Professional Certificate in Machine Learning and Artificial Intelligence

Program Overview

This program provides a comprehensive introduction to machine learning and problem-solving by search. It covers fundamental concepts, algorithms, and techniques, including decision trees, neural networks, and SLAM. Through webinars, assignments, and quizzes, participants gain practical skills and knowledge in machine learning and problem-solving. The program prepares individuals for careers in fields such as data science, artificial intelligence, and robotics.

Program Outline

Outline:

• Modules 1 & 2: Introduction to Machine Learning
• Definitions
• Introduction to algorithms
• Basic statistics and probability concepts
• Introduction to MATLAB and WEKA
• Modules 3 & 4: Problem-Solving by Search Part 1
• Problem-solving agents
• Problem types
• Example problems
• Basic search algorithms
• Modules 5 & 6: Problem-Solving by Search Part 2
• Best-first search
• A* search
• Hill-climbing search
• Genetic algorithms
• Modules 7 & 8: Simultaneous Localization and Mapping (SLAM)
• Robot localization techniques and principles
• Mathematical optimization
• Overview of Kalman filters and particle filters
• SLAM
• Modules 9 & 10: Machine Learning: Decision Trees and Naïve Bayes
• Problems solved by machine learning
• Decision trees
• Naïve Bayes
• Modules 11 & 12: Machine Learning: Neural Networks and Rules
• K-NN
• Neural networks
• Association rules

Assessment:

• 65% attendance rate at live, online fortnightly webinars
• 60% mark in set assignments
• 100% mark in quizzes

Teaching:

• Fortnightly webinars that run for about 90 minutes
• Class discussions