Return to Mike Gashler's page

My online courses

Let Dr. Gashler guide you from novice to data scientist with this six-course curriculum.

Will it be quick? Nope. This series contains over 100 hours of university lecture content in 416 videos, and you will need another 200 hours for the programming projects.

Will it be easy? Not a chance. You will be guided to complete 33 challenging programming projects. They are hard. And yes, they are essential for effective learning.

Will it be worth it? If you are dedicated, then probably. Pursuing expertise in one of the fastest-moving fields of science is not for everyone. But education is most certainly worthwhile.


Beginning
Programming
This course introduces students to computer programming and guides them to build a simple video game in Java.

Intermediate
Programming
This course builds upon basic programming skills to help students develop proficiency with computer programming. Students are guided to complete six programming projects that build on each other to arrive at a self-playing Mario-style tribute game.

Advanced
Programming
This course builds upon intermediate programming skills to help students develop proficiency with web-based programming. Students first teach themselves Javascript, then use Java to write an MMO that leverages client-server architecture and AJAX.

Artificial
Intelligence
This course introduces students to basic concepts in artificial intelligence. Students are guided to build software agents to solve puzzles, navigate over terrain, control agents, win strategy games, and make predictions.

Neural
Networks
This course guides students to implement their own neural network toolkit. It also covers a variety of neural net concepts, including basic theory, mathematical derivation, and intuition, but the primary emphasis is on implementation.

Advanced Artificial Intelligence
This course investigates deep Q-learning, kd-trees, nonlinear dimensionality reduction, cognitive architectures, the extended Kalman filter with neural networks, and Bayesian graphical models (a.k.a. belief networks).