Kickstart Artificial Intelligence
- Be able to understand data structures, imports, and basic math operations in python. Advanced math, or detailed understanding of Artificial Intelligence is not required. Must have working computer/laptop for practice purposes
In this course, students will learn how to implement Artificial Intelligence in a hands on manner for a wide variety of new use cases while using cutting edge technologies such as Generative Adversarial Networks, Reinforcement Learning as well as classic Artificial Intelligence technologies such as Dense Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks and Long Short Term Memory Networks. Join the Gitter for new updates on AI and ML, and to spark some interesting information! With help from Jon Krohn's Github Tensorflow Live Lessons
Who this course is for:
- Software developers who want to get into AI Development, as well as business professionals who want to understand AI.
- 03:04Getting Started
- Preview18:31Technology behind Neural Networks
- 13:38Types of Layers
- 16:12Code Walkthrough (Dense Neural Network for MNIST Digit Classification)
- 12:05AI Testing and Optimization
- 07:45Code Demo: AI Testing and Optimization
- 4 questionsProgramming Assignment Options
I’m a seasoned AI and Deep Learning Developer who has programmed and delivered 5 MLH hackathon winning projects and interned at Genpact and EduChat. I am currently the Dean of the Princeton School of AI where we strive to provide world-class AI education for all for free. I am also a Stanford Online certified Artificial Intelligence specialist. Finally, I’m a certified cyber security professional having a CompTIA Security+ certification.