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Artificial Intelligence Exploring Artificial Intelligence E-learning
Exploring Artificial Intelligence E-learning
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Exploring Artificial Intelligence E-learning

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Exploring Artificial Intelligence E-learning

Order this great E-learning Training Exploring Artificial Intelligence online course  1 year 24/7 access to rich interactive videos, voice, practice assignments, progress monitoring through reports and tests per subject to test the knowledge directly. After the course you will receive a certificate of participation..

Course content

Introduction to Artificial Intelligence
Course: 51 Minutes

Search Problems
Course: 44 Minutes

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

Brute Force Searching
Breadth-first Search
Depth-first Search
Iterative Deepening Search

Informed Searching
Greedy Best-first Search
Heuristics
Making Good Heuristics
A* Search

Local Searching
Hill-climbing Search
Simulated Annealing

Practice: Identifying Search Problems
Exercise: Describe Search Problems

 

Constraint Satisfaction Problems
Course: 28 Minutes

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

Solving CSPs
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
Exercise: Solve a Constraint Satisfaction Problem

 

Adversarial Problems
Course: 44 Minutes

Adversarial Games
Course Introduction
Adversarial Problems
Adversarial Problem Representation
Minimax Algorithm
Alpha-beta Pruning

Imperfect Decisions
Evaluation Functions
Cutoff Search
Lookup Tables
The Game of Chess

Stochastic Games
Expectiminimax Value
Stochastic Evaluation Functions
Monte Carlo Tree Search

Practice: Using the Minimax Algorithm
Exercise: Use Minimax and Pruning to Play a Game

 

Uncertainty
Course: 47 Minutes

Understanding Uncertainty
Course Introduction
What Is Uncertainty?
Uncertainty Representation

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

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

Practice: Markov Decision Process
Exercise: Describe the Markov Decision Process

 

Machine Learning
Course: 48 Minutes

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

Decision Trees
Using Decision Trees1
Decision Tree Learning: Information Gain
Decision Tree Learning: Choosing Attributes
Overfitting

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

Practice: Perceptron Training
Exercise: Make a Perceptron Learn From Examples

Reinforcement Learning
Course: 35 Minutes

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

Practice: Q-learning
Exercise: Describe Q-learning

 

Introducing Natural Language Processing
Course: 44 Minutes

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

Basic Models
Building Natural Language Processing (NLP) Models2
Text Classification
Naïve Bayes Classification
Information Retrieval (IR)

Communication
Answering Questions
Parsing
Machine Translation
Speech Recognition

Practice: NLP Operations
Exercise: Describe NLP Operations

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Specifications
General properties
Availabilty: 9 hours
Language: English
Certificate of participation: Yes
Online access: 90 days
Progress monitoring: Yes
Award Winning E-learning: Yes
Suitable for mobile: Yes
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