- Practical Hands on course to Artificial Intelligence
- Free tutorial
- Rating: 3.4 out of 53.4 (305 ratings)
- 27,895 students
- 3hr 5min of on-demand video
- Created by Kashyap Murali
English
What you’ll learn
- Students will be able to apply Artificial Intelligence in real world tasks and will be able to build fully functioning AI solutions on their own.
Requirements
- 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
Description
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.
Show less
Course content
3 sections • 22 lectures • 3h 5m total lengthCollapse all sections
Deep Learning Foundations7 lectures • 1hr 19min
- Getting Started03:04
- Introduction07:51
- Technology behind Neural NetworksPreview18:31
- Types of Layers13:38
- Code Walkthrough (Dense Neural Network for MNIST Digit Classification)16:12
- AI Testing and Optimization12:05
- Code Demo: AI Testing and Optimization07:45
- Programming Assignment Options4 questions
Introduction to RNNs8 lectures • 59min
- An overview of NLP and it’s Relatives05:53
- Preprocessing Steps for NLP10:42
- Modeling Natural Language Data08:45
- Recurrent Neural Networks08:22
- Long Short Term Memory Networks05:58
- Understanding the Difference Between RNNs and LSTMs03:14
- Code Walkthrough09:28
- New Types of Neural Network Architectures06:24
- Programming Assignment: Introduction to RNNs (Reuters Newswire)1 question
Reinforcement Learning and GANs7 lectures • 47min
- Application of GANs and Reinforcement Learning05:16
- Theory of GANs and Google’s Quick, Draw! Dataset07:11
- Code Walkthrough12:38
- Deep Reinforcement Learning04:27
- Code Walkthrough 212:43
- Programming Assignment Options: Reinforcement Learning and GANs2 questions
- Bonus Lecture: Boltzmann Machines03:04
- Summary of Course01:52
