LEARN • PRACTICE • BUILD • RESEARCH
Explore structured academic courses across Mathematics, Programming, Computer Science, Artificial Intelligence and Data Science — supported by notes, assignments, quizzes, projects and practical learning resources.
COURSE CATALOG
Select an academic area to quickly navigate to relevant courses and learning materials.
Calculus, Linear Algebra, Discrete Mathematics, Statistics, Numerical Analysis and Modeling.
Programming, algorithms, data structures, databases and computational thinking.
Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision and NLP.
Data Analytics, Statistics, Visualization, Data Mining and Machine Learning.
ACADEMIC AREA
Mathematical foundations for computing, data science, artificial intelligence and scientific problem solving.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon..
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
ACADEMIC AREA
Programming and computational foundations for software development and intelligent systems.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
Arrays, linked lists, stacks, queues, trees, graphs, searching, sorting and algorithmic problem solving.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
ACADEMIC AREA
Intelligent systems, machine learning and modern AI concepts from foundations to practical applications.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
ACADEMIC AREA
Learn how to transform data into insights using statistics, visualization, analytics and machine learning.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
Lectures Coming Soon We are currently uploading lectures. New learning materials will be available soon.
LEARNING RESOURCES
PMAI Lab courses are designed to connect theoretical foundations with practical learning and project-based experience.
Structured course outlines, topics, semester information and learning objectives.
Faculty-provided lecture notes and organized academic learning materials.
Practice assignments designed to strengthen concepts and problem-solving skills.
Revision quizzes and assessment resources for effective exam preparation.
Previous examination papers and practice resources where available.
Recommended references, external resources, tutorials and supplementary materials.
FOR FACULTY & ACADEMIC CONTRIBUTORS
Faculty members can contribute approved course outlines, lecture notes, assignments, quizzes, projects and other academic resources to the PMAI Lab learning platform.
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