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Friday, April 13, 2012

Online Learning Courses

I first signed up for a Standford University course on artificial intelligence. Took one of the courses and found it was actually a bit difficulty. Not sure what the other 200,000 people who took it, and completed it ( I didn't), thought. Next, I signed up to take a course from udacity (Standford again) on progamming the robotic car, but that class time conflicted with something called my job. These courses are interesting, but today I found out that my university library, in the multi-media centre, has a subscription and dedicated computer with an IP link to lynda.com where there are all kinds of software tutorials. As I am still trying to learn enough Python to run an application at that place called my job, this might be very useful. Programming a robotic car might be more fun, but for now, I am going let other people do that. In fact though, the prerequiste for programming the robotic car is knowledge of Python!
You should either already know Python, or have enough experience with another language to be confident you can pick up what you need on your own. Fortunately, Python was built to be easy to learn, read, and use. If you already know another programming language, you'll be coding in Python in less than an hour. Additionally, knowledge of probability and linear algebra will be helpful.

Python Review
Python for Programmers Introduction to Programs Data Types and Variables Python Lists For Loops in Python While Loops in Python Writing a Simple Factorial Program Fun with Strings
Probability
Basic Probability Probability (Part 6) [Conditional Probability] Probability (Part 7) [Bayes' Rule] Probability (Part 8) [More Bayes' Rule] Introduction to Random Variables Probability Density Functions Expected Value: E(X)
Linear Algebra
Introduction to Matrices Matrix Multiplication (Part 1) Matrix Multiplication (Part 2) Inverse Matrix (Part 1) Inverting Matrices (Part 2) Inverting Matrices (Part 3) Matrices to Solve a System of Equations Singular Matrices Introduction to Vectors Vector Dot Product and Vector Length Defining the Angle Between Vectors Cross Product Introduction Matrix Vector Products Linear Transformations as Matrix Vector Products Linear Transformation Examples: Scaling and Reflections Linear Transformation Examples: Rotations in R2 Introduction to Projections Exploring the Solution Set of Ax = b Transpose of a Matrix 3x3 Determinant Introduction to Eigenvalues and Eigenvectors