The Short Course in Artificial Intelligence (AI) short course will provide learners with the foundation and branches of Artificial Intelligence, such as search strategies, knowledge representation and reasoning techniques. This course will also introduce a range of well-known techniques and applications in artificial intelligence, such as fuzzy logic machine learning, expert systems, natural language processing, and intelligent agents.
Learning Outcomes
- Understand the importance of AI and its applications.
- Apply a range of well-established AI search strategies and knowledge representation techniques in problem solving.
- Assess a range of well-established techniques for reasoning with uncertain knowledge.
- Understand a range of machine learning techniques.
- Implement and evaluate a range of AI models and techniques for solving real-world problems.
Prerequisites and Target Audience
What will students need to know or do before starting this course?
- This course is structured in a way that it is largely complete in itself.
- Helpful but not required is familiarity with
- Linear Algebra, Probability, Statistics
- Computer Programming, preferably Python
Who should take this course? Who should not?
- Executives and decision makers looking for a comprehensive overview of the subject
- Professionals and students with a formal college education in Engineering, science, or mathematics
Topics Covered
1
Introduction to AI
2
Problem Solving Using Search
3
Knowledge Representation
4
Uncertain Knowledge
5
Fuzzy Logic
6
Machine Learning
7
Neural Network
8
Decision Tree
9
Genetic Algorithms
10
Experts Systems
11
Natural Language Processing
12
Intelligent Agents
AI Architect
Business Intelligence Developer
Big Data Engineer
Data Scientist
Machine Learning Engineer
As a minimum, participants should have:
Good IT knowledge related to subject area
Good understanding of English
Knowledge of computer science, programming and mathematics/statistics.
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