Introducing AI

Course: 31 Minutes

• Course Introduction
• What Is Artificial Intelligence?
• Fields and Applications
• AI Techniques
• Defining Agents
• Types of Agents

Environments

Course: 18 Minutes

• Describing Environments
• Environment's Observability
• Number of Agents in Environments
• Certainty in an Environment
• Environment's Behavior

Practice: Agents and Environments

Course: 3 Minutes

• Exercise: Describe an Agent and an Environment

Introducing Search Problems

Course: 15 Minutes

• Course Introduction
• Search Problems Defined
• Search Problem Examples
• Representing Search Problems for Search Algorithms

Brute Force Searching

Course: 9 Minutes

• Breadth-first Search
• Depth-first Search
• Iterative Deepening Search

Informed Searching

Course: 14 Minutes

• Greedy Best-first Search
• Heuristics
• Making Good Heuristics
• A* Search

Local Searching

Course: 5 Minutes

• Hill-climbing Search
• Simulated Annealing

Practice: Identifying Search Problems

Course: 2 Minutes

• Exercise: Describe Search Problems

Introducing CSPs

Course: 6 Minutes

• Course Introduction
• What Are Constraint Satisfaction Problems (CSPs)?
• Constraint Satisfaction Problem Examples

Solving CSPs

Course: 19 Minutes

• Backtracking Search
• Variable Ordering
• Arc Consistency
• Constraint Propagation
• Using Inference with Search
• Using a Local Search for CSPs
• Solving a Sudoku Puzzle

Practice: Constraint Satisfaction Problems

Course: 3 Minutes

• Exercise: Solve a Constraint Satisfaction Problem
• Course Introduction
• Adversarial Problems
• Adversarial Problem Representation
• Minimax Algorithm
• Alpha-beta Pruning

Imperfect Decisions

Course: 15 Minutes

• Evaluation Functions
• Cutoff Search
• Lookup Tables
• The Game of Chess

Stochastic Games

Course: 11 Minutes

• Expectiminimax Value
• Stochastic Evaluation Functions
• Monte Carlo Tree Search

Practice: Using the Minimax Algorithm

Course: 2 Minutes

• Exercise: Use Minimax and Pruning to Play a Game

Understanding Uncertainty

Course: 10 Minutes

• Course Introduction
• What Is Uncertainty?
• Uncertainty Representation

Understanding Utility Theory

Course: 13 Minutes

• Utility Theory
• Utility and Preferences
• Utility and Risks
• Value of Information

Examining the Markov Decision Process

Course: 21 Minutes

• Markov Chains
• Markov Decision Process
• MDP Value Iteration
• Partially Observable Markov Decision Process (POMDP)
• POMDP Value Iteration
• Applying POMDPs

Practice: Markov Decision Process

Course: 3 Minutes

• Exercise: Describe the Markov Decision Process

Learning for Computers

Course: 9 Minutes

• Course Introduction
• How Computers Can Learn
• Learning From Examples

Decision Trees

Course: 12 Minutes

• Using Decision Trees
• Decision Tree Learning: Information Gain
• Decision Tree Learning: Choosing Attributes
• Overfitting

Neural Networks

Course: 25 Minutes

• Artificial Neural Networks
• Neural Network Structure
• Types of Neural Networks
• Perceptron Learning
• Deep Neural Networks
• Convolutional Neural Networks
• Recurrent Neural Networks

Practice: Perceptron Training

Course: 2 Minutes

• Exercise: Make a Perceptron Learn From Examples

Introducing Reinforcement Learning

Course: 21 Minutes

• Course Introduction
• What Is Reinforcement Learning?
• Additive and Discounted Rewards
• Passive Learning
• Direct Utility Estimation
• Temporal Difference Learning
• Active Learning
• Exploration and Exploitation Policies

Q-learning Algorithm

Course: 12 Minutes

• Defining Q-learning
• Implementing Q-learning
• Off-policy and On-policy Learning
• Function Approximation
• Deep Q-learning

Practice: Q-learning

Course: 2 Minutes

• Exercise: Describe Q-learning

Defining NLP

Course: 17 Minutes

• Course Introduction
• Introducing Natural Language Processing (NLP)
• Base NLP Operations
• Porter Stemming Algorithm
• Named Entity Recognition

Basic Models

Course: 11 Minutes

• Building Natural Language Processing (NLP) Models
• Text Classification
• Naïve Bayes Classification
• Information Retrieval (IR)

Communication

Course: 14 Minutes

• Answering Questions
• Parsing
• Machine Translation
• Speech Recognition

Practice: NLP Operations

Course: 2 Minutes

• Exercise: Describe NLP Operations

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