Add many courses in mathematics + virtual reality

Add a variety of courses (AI, maths, programming)

Add courses in AI and Linux

Add 'Udacity' to the course

online_courses/free/README.md

@@ -4,14 +4,17 @@
 
 * [Artificial intelligence & machine learning](#artificial-intelligence--machine-learning)
     * [First steps](#first-steps)
+    * [Deep learning](#deep-learning)
+    * [Machine learning](#machine-learning)
     * [Next steps](#next-steps)
-    * [Next steps: complementary topics](#next-steps-complementary-topics)
+        * [Complementary topics](#complementary-topics)
 * [Computer science](#computer-science)
     * [Algorithms](#algorithms)
     * [Blockchain technology](#blockchain-technology)
     * [Cloud computing](#cloud-computing)
     * [Security](#security)
 * [Learning strategies](#learning-strategies)
+* [Linux](#linux)
 
 <!-- vim-markdown-toc -->
 
@@ -26,15 +29,19 @@
 ### First steps
 - [AI for everyone](https://www.coursera.org/learn/ai-for-everyone) — Coursera. Lecturer: Andrew Ng.
 
-### Next steps
+### Deep learning
 - [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning) — Coursera. Offered by [deeplearning.ai](https://www.deeplearning.ai/).
-- [Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning](https://www.coursera.org/learn/introduction-tensorflow/) — Coursera. Offered by [deeplearning.ai](https://www.deeplearning.ai/).
-- [Linear Regression and Modeling](https://www.coursera.org/learn/linear-regression-model) — Coursera. Duke University.
+- [Intro to TensorFlow for Deep Learning](https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187) — by TensorFlow, on Udacity. *"Learn how to build deep learning applications with TensorFlow."*
+
+### Machine learning
 - [Machine Learning](https://www.coursera.org/learn/machine-learning) — Coursera. Lecturer: Andrew Ng. Offered by Stanford.
 - [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning) — Coursera. Offered by University of Washington.
 
-### Next steps: complementary topics
+### Next steps
+- [Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning](https://www.coursera.org/learn/introduction-tensorflow/) — Coursera. Offered by [deeplearning.ai](https://www.deeplearning.ai/).
+- [Linear Regression and Modeling](https://www.coursera.org/learn/linear-regression-model) — Coursera. Duke University.
 
+#### Complementary topics
 - [Self-Driving Cars Specialization](https://www.coursera.org/specializations/self-driving-cars) — Coursera. Offered by University of Toronto.
 
 ---
@@ -66,3 +73,9 @@
 ## Learning strategies
 - [Learning How to Learn: Powerful mental tools to help you master tough subjects](https://www.coursera.org/learn/learning-how-to-learn) — Coursera. McMaster University & University of California San Diego.
 - [Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential](https://www.coursera.org/learn/mindshift) — Coursera. McMaster University.
+
+---
+
+## Linux
+
+- [Introduction to Linux](https://www.edx.org/course/introduction-to-linux) — edX. *"Develop a good working knowledge of Linux using both the graphical interface and command line, covering the major Linux distribution families."*

websites/README.md

@@ -2,54 +2,80 @@
 
 <!-- vim-markdown-toc GFM -->
 
+* [Artificial intelligence](#artificial-intelligence)
+    * [Machine learning](#machine-learning)
+* [Computer science](#computer-science)
 * [Mathematics](#mathematics)
     * [Beginner topics](#beginner-topics)
     * [Calculus](#calculus)
     * [Linear Algebra](#linear-algebra)
     * [Online tools](#online-tools)
+    * [Statistics](#statistics)
 * [Programming](#programming)
+    * [iOS](#ios)
+        * [Swift](#swift)
     * [Julia](#julia)
     * [Python](#python)
+* [Startups](#startups)
 
 <!-- vim-markdown-toc -->
 
 ---
 
-# Mathematics
+# Artificial intelligence
+## Machine learning
+- [Machine Learning Crash Course with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) — Google. — *"Google's fast-paced, practical introduction to machine learning."*
+- [Machine Learning: 2014-2015](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) — University of Oxford.
 
-## Beginner topics
+---
 
-- [Khan Academy](https://www.khanacademy.org/) — Brush up on arithmetic, algebra, geometry, trigonometry, statistics & probability, calculus, differential equations, linear algebra.
+# Computer science
+- [Computer Science 162, 001 - Fall 2013](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iDrt_oPWfQ4-fjHm2KSSOPq) — UC Berkeley.
+- [Computer Science 188, 001 - Spring 2015](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iA4YSaTMfF_K_wvrKAY2H8u) — UC Berkeley.
+- [Computer Science 194, 024 - Spring 2013](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iB_5Q8G8kW5idSwNmXypmQE) — UC Berkeley.
+- [Computer Science 61B, 001 - Fall 2014](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iDVox3OKFhF4LxMHqpi2GS2) — UC Berkeley.
+- [Understanding Computers and the Internet](http://computerscience1.tv/2011/spring/) — Harvard Extension School. About hardware, Internet, multimedia, security, website development, programming.
 
 ---
 
-## Calculus
+# Mathematics
+- [Mathematics 16A, 002 - Fall 2013](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iCCCqDD9uTufr5I3Xtr3szk) — UC Berkeley.
 
-- [Calculus III](http://tutorial.math.lamar.edu/Classes/CalcIII/CalcIII.aspx) — *Here are my online notes for my Calculus III course that I teach here at Lamar University. Despite the fact that these are my “class notes”, they should be accessible to anyone wanting to learn Calculus III or needing a refresher in some of the topics from the class.*
+## Beginner topics
+- [Khan Academy](https://www.khanacademy.org/) — Brush up on arithmetic, algebra, geometry, trigonometry, statistics & probability, calculus, differential equations, linear algebra.
 
----
+## Calculus
+- [Calculus III](http://tutorial.math.lamar.edu/Classes/CalcIII/CalcIII.aspx) — *Here are my online notes for my Calculus III course that I teach here at Lamar University. Despite the fact that these are my “class notes”, they should be accessible to anyone wanting to learn Calculus III or needing a refresher in some of the topics from the class.*
 
 ## Linear Algebra
-
+- [Applied Linear Algebra 1](https://open.math.uwaterloo.ca/4?gid=314) — University of Waterloo (Canada).
 - Problem sets
     - [PDF] [Exercises and Problems in Linear Algebra, Portland State University](https://web.pdx.edu/~erdman/LINALG/Linalg_pdf.pdf), Version July 13, 2014
 
----
-
 ## Online tools
-
 - [Desmos](https://www.desmos.com/) — *"Graph functions, plot data, evaluate equations, explore transformations, and much more – for free!"*
 - [Symbolab](https://www.symbolab.com/) — *"Symbolab: equation search and math solver - solves algebra, trigonometry and calculus problems step by step."* **(:heavy_dollar_sign: requires subscription for all features)**
 - [Wolfram|Alpha](https://www.wolframalpha.com/) — *"Wolfram|Alpha is a computational knowledge engine or answer engine."* **(:heavy_dollar_sign: requires subscription for all features)**
 
+## Statistics
+- [Learn How To Put Statistics To Work](http://www.learner.org/courses/againstallodds/) — Annenberg Learner.
+- [Statistics 20, 003 - Fall 2010](https://archive.org/details/ucberkeley-webcast-PLFCCED623A3AB020F) — UC Berkeley.
+
 ---
 
 # Programming
 
-## Julia
+## iOS
+### Swift
+- [Developing iOS 10 Apps with Swift](https://itunes.apple.com/us/course/developing-ios-10-apps-with-swift/id1198467120?ign-mpt=uo%3D8) — Stanford
 
+## Julia
 - [Quantitative Economics with Julia](https://lectures.quantecon.org/jl/) — Learning Julia, dynamic programming, many mathematical concepts.
 
 ## Python
-
 - [Quantitative Economics with Python](https://lectures.quantecon.org/py/) — Great reference for scientific libraries, working with data, advanced Python concepts, dynamic programming.
+
+---
+
+# Startups
+- [Notes Essays—Peter Thiel’s CS183: Startup—Stanford, Spring 2012](http://blakemasters.com/peter-thiels-cs183-startup) — There is a book available from those notes: [Zero to One: Notes on Startups, or How to Build the Future](https://amzn.to/2I6AlDJ).