Two 5-hour days: 2 hours session, lunchbreak, 3 hours session; for each day.
Prerequisites: We will alternate between presentations and programming exercises. The programming exercises are not required, but require use of a laptop with Python 3 installed. Experience in Python would be very helpful. If you don’t have these skills, you could pair up with someone who does.We will also be using a number of concepts of probability, statistics, and linear algebra.
Day 1 - May 12
Day 2- May 19
What do we mean by intelligence?
What do we mean by artificial intelligence?
Examples of AI
What are the primary concepts and approaches used in AI?
Solving problems by searching
Informed search methods
Programming Example: Problem Solving
What tools and languages are commonly used?
Sudoku example in Python
Knowledge and Reasoning
What is knowledge?
Building a knowledge base
Inference in first-order logic
Logical reasoning systems
Programming Example: Knowledge and Reasoning
Uncertain Knowledge and Reasoning
Making simple decisions
Making complex decisions
Programming Example: Uncertainty and Reasoning
Guest Presentation by Jenny Cai, Data Scientist at Moxie
This talk will cover typical projects carried out by Data Scientists.
Learning from observations
Learning in Neural and Belief Networks
Programming Example: Learning from data
Programming in Python Notebooks
Deep Learning/Neural Networks
Why are these the current hot topic?
First set of examples
Structure of Neural Networks
Second set of examples
Programming Example: Deep Learning
Programming linear regression in TensorFlow
Keras and other frameworks
Specialized Types of Neural Networks
Programming Example: CNN’s and Images
Using TensorFlow for digit recognition
Using TensorFlow for image classification
Guest Presentation from Mr. Utkarsch Contractor, Head of AI and Data Science at Aisera
This talk will focus on language and text processing
Current applications of AI
Reading list for further investigation