of SQL for you.
  
  
• Validation: You can do it in both Javascript and PHP. In Javascript validation will enhance your users experience while in the PHP it is essential for your site's security and your data integrity. In back end I would say validation is mandatory while in front end you can skip it for now, according to your needs.
  
  Most important: Go to github.com and seek for projects doing what you want to do preferably with the frameworks you choose. Then read their code and try to understand what they do.
  
  PS: If you haven't done any serious reading so far I would recommend this book. https://www.amazon.com/Learning-PHP-MySQL-JavaScript-Javascript/dp/1491918667
  It is a bit outdated but it is packed with good advice to get you started. The rest you can learn by googling.

A great portfolio and github profile can be worth more than a degree in many cases. The degree can help get you in the door for your first few jobs, but definitely is not required. Show off your side projects. Show off your code. All your web projects should have readable HTML, CSS, and Javascript (I should be able to right click, view source, and see what you wrote).

You're pretty much guaranteed a front-end web job if you have great skills with one of the big front-end js frameworks right now: angular, react, etc...

Some jobs to look out for: Front-end developer, UX Developer, UX Prototyper. Front-End dev is such a valuable position, some companies don't know how much they're needed. UX Developer -- who knows what they mean by this... UX Prototyper -- usually someone who focuses on front-end interactions, generally hands off to a core development team.

Lastly, it'd be great to have some core "UX" skills. Steve Krug's Don't Make Me Think is a great intro. Pick up a wireframing tool like Balsamiq or Axure and learn to wireframe before you implement. (As a UX dev though, hopefully the design team hands off wireframes to you, or involves you in the design process)

I buy books because they go into a lot more details, or often are written really well, and easy to follow. Also, it's really nice to read paper. Often I keep books in the office as it's a quick and reliable way to research a topic in-depth without scrolling through hundreds of shit articles on a particular (and even controversial subject).

I really recommend these:

High Performance MySQL: Optimization, Backups, and Replication - I've read snippets, but it's recommended a lot and very good for more advanced readers.

SQL Antipatterns: Avoiding the Pitfalls of Database Programming - VERY beginner friendly, easy to read, follow, provides real and common scenarios and explains the anti-pattern, it's problems, the reasons to sometime excuse their use, and solutions. I love this book.

The Go Programming Language - Very good read, not TOO technical jargon, very nice to read, explains in depth and in an understandable way.

I've had plenty more over the years, but these are my current I have at home. Still more on order. :)

ohh "set things up" is a very very wide term. OBIEE can do a ton of stuff. First do you have a data warehouse? What is the source of your data? I can give you the basics. OBIEE uses a metadata repository its called and RPD this is the source of all queries. You pull metadata from your source and then build out the RPD through a physical -> Business -> Presentation layer. The Business layer can do quite a bit of work for you in terms of combining dimensions and joins but you want as much of a star schema as possible from the source. Read Kimballs book listed below to understand star schema and warehousing concepts.

Inside of the OBI admin tool there is also some user management, user management isa whole nother aspect. Are you using some ldap authentiacaiton or will you be managing users though obiee? There are USERS, GROUPS, & ROLES. This is another aspect to deal with.

There is also the EM web portal, Enterprise Manager from here you do other management of users and roles and the actual services. This is another thing, where is this hosted? Do you already have OBIEE 11g set up on a server? If so you will need access to that box to do services management. Also may need to modify config files here.

Then there is the actual reporting service, OBIEE uses dimensions and a fact to create charts, pivot tables etc. Here you will log into the web front end this would be accessed by going to http://servername:port/analytics From here you log in as your development user by default its weblogic i beileve. And here is where you would create dashboards etc.

This is just one aspect of the tool set, there is also BIP (bi publisher) used to develop reports from various sources by creating a template and filling the template out by using XML.

Oracle offers classes, which if your managment is throwing you into OBIEE they should be giving you at least 1 class. The report building stuff is easy enough to pick up, but if you are responsible for the management of the server, you need a class.. there is just so much to know about it.

I have worked in the RPD and reports/dashboard building side of things for 2 years. and im still learning stuff (usually the limitations of OBIEE). We have a whole nother TEAM(TEAM) of people who manage the databases and server side.

Resources:

Get a subscription to METALINK from oracle to issue service requests and look up bug fixes etc.

https://login.oracle.com/mysso/signon.jsp

Blogs:

http://www.rittmanmead.com/
http://gerardnico.com/

There are also youtube videos to explain simple stuff for setting up and RPD etc. You can also download an entire sample setup of OBIEE 11g from oracle.. its a huge download 50gb or something like that, but it has database, RPD, sample reports. all in a virtual machine. You can spend a week setting it up just to have examples to work from.

There is plenty of resources, but to give 1 generalized resource is difficult, you need to search for specific things you need to do. "Installing obiee11g on linux" "importing meta data into RPD"

If you need books on Data Warehousing and explanations of STAR schema and data denormalization I suggest reading up on kimball method:

http://www.amazon.com/The-Data-Warehouse-Toolkit-Dimensional/dp/1118530802/ref=sr_1_1?ie=UTF8&qid=1377213718&sr=8-1&keywords=kimball

and

Inmon

http://www.amazon.com/Building-Data-Warehouse-W-Inmon/dp/0764599445/ref=sr_1_2?ie=UTF8&qid=1377213827&sr=8-2&keywords=inmon

They have different philosophies for data warehousing i personally subscribe to the Kimball method because it supports rapid development better.


I'd like you to know but not discourage you, this is a large undertaking for 1 person. We manage 2 RPD's and 2 sets of dashboards for a custom reporting application we also do the ETL and warehousing. The whole warehouse was set up by a team, then we moved in ETL is handled by another team of people and we have a team doing reporting, then there is management and functional. So building out an OBIEE implementation from the ground up doing warehousing is a huge undertaking. There is another team of people doing server management and upgrades, and migrations.

This is at least a 3 man job, with each person being specialized. Push for RPD traning, Server managment Traning, and dashboard design Training. Warehousing methods and ETL work is another story.

SQL Queries for Mere Mortals is an excellent beginner's read front to back. The same guy wrote a database design book, which I did not find as helpful.

As for software, it depends on what database system you end up using. I use SQL Server and a little MySQL, but I know PostgreSQL, SQLite, and many others are popular.

If you're learning indipendantly, I'd start with MySQL , as it is free (open source) and you will be able to learn the basics of SQL in any SQL database. It also has a good free GUI development tool, MySQL Workbench, and a robust online community.

Like any programming language, the best way to learn is to build something with it. So start thinking of something you want to build, so you'll have something to do once you know enough to play around.

Sure!

​

I think two classic books to start with is

1. Design of Everyday Things (https://www.amazon.com/Design-Everyday-Things-Revised-Expanded-ebook/dp/B00E257T6C/) and
   
2. Don't Make Me Think (https://www.amazon.com/Dont-Make-Think-Revisited-Usability-ebook/dp/B00HJUBRPG).
   
   ​
   
   Then I would move onto IDEO's Creative Confidence (https://www.amazon.com/Creative-Confidence-Unleashing-Potential-Within-ebook/dp/B00CGI3DWQ), which documents tons of different UX methods. Also, I haven't read it, but I've heard that Lean UX is a great book (https://www.amazon.com/Lean-UX-Designing-Great-Products-ebook/dp/B01LYGQ6CH).
   
   ​
   
   Oh and to learn HTML, CSS, and JS (if you don't know them already), these are AMAZING reads: https://www.amazon.com/Web-Design-HTML-JavaScript-jQuery/dp/1118907442/ref=sr_1_3?crid=1QXNLBZ2V6GL8&keywords=learn+html+css+javascript&qid=1558328362&s=gateway&sprefix=learn+html+css+ja%2Caps%2C-1&sr=8-3
   
   ​
   
   With that said, I know books are a big commitment so here's a random assortment of UX articles I've bookmarked over the years to get you started (some may be a little old but should still hold up from a process standpoint):
   
   
3. https://uxplanet.org/user-experience-design-process-d91df1a45916
   
4. https://uxplanet.org/ux-is-process-actionable-user-insight-9c17107887bd
   
5. https://uxplanet.org/ux-is-process-designing-from-a-creative-brief-62f8588cb6f2
   
6. https://www.interaction-design.org/literature/article/task-analysis-a-ux-designer-s-best-friend
   
7. https://uxmastery.com/how-to-write-screeners-for-better-ux-research-results/
   
8. https://library.gv.com/get-better-data-from-user-studies-16-interviewing-tips-328d305c3e37?gi=82762a521a6
   
9. https://www.nngroup.com/articles/diary-studies/
   
10. https://uxdesign.cc/6-storytelling-principles-to-improve-your-ux-737f0fc34261
    
11. https://www.usertesting.com/blog/storytelling-in-ux/
    
12. https://www.nngroup.com/articles/interviewing-users/
    
13. https://medium.com/user-research/never-ask-what-they-want-3-better-questions-to-ask-in-user-interviews-aeddd2a2101e
    
14. https://www.smashingmagazine.com/2010/01/better-user-experience-using-storytelling-part-one/
    
15. https://www.bitovi.com/blog/10-best-practices-usability-testing-within-agile-teams
    
16. https://www.nngroup.com/articles/microsoft-desirability-toolkit/
    
17. https://www.nngroup.com/articles/desirability-reaction-words/
    
18. https://lean-product-design.18f.gov/3-identify-assumptions/
    
19. https://lean-product-design.18f.gov/index.html
    
20. https://www.justinmind.com/blog/interaction-design-frameworks-do-you-need-one/
    
21. https://medium.com/ruxers/building-block-design-a-modular-design-strategy-for-uxers-927f63eec90c
    
    ​
    
    There's a lot more where that came from, so let me know if you get through that and are craving more material.
    
    ​
    
    Here are a couple videos as well:
    
    
22. https://vimeo.com/7099570?utm_source=gdev-yt&utm_medium=video&utm_term=&utm_content=conductingresearch&utm_campaign=firstthingsfirst
    
23. This is a youtuber I follow who can teach you everything you need to know to get started in the design space (though she heavily focuses on digital design): https://www.youtube.com/user/charlimarieTV
    
    ​
    
    Finally, here's a very very short article I wrote myself that provides a quick intro into human centered design: http://www.jdktech.com/human-centered-design/
    
    ​
    
    As you dive into this, note that user interface design and user experience design are different things--although they overlap and rely on each other in various ways. You can be a user interface designer (in which case I would recommend different reads), a user experience designer, or both. I'm a full stack designer, which means I specialize in all sides of the product life cycle, including research, validation, design, product management and development.
    
    ​
    
    Hope this helps! Let me know if you have any other questions!

Believe it or not, attitude is half (if not more) of the battle. Keep doing what you are doing to continuously expand and build upon your skills.

With that said, I cannot stress highly enough taking a look at the Kimball Group Reader. It is chock full of real-world scenarios and is structured in a way that lends itself great to newcomers and seasoned pros alike. I think this will help to supplement what you are learning with the AdventureWorks system at the moment.

Once you familiarize yourself with SQL Server, I would recommend researching Oracle (Database, OLAP, OBIEE) and other technologies to better understand how they are alike, but also how they differ.

A cool way to learn more about data analysis is to try and apply it to something that interests you and expand from there. For example, if you like sports, you can mine football, baseball, etc... statistics for analysis. Find something that interests you and it may help reinforce your learning, especially on the parts that you may not find as satisfying to learn.

My background: I have been in Data Warehousing for about 8 years now and in my current role I flex between an Oracle DBA and DW Architect.

Best of luck to you and continue to strive learning new things!

It's hard to provide a full answer just based on available information, but roughly you have many different ways to achieve what you have in mind.

Some families of ways to handle this:

• ETL (Extract Transform Load) -> extract from CSV, during the process transform / clean / remap any field, if you don't do incremental reload you could also dedupe in the transform step, then load a "clean dataset" into either Postgres, ElasticSearch, etc
  
• ELT (Extract Load Transform) -> extract from CSV, dump right into ES or PG (mostly unchanged), then modify there (or query a "temporary dataset" to do a sort of ETL, clean / filter etc, and pour the data into a more "final" destination in the same datastore
  
  What's the most adequate way to do this depends on various factors:
  
  
• Do you want to deduplicate inside a single CSV (which can be achieved in memory before loading), or cross-CSVs (in which case you need a business key, with unique constraint, and do "upserts", or at least verify if you must drop the rows by checking id presence before)
  
• Do you have many different CSV formats or are them quite different? (if they are quite different, it's often more easy to go ETL, to have a very flexible & well tested way to verify the mappings & conversions etc)
  
• Are the outputs mostly largely similar with a bit of different fields, or mostly completely different?
  
  Finally, here are some tools which can help:
  
  
• My own gem https://www.kiba-etl.org (which I use both for ETL & ELT scenarios)
  
• Ruby Sequel https://github.com/jeremyevans/sequel (which is actually used by my upcoming Kiba Pro offer for database related tasks)
  
• pgloader https://github.com/dimitri/pgloader
  
• embulk http://www.embulk.org/docs/
  
  If you are into this for the long term, it can be worth reading a book that I often mention, which is the ETL book by Ralph Kimball. While quite old, it provides interesting patterns.
  
  Happy to detail this more if you provide more input!

Awesome! I kind of fell into the job. I was initially hired as a web developer, and didn't even know what BI was, and then got recruited by one of the BI managers and fell in love. To me, it is one of the few places in IT where what you create will directly impact the choices a business will make.

Most of what I do is ETL work (taking data from multiple systems, and loading them into a single warehouse), with a few cubes (multidimensional data analaysis) and SSRS report models (logical data model built on top of a relational data store used for ad hoc report creation). I also do a bit of report design, and lots of InfoPath 2010 + SharePoint 2010 custom development.

We use the entire Microsoft BI stack here, so SQL Server Integration (SSIS), Analysis (SSAS), and Reporting Services (SSRS). Microsoft is definitely up and coming in the BI world, but you might want to try to familiarize yourself with Oracle BI, Business Objects, or Cognos. Unfortunately, most of these tools are very expensive and not easy to get up and running. I would suggest you familiarize yourself with the concepts, and then you will be able to use any tool to apply them.

For data warehousing, check out the Kimball books:

Here and here and here

For reporting, get good with data visualizations, anything by Few or Tufte, like:

Here and here

For integration, check these out:

Here and here

Also, if you're interested in Microsoft BI (SSIS, SSAS, SSRS) check out this site. It has some awesome videos around SSAS that are easy to follow along with.

Also, check out the MSDN BI Blog: http://blogs.msdn.com/b/bi/

Currently at work, but if you have more questions, feel free to shoot me a message!

Mitchandre has an excellent point. This program is called an REU or Research Experience for Undergrads, and most professors will really love having an eager undergraduate for the summer to learn more. I am a computational chemist pursuing my PhD at Georgia Tech with Dr. Sherrill, and I know that we are looking for REU students every summer. I have previously worked with Dr. Robert Harrison at the University of Tennessee/Oak Ridge National Labs and he also has REU students most summers.
Here is the REU program: http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5517&from=fund
If you are just interested in learning some computational chemistry for yourself, a book that I have found to be extremely useful and basic enough to understand at any level is Introduction to Computational Chemistry by Frank Jensen: http://www.amazon.com/Introduction-Computational-Chemistry-Frank-Jensen/dp/0470011874/ref=sr_1_1?ie=UTF8&s=books&qid=1267759772&sr=8-1

If you really wanna try and get your feet wet, try applying for an REU with any professors you can contact, plus its a great way just to see a different part of the country for a summer! Good luck

A graph theory project! I just started today (it was assigned on Friday and this is when I selected my topic). I’m on spring break but next month I have to present a 15-20 minute lecture on graph automorphisms. I don’t necessarily have to, but I want to try and tie it in with some group theory since there is a mix of undergrads who the majority of them have seen some algebra before and probably bored PhD students/algebraists in my class, but I’m not sure where to start. Like, what would the binary operation be, composition of functions? What about the identity and inverse elements, what would those look like? In general, what would the elements of this group look like? What would the group isomorphism be? That means it’s a homomorphism with a bijective function. What would the homomorphism and bijective function look like? These are the questions I’m trying to get answers to.

Last semester I took a first course in Abstract Algebra and I’m currently taking a follow up course in Linear Algebra (I have the same professor for both algebra classes and my graph theory class). I’m curious if I can somehow also bring up some matrix representation theory stuff as that’s what we’re going over in my linear algebra class right now.

This is the textbook I’m using for my graph theory class: Graph Theory (Graduate Texts in Mathematics) https://www.amazon.com/dp/1846289696?ref=yo_pop_ma_swf

Here are the other graph theory books I got from my library and am using as references: Graph Theory (Graduate Texts in Mathematics) https://www.amazon.com/dp/3662536218?ref=yo_pop_ma_swf

Modern Graph Theory (Graduate Texts in Mathematics) https://www.amazon.com/dp/0387984887?ref=yo_pop_ma_swf

And for funsies, here is my linear algebra text: Linear Algebra, 4th Edition https://www.amazon.com/dp/0130084514?ref=yo_pop_ma_swf

But that’s what I’m working on! :)

And I certainly wouldn’t mind some pointers or ideas or things to investigate for this project! Like I said, I just started today (about 45 minutes ago) and am just trying to get some basic questions answered. From my preliminary investigating in my textbook, it seems a good example to work with in regards to a graph automorphism would be the Peterson Graph.

thenewboston.org is a really good tutorial website. I like the Head Start HTML & CSS book, then the O'Reilly book, PHP,mySQL,JavaScript, and CSS (all in one book)

Here is the link to the book. I am on chapter 4 and so far it is pretty good. They explain everything like you have never touch it before, which is good.

http://www.amazon.com/Learning-MySQL-JavaScript-Step---Step/dp/1449319262/ref=sr_1_2?ie=UTF8&qid=1343577123&sr=8-2&keywords=learning+php%2C+MySql%2C+and+JavaScript

Oh, and here is the one to the Head First HTML & CSS one
http://www.amazon.com/Head-First-HTML-Elisabeth-Robson/dp/0596159900

If you read both of these books, you will be well prepared to tackle web development projects. Then, when you want to learn more about a programming language (Like JavaScript) you can either buy the JavaScript book from O'Reilly, or watch the more advanced TheNewBoston tutorial videos.

Good luck!

Hi,

I am currently a grad student in comp/theory.

A background in programming is not necessary, but you may find yourself wanting to get familiar with programming for data analysis. You should feel comfortable in the terminal to begin something like this (but I've seen people with almost no computer skills learn to run MD simulations within a few weeks of struggle).

The points I give below apply to most questions of this sort.

A good starting place is considering what do I want to simulate?
Consider the underlying physics. If you can write the formulas of what you want to observe with statistical mechanics consider molecular dynamics or monte carlo. If you require quantum mechanics use post Hartree-Fock or DFT.

Do you want to simply look at a change in structure? MD will work. Do you want to look at the process of polymerization? That requires bond formation which requires quantum mechanics. A note: SCF is not orthogonal to MD; there exists QM/MD origrams such as terachem but its sounds fairly impractical to apply to a polymer.

Lets say you wanted to observe the unfolding of a polymer w.r.t. temperature. This could be observed with molecular dynamics. Now you need to consider what program to use. I don't know your system but NAMD is a good starting place because it is fairly user friendly. If you'd like some reading suggestions I'd suggest skimming Jensen's comp chem Let me know if you have more questions

DISCLAIMER:
I am a QM guy specifically quantum Monte Carlo, but I work closely with NAMD users

The book Learning PHP, MySQL, JavaScript, CSS & HTML5 was one of the most useful PHP books I read as a newcomer to PHP. It's very basic but it teaches how you can start using PHP to do useful and interesting things.

After making it though that book, I think PHP Objects, Patterns, and Practice is a really good next step. It will help you learn to design, organize, and write your code to a more professional standard. It will also help you better understand the workings of a PHP framework.

Well, it's my job, so definitely I can recommend some resources for you to learn from.


Customer Manipulation - Chloe Thomas

Seductive Interaction Design Creating Playful, Fun, and Effective User Experiences - Stephen Anderson

Gamify How Gamification Motivates People to Do Extraordinary Things - Brian Burke(2014)

Tested Advertising Methods

The Irresistible Offer How to Sell Your Product or Service in 3 Seconds or Less - Mark Joyner 2005

Brainfluence 100 Ways to Persuade and Convince Consumers with Neuromarketing - Roger Dooley

No need to thank me Jeff Bezos, you rich smart man.

>But basically after that I have to decide soon whether or not to focus on a Cisco, or Microsoft track at my college.

Sounds like your "college" is a joke. You should be learning the fundamentals that are responsible for the underpinnings of these technologies, not vendor recommendations that can easily almost be called propaganda. Especially at your beginner level, you wouldn't even touch technologies as part of your responsibility at the level taught by an MCSE or CCNA unless you work for an absolute moron.

The world is larger than Cisco and Microsoft. I suggest you look for actual academic books on Networking and Server Architecture to learn more useful things.

Computer Networking: A Top-Down Approach (6th Edition) https://www.amazon.com/dp/0132856204/ref=cm_sw_r_cp_awd_4Ev3wbE0EVGDH

Understanding and Deploying LDAP Directory Services, 2nd Edition https://www.amazon.com/dp/0672323168/ref=cm_sw_r_cp_awd_KFv3wbW3QNAGF

For future tracks:

Databases:

SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL (3rd Edition) https://www.amazon.com/dp/0321992474/ref=cm_sw_r_cp_awd_SGv3wbGCZ24FA

Fundamentals of Database Systems (7th Edition) https://www.amazon.com/dp/0133970779/ref=cm_sw_r_cp_awd_qHv3wb1YC95NS

Security:

Computer Security: Principles and Practice (3rd Edition) https://www.amazon.com/dp/0133773922/ref=cm_sw_r_cp_awd_ZHv3wb7J1YJKC

Blue Team Handbook: Incident Response Edition: A condensed field guide for the Cyber Security Incident Responder. https://www.amazon.com/dp/1500734756/ref=cm_sw_r_cp_awd_uIv3wbK1361D2

Hardware:

Upgrading and Repairing PCs (22nd Edition) https://www.amazon.com/dp/0789756102/ref=cm_sw_r_cp_awd_gJv3wbCKGA502

Problem Solving:

The Thinker's Toolkit: 14 Powerful Techniques for Problem Solving https://www.amazon.com/dp/0812928083/ref=cm_sw_r_cp_awd_XKv3wbKQFJK6Q

Best of luck. I recommend learning Shell languages and the basics of shell navigation and data manipulation techniques for various operating systems as well.

If you really want to go into business intelligence, I suggest you start with this book. This is pretty much the bible of data warehousing, which is the foundation of business intelligence. Kimball is one of the "founders" of data warehousing (along with Inmon). It's a large book, but it's actually really easy to read.

After you get the basics of admin tasks--(backup/restore and performance troubleshooting), jump into creating your own data warehouse from scratch. At this point, a lot of people say to learn SSRS to be able to build reports, but I disagree. I think it's important to learn OLAP cubes, the 3 basic models (ROLAP, HOLAP, and MOLAP), and jump into SSAS. SQL Server 2012 actually has a new BI model called "tabular model", which I honestly haven't touched, but it looks promising.

Finally, come join us at /r/BusinessIntelligence.

Thank you! This is exactly what I was looking for!!!! I didn't think anyone was going to give me a sufficient reply because there are a lot of books (sorry), but this is what I wanted. Where would you place the two books I linked, Principles and Techniques in Combinatorics and Introduction to Combinatorial Mathematics, Liu, in that list or would you consider studying them a redundant exercise? I also did not include this book in the list, but where would you place Problems from the Book and its accompanying Straight from the Book?

I will likely end up replacing the Graph Theory book I have in the list, by Berge, with Modern Graph Theory by Bellobas, since Berge doesn't have exercises, but I will assume it stays in the same order of the sequence.


I apologize for not initially including them. I did not realize that I did not. Also, are there any other topics you would recommend I cover for establishing a solid foundation. I didn't buy Rudin's Complex Analysis because I didn't know if that kind of thing was necessary. I don't even know what other branches of mathematics Complex Analysis relates to. There could be other topics I'm not aware of as well. Please don't hesitate to make more recommendations. I appreciate it.

tl:dr; make websites and learn Search Engine Optimisation

The context of my starting point is important, hence the detail:

I'm 26 now, and after leaving sixth-form I became the full time carer of my Dad and as a result haven't worked a normal job, now I'm trying to get in to work from basically step 0, and struggling massively to even get a rejection email/letter.

In that time I volunteered for a media charity that does hospital radio & internet radio, and I made 5 websites for them. When we launched an internet radio station from scratch, I made their website. Without me they would have needed to pay money we just can't spare. When you search "[Local area] radio" it's on the very first page of Google results, even ahead of 'radio directory' websites. Companies in our area are contacting us to work with us, they say they find us on Google. I learned everything I know in my free time without paying a penny. They tried to bring people on from a local college to assist me when my time was short and couldn't find anyone to do even basic tasks.

It's a great skill to have and it's in demand. It's easy to learn. There's pre-made software you can build upon such as WordPress. If you look in your local area it's very easy to find companies with shitty websites that can be convinced to pay you, and that is where I am currently heading. I picked up a huge book to finally formally learn PHP, JavaScript etc and next year I'll start my company. I already have a portfolio and proof my work is effective.

http://www.amazon.co.uk/Learning-MySQL-JavaScript-HTML5-Step/dp/1491949465

If you don't want to hunt down books, there are an infinite number of free resources for all skill levels.

http://www.w3schools.com/html/

https://www.codecademy.com/learn/web

If you're talking about a publicly available dataset, it will probably be in a delimited format, like .csv or .tsv. Go get MySQL or even the Microsoft SQL Server free version and then you'll just import your dataset into your server and then you can start querying. It's been a while since I've looked, but you might still be able to pick up a free copy of AdventureWorks here, which is a nice starter database w/ several tables so you can figure out how joins work. As for books, I like the Murach books. A nice one for conceptual stuff (first few chapters) is The Art of SQL

1 book by far is Andy Kirk’s. Data Visualisation: A Handbook for Data Driven Design https://www.amazon.com/dp/1526468921/ref=cm_sw_r_cp_api_i_rjx3DbDVRPFDN

It’s very broad and accessible yet substantial. That’s the book I recommend to anyone who need to read just one book.

2 is RJ Andrews book Info We Trust: How to Inspire the World with Data https://www.amazon.com/dp/1119483891/ref=cm_sw_r_cp_api_i_gmx3Db0FDG9DC.

This is a wonderful book that I read as an ode to visualization as a medium. It’s more artistic than Andy’s book both in its topic and its execution.

3 book depends on your specific interest. Dashboards/tableau? https://www.amazon.com/big-book-dashboard/s?k=big+book+of+dashboard.

Data art? https://www.amazon.com/dear-data-book/s?k=dear+data+book

Data journalism/ storytelling? Data-Driven Storytelling (AK Peters Visualization Series) https://www.amazon.com/dp/B07CCZPKV3/ref=cm_sw_r_cp_api_i_Msx3DbF1GZMG8

Science of visualization? https://www.amazon.com/Information-Visualization-Perception-Interactive-Technologies/dp/0123814642

Visualization from an academic point of view? https://www.amazon.com/Visualization-Analysis-Design-AK-Peters/dp/1466508914

D3js? https://www.amazon.com/Interactive-Data-Visualization-Web-Introduction/dp/1449339735

Yo, I'm not getting that image, but at a base level I can tell you this -

1. I don't know you if you know any R or Python, but there are good NLP (Natural Language Processing) libraries available for both
   
   Here's a good book for Python: http://www.nltk.org/book/
   
   A link to some more: http://nlp.stanford.edu/~manning/courses/DigitalHumanities/DH2011-Manning.pdf
   
   And for R, there's http://www.springer.com/us/book/9783319207018
   and
   https://www.amazon.com/Analysis-Students-Literature-Quantitative-Humanities-ebook/dp/B00PUM0DAA/ref=sr_1_9?ie=UTF8&qid=1483316118&sr=8-9&keywords=humanities+r
   
   There's also this https://www.amazon.com/Mining-Social-Web-Facebook-LinkedIn/dp/1449367615/ref=asap_bc?ie=UTF8 for web scraping with Python
   
   I know the R context better, and using R, you'd want to do something like this:
   
   
2. Scrape a bunch of sites using the R library 'rvest'
   
3. Put everything into a 'Corpus' using the 'tm' library
   
4. Use some form of clustering (k-nearest neighbor, LDA, or Structural Topic Model using the libraries 'knn', 'lda', or 'stm' respectively) to draw out trends in the data
   
   And that's that!

Hello, I would suggest to get a good book on SQL basics, install an open source free database server like MySQL on your mac (via DMG) http://dev.mysql.com/doc/refman/4.1/en/macosx-installation.html and just get the basic commands. Nothing to get certified in. The user side, you, are just going to perform basic commands. Database Administrators with bazillion years of experience (/s) will take care of the data servers for the users, you. Good luck.

A good book for you would probably be:
SQL Queries for mere mortals.

http://www.amazon.com/SQL-Queries-Mere-Mortals-Hands-/dp/0321992474/ref=sr_1_1?ie=UTF8&qid=1426695830&sr=8-1&keywords=sql+for+mortals

Any SQL certification for you, as a data analyst or a financial analyst, is completely useless. Just get the practical skills and show them on your interview.

By "expensive calculation", I meant DFT. A semiempirical method such as PM6, PM3, AM1, ZINDO, etc. is much, much quicker to run and can often get you a good starting geometry for a DFT calculation. You'll need to use your eyeballs for this part though.

You usually want the best basis set you can afford. In this case, you want it to include d and f angular momentum functions to properly describe the wavefunction at the cobalt. A small basis set like 3-21G will not work. However, 6-311+G(d,p) is too costly and may fail; even though it has higher angular momentum functions, the '+' means a set of diffuse functions has been added. This will result in orbitals that are quite large but "fuzzy", potentially causing false overlap of orbitals between atoms. It's important for many anions, but unnecessary here. Something intermediate like 6-31G(d) might be acceptable for a geometry.

If you want to learn more, I highly recommend this book, this book, and maybe most of all this book, depending on how much modeling you're required to do.

WHY DO YOU ASK MAINTAINS THE PROPER ATTITUDE OF A DECENT THING?

)

> From experience, one book is barely enough to get your feet wet

Ha! Definitely. I keep getting ideas for other books I should write.

I'd recommend the following as good general books to read. They're all good no matter what type of programming you do:

Code: The Hidden Language of Computer Hardware and Software
Code Complete: A Practical Handbook of Software Construction, Second Edition
The Pragmatic Programmer: From Journeyman to Master
The Mythical Man-Month
In the Beginning...was the Command Line
Secrets and Lies: Digital Security in a Networked World
User Interface Design for Programmers
Don't Make Me Think

That should keep you busy. :)

EDIT: Oh, also, you can read my other two Python books. One is on graphical games with Pygame and the other is on classical ciphers and how to crack them. http://inventwithpython.com

Work on your code/portfolio in your spare time and apply to any job that interests you.

In terms of how to improve your code, I'd take a look at these resources:

HTML/CSS

• http://learn.shayhowe.com/html-css/
  
• http://learn.shayhowe.com/advanced-html-css/
  
  Javascript
  
  
• http://javascriptbook.com/
  
  PHP/MySQL
  
  
• http://www.amazon.co.uk/Learning-PHP-MySQL-JavaScript-Javascript/dp/1491918667
  
  Or look online for any good resources for whatever technology you want to get into.
  
  Good luck :)

I'm pretty sure this book talked about how easy it was to scrape facebook before they locked down their API.

https://www.amazon.com/Mining-Social-Web-Facebook-LinkedIn/dp/1449367615/

A lot of people probably did this. I remember a talk given in my city, the guy had a few thousand people signup to his app and got millions of entries to his graph database

https://maxdemarzi.com/2013/01/28/facebook-graph-search-with-cypher-and-neo4j/

Popular game devs probably got oodles of data. Must have been awesome having a social graph of the US

Hi /r/datascience. I'm an aspiring data scientist and I'm trying to put together a data science course that's self-taught and can be done on one's time. Any pointers would be appreciated.

Section A: Foundations in Mathematics

• Calculus I
  
  
• Calculus II
  
  
• Calculus III
  
  
• Linear Algebra
  
  
• Statistics
  
  
• Probability Theory
  
  
• Bayesian Statistics
  
  Section B: Foundations in Computer Science
  
  
• Introduction to Computer Science and Programming using Python
  
  
• Python and/or R
  
  
• SQL
  
  Section C: Basic Data Science
  
  
• Intro to Data Science
  
  Section D: Advanced Data Science
  
  
• Machine Learning
  
  
• Deep Learning
  
  These are the courses/subjects I've gathered would be most important or useful for someone trying to learn data science. Below are the resources that can be used to learn these subjects.
  
  Section A Resources
  
  Khanacademy - General Calculus, Linear Algebra
  
  PatrickJMT - General Calculus, Linear Algebra
  
  Professor Leonard - Calculus I, Calculus II, Calculus III, Statistics
  
  MIT OpenCourseWare - Single Variable Calculus (I/II), Multivariable Calculus (III), Linear Algebra, Statistics, Probability Theory/Bayesian Statistics
  
  Harvard - Probability Theory/Bayesian Statistics
  
  Section B Resources
  
  Datacamp
  
  Dataquest
  
  Codeacademy
  
  Code School
  
  LearnPython.Org
  
  Kaggle
  
  Udemy
  
  Udacity
  
  Rmotr
  
  Section C Resources
  
  University of Michigan - Introduction to Data Science in Python
  
  Harvard CS109 - Introduction to Data Science
  
  R for Data Science
  
  Section D Resources
  
  Andrew Ng's Machine Learning
  
  Jose Portilla's Python for Data Science and Machine Learning
  
  Andrew Ng's Deep Learning Series
  
  Am I missing any important courses, free or otherwise? Any important books? Any concepts I'm completely forgetting about?
  
  I've been told this is missing real education in science itself. How can I incorporate that?

A list of some of my favorites so far..

Interactions of Color by Josef Albers

[The Elements of Typographic Style] (https://www.amazon.com/Elements-Typographic-Style-Version-Anniversary/dp/0881792128/ref=sr_1_3?s=books&ie=UTF8&qid=1485894924&sr=1-3&keywords=typography+book) by Robert Bringhurst

[Don't Make Me Think] (https://www.amazon.com/Dont-Make-Think-Revisited-Usability-ebook/dp/B00HJUBRPG/ref=sr_1_1?s=books&ie=UTF8&qid=1485895055&sr=1-1&keywords=dont+make+me+think) by Steve Krug (More of web design, but I loved the book. It can apply to all design.)

Logo Design Love by David Airey

Designing Brand Identity by Alina Wheeler

The Design of Everyday Things by Don Norman

These are just a few that I have really enjoyed.

SQL Server Developer, BI Backend Developer, Data Architect, stuff like that.

The Kimball Group Reader (Amazon link, without a referral or whatever) is a must read in the business of DWH and BI. Coincidentally, I haven't read it (impossible to get where I live), so don't ask me for an opinion if it's any good!

> I try to use the same principles of code cleanliness, separation of concerns, etc from .Net dev.

The first thing I imagine when I hear something like that is the person happily converting code into user defined scalar functions (I hope you don't use them). Not all rules from procedural development apply to SQL, remember that!

Eu sunt în general împotriva tutorialelor, cel puţin pe partea de programare. E greu de urmărit şi nu prea are de-a face cu procesul de învăţare ci mai degrabă cu cel de înmagazinare a unor cunoştinţe.
Cel mai bine ar fi la început să începi să citeşti o carte/un articol despre concepte ale programării în general pentru ca apoi să te apuci de sintaxa unui anume limbaj. Plus că îţi trebuie determinare şi multă răbdare.

Odată ce ai prins basicul limbajului, recomandarea mea ar fi să te implici într-un proiect la care poţi contribui cu cod. Codul ăsta va suferi o grămadă de transformări pentru ca la final să nu mai semene deloc cu cel de la început. Ştiu, sună descurajator dar ăsta e procesul natural prin care îţi îmbunătăţeşti skillurile.

Dacă vrei neapărat tutorial video, singura mea recomandarea ar fi PHP with MySQL Essential Training
with Kevin Skoglund
, însă repet: nu mi se pare cea mai fericită metodă de a învăţa programare. Cele mai sfinte lucruri în PHP sunt: cărţile, practica şi http://www.php.net/manual/en/index.php!

Dintre cărţi ţi-aş recomanda:

• Programming PHP
  
• Learning PHP, MySQL, JavaScript, and CSS: A Step-by-Step Guide to Creating Dynamic Websites
  
• PHP Objects, Patterns and Practice 3rd Edition (Expert's Voice in Open Source)
  
  Astea fiind spuse, îţi urez spor la treabă!

Some resources I found useful:

• This Github repository is a really good overview. Although it doesn't exactly give a deep understanding of any particular topic, it's a really good way of understanding the system design "landscape". After reading this, I had a much better idea of what I needed to study more.
  
• Designing Data-Intensive Applications is an awesome and thorough book that covers just about everything you need to know for a system design interview.
  
• Maybe a bit obvious, but CTCI's system design chapter is useful (although not enough on its own).
  
• It's in some ways a bit orthogonal to system design, but Computer Systems: A Programmer's Perspective gave me a much better idea of how the hell this machine I touch all day works. I think learning the things covered in here helped me speak with more confidence on system design.

If you want to a job upon graduation, you need the following items:

• Work experience. No work experience, no job upon graduation. Sucks, right? But that's a fact. Try to get as many internships as possible.
  
• Languages: Python (fucking hot right now; NumPy, Pandas, TensorFlow), SQL (you need to know this as the back of your hand), R, and SAS (maybe, depends from the employer; from what I have heard, SAS is dying out).
  
• Now, let's talk about cherry on top. Few things that may really spice up your resume are TA and research opportunities. Additionally, it would be nice to have some independent projects, e.g. Time Series analysis of the Toronto housing market.
  
  The problem with the Stats degree is that it is heavily theoretical. So, in order to balance it out, you need to get experience. Overall, I liked my experience with Stats, although I wish I spend more time on internships.
  
  To summarize: work experience, programming, research.
  
  Also, Machine Learning is hot right now. Pick up some books such as:
  
  
• Hands-On Machine Learning with ScikitLearn and TensorFlow
  
  
• Python for Data Analysis
  
  
• Python Data Science Handbook.
  
  Lastly, you gotta network like your life depends on it. Meetup.com and eventbrite.come have some pretty good Data Science/ML/Programming networking events where you can make connections and learn about the industry demands. Additionally, leverage the power of LinkedIn; create your profile and start asking people out for coffee in order to learn what they do, how they do it, what tools they use and for you to gain insight into the market demands and what you can expect upon graduation.
  
  May Central Limit Theorem work with all your distributions.
  
  Also, another thing that seems to be hot in financial markets is Risk Management. I would suggest you speaking with the Stats profs or Risk Management profs from Rotman in order to understand how you can leverage your Stats degree in Risk Management. Fantastic, here is one of the first things you can do for networking. Fuck, I wish I was back in uni.
  
  Sorry, just remembered. Hadoop is also pretty important as is Tableau (for data visualization).
  
  Ah, yes, experience. I don't know whether you spent the last part of 2017 and early part of 2018 on searching for internships. If not, keep searching you still have a slight chance to find some for this summer. Indeed and LinkedIn are pretty good sources. Lastly, try reaching out to recruiters from various organizations in order to learn if they have anything available. Now, if you don't find anything at all, like AT ALL, I would suggest either you take summer school and start looking for internships during either the Fall or Summer semesters OR contact the temp agencies to see what opportunities they have. Some opportunities may not be related to what you studied, but at least they will give you some work experience and your resume will not look as empty as it does now. Also, if I am correct, then U of T should have an alumni database. Try going through that database, find the alumni of interest, reach out to them, and ask them out for coffee to learn more about what they do and if they have anything available. Tick tock, tick tock.
  
  After some googling, indeed
  
  How am I doing? I am depressed man, I am fucking depressed. But, TensorFlow is keeping me awake.

• Clean code (mentioned elsewhere)
  
• The Mythical Man Month
  
• Code: The Hidden Language of Computer Hardware and Software
  
  Docker or Kubernetes:
  
  
• Docker Deep Dive
  
• The Kubernetes Book
  
  ​
  
  Data Science, Machine Learning:
  
  Hands-On Machine Learning with Scikit-Learn and TensorFlow
  
  
• Now that you understand Python and the applicable libraries, you can actually use it for ML
  
  Python for Data Analysis
  
  
• Fantastic for learning Python and growing familiar with the libraries you’ll use in data analysis. It is from the creator of the Pandas framework.
  
  Python Data Science Handbook
  
  
• Great overviews of Juypter notebooks, NumPy, Pandas, Matplotlib, Scikit-learn
  
• Free lite version & code from the author here.
  
  Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
  
  
• So helpful for explaining the business use case for ML and data science to non-technical individuals
  
• Also helps boil down problems into data science terms, and realize if it really is an ML problem
  
  I put together a list of resources on my blog.

After you finish that and are comfortable in python check out Python Data Science Handbook. I am not a data analyst, I am a PhD student doing research in fields that generate/require a lot of data.

The handbook goes over pythons numpy package and then gets into pandas. Pandas should be the tool you want to learn. Under the hood it uses numpy a lot so don’t skip the first half. Numpy implements a lot of matrix operations in FORTRAN/C if you use it properly (avoid loops when possible) it is incredibly efficient on large datasets.

While you are learning python I highly reccomend using jupyter lab.

Good luck!

Hhm. Well, first of all, I think you might have a hard time finding a book that will teach about both design and web development. Each of those are complicated enough to write separate books on. I think you'll be better off by finding two separate books (one on web dev, one on design) than finding one that combines both.

A kind of the same goes for Web. Dev. This is such a broad term, that you will hardly find any book that tries to cram in every possible aspect of web development. If you are a bit more specific and focus on a specific technology (like NodeJS, ASP.net with Angular or just plain old PHP, MySQL and JavaScript ) you'll get more value for money. There are more generic books out there, but the technologies (especially for web dev) change almost daily and books simply can't keep up with that. If you'd ask me, I think you'll be much better off having a good understanding of JavaScript in general before you move on to a specific stack or framework.

My suggestion would be to go to a library, walk down the aisle scanning each graph theory textbook for a few minutes and then choose one which clicks. Having access to exercises is super important (accompanying solutions is nice.)

Having access to a few textbooks is nice because if you get stuck on a concept in your 'main' text you can see if the others explain the idea better (wikipedia is also good for this.) Be alert for problems arising from differences in notation if you do this though.

Free online text book: http://diestel-graph-theory.com/basic.html

One I purchased: http://www.amazon.com/Modern-Graph-Theory-Bela-Bollobas/dp/0387984887

Combinatorics via exercises: http://www.amazon.com/Combinatorial-Problems-Exercises-Second-Lovász/dp/044481504X

Check a university library for copies of the latter two.


University courses:
http://www1.maths.leeds.ac.uk/~pmt6sbc/3032/3032.html
http://users.utu.fi/harju/graphtheory/graphtheory.pdf
http://www-math.ucdenver.edu/~wcherowi/courses/m4408/gtln.html
http://www.personal.psu.edu/cxg286/Math485.pdf
http://www.warwick.ac.uk/~masgax/notes.pdf
http://www.cs.elte.hu/~karolyi/GT/index.html
http://ocw.mit.edu/courses/mathematics/18-315-combinatorial-theory-introduction-to-graph-theory-extremal-and-enumerative-combinatorics-spring-2005/

I've had the experience where I was turned down for a $80k/y job because they straight up didn't like me and I passed a $155k/y interview with a palindrome check question.

As software guys I think to one degree or another we're all on some sort of a spectrum :) What makes you good at this job is always going in 100%, all-or-nothing, winner-take-all and the reality of the matter is that it's not actually like that. Don't take a single loss like that's going to be your life now. It's a little easier to see if you come from the background I come from (immigrant) but I get it.

Imagine that you fail 5 more interviews and then, after that, you are guaranteed to make 200k working 30 hours remotely (it happens)

You can now go live your life anywhere on the planet and crush it. It just has to be 5 though, not 4. If you imagine this to be true, you'll suddenly see how that lifts you out of your negative frame of mind.

Meanwhile, focus on things you can control:

• Read Elements of Programming Interviews in Python (or whatever flavor you prefer) because it's a very comprehensive book that's easily accessible
  
• Coding problems in Ruby is also good and very succinct (if you care about Ruby, but it's thorough)
  
• Exercise
  
• Hang out with friends, get different perspectives like on this forum, although reddit in general is very negative and cancerous
  
  Work on that, remain focused and next thing you know you'll be off the market
  
  Edit: Also check out The Senior Software Engineer and Designing Data-Intensive Applications because those are key to everything but "leetcode" stuff.

This is the book I'm following. I was not very familiar with d3.js beforehand, but it serves as a solid introduction to the core concepts. Very easy to read and hands-on approach. The first three chapters (around 60 pages) are introductions to html, css, javascript, with some descriptions of basic syntax and whatnot. Starting chapter 4 it's pure D3.

Building scatter diagrams, bar charts, geodata, representing graphs with interconnected nodes, all sorts of fun stuff.

Seductive Interaction Design: Creating Playful, Fun, and Effective User Experiences

Not SQLServer specific, but Joe Celko's "SQL For Smarties" is a great reference for all things SQL: http://www.amazon.com/Joe-Celkos-Smarties-Fourth-Edition/dp/0123820227

http://www.amazon.com/The-Kimball-Group-Reader-Relentlessly/dp/0470563109

This a great book. Bite size chunks explaining why to do a warehouse and how. Pretty much any Kimball book it seems good.

I can totally believe that that code made it to production, especially while a site is still growing, but if they needed an expert to tell them not to use LIKE queries...

The book on SQL Antipatterns has my favorite cover ever, and it's a great presentation.

Pixel Perfect Precision handbook for UI basics.

Seductive Interaction Design is also a good read.

Visit Dribbble, Behance, Codepen etc. for inspiration.

What kind of resources are you looking for: books, online tutorials, cheatsheets, other?

Is there a language or technology you are specifically using or looking at using?

If you are using R I would recommend parts of Hadley Wickham's "R for Data Science: Import, Tidy, Transform, Visualize, and Model Data". Specifically the chapters on Data Import, Transformation and Tidy Data.

If you have any specific questions feel free to ask.

The chapters in question available for free online:

https://r4ds.had.co.nz/data-import.html

https://r4ds.had.co.nz/transform.html

https://r4ds.had.co.nz/tidy-data.html

To buy a physical copy of the book:

https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ref=sr_1_1?crid=3EQZKAWKO7ZW9&keywords=r+for+data+science&qid=1574185159&sprefix=r+for+d%2Caps%2C232&sr=8-1

Edit:

Full github repository for book source code:

https://github.com/hadley/r4ds

The most important reading from a database design perspective, IMO, is one of Kimball’s books:

https://www.amazon.com/Data-Warehouse-Toolkit-Definitive-Dimensional/dp/1118530802

It’s less technically focused, and more focused on how to build good datasets. It’s an older text so it’s references to specific technologies are a bit out of date, but when it comes to describing how to design particular schemas (or at least speak the language of people who design schemas), it’s pretty much canon.

Great, thanks. A few days ago I asked on here about recommended MySQL books, one of the ones suggested was Bill Karwin's SQL Antipatterns. I've been reading through it and one of the topics discussed were intersection tables so I've been trying to put what I've learned into practice.

Here are all the local Amazon links I could find:


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Dimensional modeling is under valued in today's climate. Any complex models on a large scale will be more effective when modeled optimally.

https://www.amazon.com/Data-WarehouseÂ-ETL-Toolkit-Techniques-Extracting/dp/0764567578

First don't think of this as "DBA" stuff - you're a developer, you need to know database technology, period. Read this rant by Dennis Forbes in response to Digg's CTO's complaints about databases it's very reminiscent of TFA.

Read Data and Reality by the late William Kent (here's a free copy) and get a fundamental understanding of "information" vs. "data". Then read Information Modeling and Relational Databases to pickup a couple practical approaches to modeling (ER & OR). Now read The Datawarehouse Toolkit to learn dimensional modeling and when to use it. Practice designing effective models, build some production databases from scratch, inherit some, revisit your old designs, learn from your mistakes, write lots and lots and lots of SQL (if you want to get tricky with SQL I suggest to pickup Celko's SQL for smarties - it's like the Hacker's Delight for SQL).

Many strange models you may encounter in the wild are actually optimizations. Some are premature, some outright stupid, and some brilliant, if you want to be able to tell one from the other then you're going to dive deep into internals. Do this generically with Modern Information Retrieval and Managing Gigabytes then for specific RDBMSs Pro SQL Server Internals, PostgreSQL Internals, Oracle CORE, etc.

Reflect on how awesome practically every modern RDBMS is as a great technological achievement for mankind and how wonderful it is to be standing on the shoulders of giants. Roll your eyes a little bit whenever you overhear another twenty-something millenial fresh CS graduate who skipped every RDBMS elective bleat about NoSQL, Mongo, whatever. Try not to fly into murderous rage when another loud-mouthed know-nothing writes at length about how bad RDBMS technology is when they couldn't be bothered to learn the most basic requisite skills and knowledge to use one competently.

Today I stumbled upon a free Kindle Python book set from Amazon here. Maybe it might interest you?

I'd strongly suggest that you get the book SQL Antipatterns.

Specifically Polymorphic Associations starting on slide 32. It's detailed in the book, but the slide gives you some good information.

Basically, solution #3 where you use a base parent table. Store the content, title and date in a common "content" table, then store the content-specific information in sub-tables.

You might look at the O'Reilly book "Mining the Social Web". I've found it very helpful and the author has even responded to my questions about how to get the virtual machine with the ipython notebooks up and running. Has code examples, explanations about the underlying technologies, and intros to things like natural language processing included.

http://www.amazon.com/Mining-Social-Web-Facebook-LinkedIn/dp/1449367615

Hoowhee, how did this text get so... wally.

Bots are usually (fairly) simple programs, so Python will make it easy to get at all the common functionality you want (maybe looking for pattern matches in a piece of text, some math/analytics, saving files to your hard drive, converting images...) and in practice you'll mostly only be limited by what you can figure out how to do in your language of choice, regardless of the bot you're writing.

Wherever possible, you should use official APIs (which will often support Python these days), or at least third-party APIs that are built on top of the official ones. The APIs are sort of like a mediator between your bot and the service, or a menu of remotely-accessible functionality -- for twitter it might include things like "get the list of tweet IDs posted by this user ID in the last month" and "get the full text and metadata for this tweet ID." The set of functionality in that API determines what is and isn't possible for your bot to do (and depending on the service, it might actually hide a lot of complexity around sending messages to multiple servers, authenticating the request, etc)

When there's no API (or if the official API doesn't let you do something that you know should be possible) you usually have to switch to scraping. It's error-prone (could break any time) and frowned on by a lot of services (which is why you have to think about rate limiting and bans -- you may well be violating their terms of service, and either way you're using the service in unintended ways that might interfere with its normal functioning). "Unofficial APIs" are often just scrapers under the hood, tidied up into something that looks more like a normal API. I've written a ton of little scrapers in Python -- it really is a great tool for the job.

I suppose the other case is that some services can be built in standardized ways, so you don't need an official API from that particular company, because anyone else's API for that standard should be interoperable. That's common for databases, for example, but probably not the services you're talking about -- the popular web services are usually either proprietary, or a "standard" they invented that no one else actually uses, so you're basically stuck with the official API anyways.

For a lot of examples of integrating with public APIs, you can try Mining the Social Web from O'Reilly. I didn't actually spend a lot of time with that book personally (I wasn't expecting the sort of "cookbook" format with lots of examples and code) but it might cover some of the APIs that you're interested in.

There is That book coming out in 10 days by Jake VanderPlas. I haven't read it yet (obviously) but his youtube lectures are great.

My vote would be D3 over out of the box libraries like highcharts.

Since you're focusing on statistic, I'm guessing you'll want to do some decent custom visualizations to highlight certain aspects of the data. Typically most of the charting libraries work well for traditional vis (bar charts, etc) but fall apart trying to make more advanced visuals.

D3 has a learning curve, but it's not as high as people think. One book in particular really helped me understand how it works, and once you know, you'll never go back.

https://www.amazon.com/Interactive-Data-Visualization-Web-Introduction/dp/1449339735

I am currently reading this which has been OK so far.

I previously read this O'Reilly book which I found helpful. It does cover some stuff you already know but I found it handy when explaining things like sanitising and salting etc. Plus it goes about making a basic social site.

Do you expect more than a few thousand people will access this system. If not then definitely stick with an RDBMS. NoSQL is generally only appropriate if you need blindlingly fast reads, tolerably slow writes, and scalability with commodity hardware. RDBMSes give you balance of read and write throughput for a less-than-crazy number of users, and they make it far easier to maintain data integrity.

Working with relational data is as much art as skill. Even for something as simple as an inventory system (the 'Hello World' of databases) there are a number of choices to make and peculiarities to troubleshoot.

In addition to whatever database specific books you may need, I would suggest you pick up
The Art of SQL. It teaches how think about data and relationships declaratively and to understand complex data systems from the outside in.

If you have got time i will recommend you going through this book - Learning PHP, MySQL, JavaScript, CSS & HTML5: A Step-by-Step Guide to Creating Dynamic Websites

this book and this:

hash('ripemd128', $salt1.$password.$salt2);

The previous edition from 2012 recommended md5.

I guess having a unique salt for each password using password_hash is better than applying the same to all of them. Not sure if ripemd128 is good or not.

for years I've recommended going through SQL for Smarties which in the years since I had it seems to have grown to be three times its size, but nevertheless describes relational databases and SQL querying from the classical DBA perspective. He also has SQL Puzzle books that are also great. If you go through Celko's books you'll really have a sense for how a relational database was really meant to be used, and when you see someone touting MongoDB queries you'll just laugh your ass off.

I wouldn't go that far, but the book has little practical value. Date is very knowledgeable, but he writes like an academic - he can take any piece of prose and suck the life out of it.
The Art of SQL is a much better book.

I'd recommend doing mathematics, It's much important than learning a language. It helps you grab the logic of solving a problem.


Discrete Mathematics by Rosen is the best book from my experience.



Graph Theory by Bollobas is recommended by many but i prefer Graph Theory by Douglas West




Algorithms by Cormen. No introductions needed this book encompasses most of the problems you'll encounter.



However if you're keen on learning a C/C++/Java i'd recommend the Head First Series from O'Reily .




Goodluck!

I second Kimball's The Data Warehouse Toolkit. Definitely be familiar with DS&A as well as SQL and big data concepts including window functions, pivots, aggregations, map-reduce, spark, etc.

I list some other resources and my study guide in my post here.

Don't pay someone unless you can afford to hire them on Salary! Otherwise you will spend SO MUCH just trying to get it right. If you want to have a successful site you need to know how sites are built. That means learning PHP. Get a book, get determined, and go through the ENTIRE book.

I suggest this one

---------------------------------
Shameless Self Promotion:
Programming for Analysis

I really love these two books.
https://www.amazon.com/Database-Design-Mere-Mortals-Hands/dp/0321884493/
https://www.amazon.com/SQL-Queries-Mere-Mortals-Hands/dp/0321992474/

You should consider reading this book. Its a great primer on Dimensional Modeling

https://smile.amazon.com/Data-Warehouse-Toolkit-Definitive-Dimensional/dp/1118530802/ref=sr_1_1?s=instant-video&ie=UTF8&qid=1549073081&sr=8-1&keywords=kimball+dimensional+modeling

If you're looking for someone to go over the language one on one with you, you could try r/ProgrammingBuddies

Otherwise, you could buy SQL Queries for Mere Mortals which was incredible in understanding and writing queries in comparison to learning from the websites that I tried. You could probably get the book via "other means" if you want, as well. You can supplement the book with Google/StackOverflow searching.

If you want to try before you buy, you could use CodeAcademy's SQL course - I don't really like recommending CA to people but I found their SQL course to be useful for a general understanding.

Just out of curiously, why are you going the php route? Instead of rails, python (django) , node or asp.net mvc?

When buying books I normally check the Amazon reviews
http://www.amazon.com/Learning-MySQL-JavaScript-HTML5-Step/dp/1491949465

I also try to buy directly from O'Reilly if I can. They often have great sales (50% off ebooks and such) and their ebooks are 100% DRM free so I can use them on any device.

I'm not familiar with the book you mentioned, but just though I'd provide insight on my book buying process.

http://www.amazon.com/Introduction-Computational-Chemistry-Frank-Jensen/dp/0470011874/ref=pd_bxgy_b_img_b

This is a good book. Also you should become familiar with programs like Gaussian (http://www.gaussian.com/) and BOSS (http://zarbi.chem.yale.edu/software.html)

https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ seems like a good one.

Fundamentals of Database Systems, it covers a broad range of topics about databases including database design theory, normalisation and data modeling.

SQL Antipatterns is a really great book.

HTML.net , Code Academy, this book is really good... http://www.amazon.com/Learning-MySQL-JavaScript-HTML5-Step-/dp/1491949465/ref=sr_1_5?s=books&ie=UTF8&qid=1420926437&sr=1-5&keywords=HTML+css+javascript

and the subreddit /r/webdev for help, more tutorials, discussions and all of that. gl!

A well-thumbed book sitting on my desk. Yet, the post in question wasn't addressing optimization as such. It was more of an overview of models and design with optimization considerations.

(Another favorite of mine is The art of SQL.)

Mining the Social Web

Not exactly what you're looking for but it's very helpful, imo

Not as quick as OP's tutorial, but the "Interactive Data Visualization For The Web" book is good too.

http://www.amazon.com/Interactive-Data-Visualization-Scott-Murray/dp/1449339735

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann.

Amazing book for anyone who works on (or wants to work on) large scale applications.

If you want to read more about the topic, this book just got released https://www.amazon.com/gp/aw/d/B06XPJML5D/ref=ya_aw_dod_pi?ie=UTF8&psc=1 and it is pretty much a must read for back end developers.

I don't love the Dummies books for technical subjects; O'Reilly books are far superior. Their Python Data Science Handbook by Jake VanderPlas is worth its weight in gold, IMO.

Agreed, OP, you're massively overcomplicating this. If you learn a bunch of math and theory to try and become a database professional you will just come across as an academic rather than someone who can get work done. Learn how to get work done. Check out books like SQL Cookbook and SQL For Smarties to learn stuff that will actually help you do what you need to do.

You do want to have normalization down and basically understand set theory, but you're already doing that.

Buy some books.

Setup your own web server and practice making sites. For SQL, look for a book which teaches SQL, then install MySQL, create a database, and practice creating tables, populating them, and doing queries.

Seductive Interaction Design by Stephen P. Richardson is pretty good..

https://www.amazon.com/Seductive-Interaction-Design-Effective-Experiences/dp/0321725522/ref=sr_1_1?ie=UTF8&qid=1486488964&sr=8-1&keywords=seductive+interaction+design

http://www.amazon.com/SQL-Antipatterns-Programming-Pragmatic-Programmers/dp/1934356557/ref=pd_sim_b_3

http://www.amazon.com/Joe-Celkos-SQL-Smarties-Programming/dp/1558605762

http://www.amazon.com/Art-SQL-Stephane-Faroult/dp/0596008945/ref=pd_sim_b_4

http://www.amazon.com/SQL-Relational-Theory-Write-Accurate/dp/0596523068/ref=pd_sim_b_7

And then read a book on whichever dialect of SQL you're using, because they're pretty different.

Informatica is widely used for ETL tools, but more important is understanding the challenges. How to design staging tables, what update strategy to use, how to design restartable jobs, and so on. This book refers to data warehousing, but the techniques are applicable to most scenarios.

The only book I can think of that covers all of those technologies is Learning PHP, mySQL, and Javascript. Of course, since it is trying to cover a multitude of different topics it never really goes "in-depth" with any of them. But it could be a good place to start out.

I used data camp and I recommend it because it covers both programming in base R and the full tidyverse library. I did the R programming course and it covered everything from functional programming to object oriented programming in R.

If you don’t want to do a monthly subscription, purchase Hadley Wickams (author of the tidyverse) book R for Data Science

I think it would depend on your data and how its being used. There's a great book 'SQL Anti patterns' that explains different approaches, pros and cons and suggests alternatives: https://www.amazon.co.uk/SQL-Antipatterns-Programming-Pragmatic-Programmers-x/dp/1934356557

pe https://www.reddit.com/r/FreeEBOOKS/ am vazut

mai erau cateva freebie legate chiar de python

There are limits and boundaries, we(humans) are those limits and boundaries, our eye and our brain. Do you recon an interface IronMan Computer-like would work in real life? I don't think so ... At least not for someone below 280 IQ.

Let me put it in a different way. Is the computer in you DNA? No it's not. Is the computer in your past history(as human)? No it's not. Homo sapiens are 50.000 years old, computers/digital interfaces are 20-30 years old? First writing on a plane surface was 5210 years ago. First writing on a computer was ... let's say 100 years old.

Now ... what would be the easiest things for you brain to understand? What's in your DNA and what's not? If you think this is irrelevant you should study design (not design tools or other digital/print designs). You can start with this one: http://www.amazon.co.uk/Seductive-Interaction-Design-Effective-Experiences/dp/0321725522

It's cool and I agree with pushing the boundaries but not in a stupid way or an unlimited way (see Iron Man digital interfaces).

As humans, we are limited.

This is a book I wish I read years earlier:

SQL Queries for Mere Mortals

Python Data Science Handbook is awesome. Doesn't cover Scikit-Lean, but it covers Pandas (which inherently means Numpy), and some visualization stuff too.

It seems like you can use a date dimension here.

To read about multi-dimensional concepts: http://www.amazon.com/Data-Warehouse-Toolkit-Definitive-Dimensional/dp/1118530802/ref=sr_1_1?s=books&ie=UTF8&qid=1415023036&sr=1-1&keywords=the+data+warehouse+toolkit

Amazon has a 3 book kindle edition for free right now (you can use an app on mobile or your PC as well). I "purchased" it but haven't looked through it yet.

https://www.amazon.com/Python-Manuscripts-Programming-Beginners-Intermediates-ebook/dp/B07CQPHC1N/

You may want to read SQL for Smarties.

It does a very good job of stressing the importance of adjusting your thinking when you're working with a relational DB. If you approach SQL as if it were a procedural language, you will hate it, your results will suck, and DBAs (and devs who are competent at SQL) will make fun of you.

La scelta del linguaggio di programmazione dipende molto dal contesto e dalla applicazione specifica. R é ottimo per l'analisi statistica, ma appunto si adatta solo a quello.

Per iniziare, mantenendo una forte connessione con quello che desideri studiare, ti suggerisco python.

Leggi "Python Data Science Handbook: Essential Tools for Working with Data" e "Learning Python"

• https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057
  
• https://www.amazon.com/Learning-Python-5th-Mark-Lutz/dp/1449355730/Installa python 3.7 tramite Anaconda, ed usa Spyder come editor ( già incluso nella distribuzione ) . In alternativa PyCharm è ottimo ma richiede delle conoscenze più approfondite per l'installazione e la configurazione dell'ambiente e la creazione di ambienti virtuali.
  
• https://www.anaconda.com/distribution/
  
• https://www.jetbrains.com/pycharm/
  
  Impara a manipolare e filtrare dati con Pandas, Numpy, Scipy,
  
  
• https://pandas.pydata.org
  
• https://www.numpy.org
  
• https://www.scipy.org/
  
  Impara a mostrare dati preacquisiti con matplotlib, seaborn, bokeh,
  
  
• https://matplotlib.org/
  
• https://seaborn.pydata.org/index.html
  
• https://bokeh.pydata.org/en/latest/
  
  o dataset che possono evolvere rapidamente con pyqtgraph
  
  
• http://www.pyqtgraph.org
  
  Mi stavo quasi dimenticando, per analisi statistiche uso Statsmodels
  
  
• http://www.statsmodels.org/stable/index.html
  
  Quanto tempo serve? Non lo so. Io imparo linguaggi e librerie nuove ogni giorno perchè ogni mese disegno qualcosa di nuovo, diverso, migliorato.
  
  
  Edit: aggiungo un commento finale. Arrivati ad un certo livello di affinità con la programmazione, il linguaggio di programmazione scelto non importa quanto la disponibilità di librerie affidabili, ben documentate, e ben mantenute. Dal mio punto di vista avere buone librerie è essenziale perché creare ex novo una libreria ha un costo {temporale, di skills, di focus, etc..} che spesso preferisco allocare diversamente.

I doubt any courses you take would spend more than a day on the basics of a language. That's something you need to learn on your own. What's your background like? It sounds like you don't have much programming experience, so perhaps start with this. Then maybe this for learning numpy, pandas, and matplotlib.

EDIT: Didn't realize you were still in high school. I don't believe there's a specific data science undergrad program anywhere, but any STEM undergrad program will probably include an introductory programming course.

GUI/UI/UX design is a specialized skill that not many developers can do (similarly, a lot of designers don't necessarily know how to design and craft code).

I've probably designed what something looked like a couple times in my career, but it's never been a real component of any of my jobs.

However, if it's something you want to get into, your school should have courses like Human-Computer Interaction, and there are plenty of resources to jump into and get your feet wet:

• Don't Make Me Think by Steve Krug - this is one of the classics in web/ux design.
  
• Rocket Surgery Made Easy also by Steve Krug - Tackling usability problems
  
• /r/userexperience - The user experience subreddit
  
• UX StackExchange - Stack Overflow for usability/UX
  
• /r/web_design - The general web design subreddit

I strongly advise you to check out this book. Best thing I have read in my life. There you will find a lot of answers.

Actualy, this is one of the first things you get taught if you take a visualization class, Never ever alter the data. And the slope is a very basic property of the data.

> it simply wouldn't be effective communication to make the decrease look really small

Again, if the data doesn't provide a big decrease, don't make it look like it does.

e.g. Try reading this nice one. http://www.amazon.com/Interactive-Data-Visualization-Scott-Murray/dp/1449339735

Frank Jensen's Introduction to Computational Chemistry is, in my opinion, one of the best books out there for computational chemistry. Jensen's book does a great job introducing the concepts and equations in a way that doesn't feel like you need years of background in math and physics to understand. This book lived on my desk while I was in grad school. From what I've seen, most university libraries have a copy of it in their collection.

There are books out there that go into far more detail about the various methods and give detailed mathematical proofs, like Ira Levine's Quantum Chemistry, but those are very dense and, even as someone with a PhD in the field, intimidating.

The Data Warehouse Toolkit by Kimball was recommended to me as "The Source" for DW. I just started reading it, so no experience yet.

The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition https://www.amazon.com/dp/1118530802/ref=cm_sw_r_cp_apa_i_LZ-7CbHQTXGRM

Designing data-intensive applications by Martin Kleppmann has been recommended to me recently.

https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable-ebook/dp/B06XPJML5D

If it's something you might want to learn more on (as back end dev work can be very lucrative), I'd recommend a book, "The art of SQL". It's more than a simple text book or cookbook, it teaches you how to think about sql problems in the context of real world applications.

https://www.amazon.com/Art-SQL-Stephane-Faroult/dp/0596008945

edit Also pinal dave of SQL authority is a life saver, check out his blog at:
https://blog.sqlauthority.com/

I think the best first book you can get is Bill Karwin's SQL Antipatterns. That book alone will keep you from making most of the mistakes that come back to bite new designers.

I recommend [SQL Queries for Mere Mortals ($36.64)](SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL (3rd Edition) https://www.amazon.com/dp/0321992474/ref=cm_sw_r_cp_apa_nCQrybW9TPPNN) and [Database Design for Mere Mortals ($31.57)](Database Design for Mere Mortals: A Hands-On Guide to Relational Database Design (3rd Edition) https://www.amazon.com/dp/0321884493/ref=cm_sw_r_cp_apa_CDQrybA2508FS)

Both helped guide me through my masters program, and they are fairly affordable.

For anyone who wants to go beyond 'this is a select... this is an insert... this is a join..' check out this book:

http://www.amazon.com/Joe-Celkos-Smarties-Fourth-Edition/dp/0123820227

He always follows the SQL standard, but... some things don't implement it, so everything in this books is not guaranteed to work with all (or even any) RDBMS.

Try Seductive Interaction Design. It's less of a step-by-step instructional and more of a interaction theory guide.

I've always had high opinions of sql for mere mortals. I have the 1st edition kicking around somewhere...

Perhaps Bollobas' Modern Graph Theory?

• Beginners: Practical SQL Handbook or SQL Primer (Disclosure: I wrote the latter)
  
• Advanced: The Art of SQL and SQL Antipatterns
  
• Reference: Introduction to SQL or SQL Cookbook

I'd personally add
The Art of SQL

Not really suitable as a reference work though, but the information contained herein should be taught in school (but as evidenced by most developers' SQL skills, obviously isn't)

The Data Warehouse ETL Toolkit

Also The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data https://www.amazon.com/dp/0764567578/ref=cm_sw_r_cp_apa_lnUSAbDC5NK4X

Assuming you've already read the Data Warehouse Toolkit? If not, do. http://www.amazon.com/dp/1118530802

Look up the DMBOK and Ralph Kimball’s The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling https://www.amazon.com/dp/1118530802/ref=cm_sw_r_cp_api_r4XMBbY0729K9 .

>data warehouse toolkit

Can you confirm that this is the book you are referring to? Amazon Link

Here's the direct link to the book on Amazon.

You can buy direct from the publisher: http://shop.oreilly.com/product/0636920034919.do

But it's a bit cheaper on Amazon

As far as Python books, you should get these 2:
Python Data Science Handbook and Python Machine Learning.

Ah... I was thinking about getting that book. What did you think about it overall?

Just a link for future reference

Bücher:

https://www.amazon.de/Dont-Make-Think-Revisited-Usability-ebook/dp/B00HJUBRPG/ref=sr_1_4?ie=UTF8&qid=1479557141&sr=8-4&keywords=ux

https://www.amazon.de/Hooked-How-Build-Habit-Forming-Products-ebook/dp/B00NW01MKM/ref=pd_sim_351_3?_encoding=UTF8&psc=1&refRID=VPBHSSF5YYXVZWHXE2TT

https://www.amazon.de/Web-Fatale-gestaltest-widerstehen-Interaktion/dp/3836238985/ref=sr_1_3?ie=UTF8&qid=1479557277&sr=8-3&keywords=user+interface+design


https://www.amazon.de/UX-Research-Practical-Techniques-Designing/dp/149195129X/ref=sr_1_6?ie=UTF8&qid=1479557171&sr=8-6&keywords=ux

https://www.amazon.de/UI-Communication-Intuitive-Interfaces-Effective/dp/0123969808/ref=sr_1_6?ie=UTF8&qid=1479557114&sr=8-6&keywords=user+centered+design

link

Read this book:

http://www.amazon.com/Data-Warehouse-Toolkit-Definitive-Dimensional/dp/1118530802

Seriously.

If you want to be good at sql, you have to think in sets. Also you need to pic a platform to learn on because even tho SQL is a standard, the sql will look different on different platforms.

1. documentation of sql implementation. (ie books online for sql server)
   
   
2. http://www.amazon.com/Database-Depth-Relational-Theory-Practitioners/dp/0596100124/ref=sr_1_fkmr0_1?ie=UTF8&qid=1269299550&sr=1-1-fkmr0
   
   
3. http://www.amazon.com/Art-SQL-Stephane-Faroult/dp/0596008945/ref=sr_1_5?ie=UTF8&s=books&qid=1269299574&sr=1-5
   
   these books balance each other out. Start with Date first. Celko can get you into trouble in places.
   
   edit: i just realized that the author wanted to learn sql, not how start out designing databases. Whoops. Syntax can be learned anywhere. The previous books will discuss how to build properly built databases. However poorly built databases will stress you SQL-fu

Although I am not a statistician myself and given your background, some of my recommendations would be:

• All of Statistics for a concise treatment of well....all of statistics :p
  
  
• [Introduction to Statistical Learning/Elements of Statistical Learning] (https://www.amazon.com/Introduction-Statistical-Learning-Applications-Statistics/dp/1461471370/ref=sr_1_1?s=books&ie=UTF8&qid=1493070885&sr=1-1&keywords=introduction+to+statistical+learning) avaliable for free in the internet if you are interested in applying statistical methods with Machine Learning
  
  
• Introduction to Probability for a intro to probability theory which underlies most of statistics.
  
  
• One of either [Python Data Science Handbook] (https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057/ref=sr_1_1?s=books&ie=UTF8&qid=1493071026&sr=1-1&keywords=python+data+science+handbook) or [R for Data Science] (https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ref=sr_1_1?s=books&ie=UTF8&qid=1493071056&sr=1-1&keywords=r+for+data+science) for building programming chops in your language of choice Python or R.
  
  This should probably be enough for now but if you need more recommendations just say so :)
  
  Regarding the time series question, it's not my area of expertise but since time series analysis ends up employing many statistical methods, I think it can be considered an area of statistics (Statisticians around here correct me if I am wrong :P)

Seductive Interaction Design, Ordering Disorder: Grid Principles for Web Design