Why Take This Course?
This course equips engineering students with essential AI foundations, practical skills, and hands-on experience to apply Artificial Intelligence in real-world engineering problems.
Course Overview
SPARK-101 is designed as a fast-track introduction to Artificial Intelligence
for undergraduate and postgraduate engineering students. The course combines
fundamental theory with hands-on practical work using Python and real datasets.
Students will learn the essential mathematical foundations required for
machine learning and gain practical skills that enable them to apply AI
techniques in engineering design and problem solving.
Course Objectives:
This course introduces engineering students to the foundations of Artificial Intelligence and Machine Learning through an engaging mix of theory and practical experimentation using Python and real-world datasets.
Accelerated Introduction to AI
Provide a fast and engaging introduction to Artificial Intelligence concepts and their role in modern engineering applications.
Mathematical Foundations for AI
Bridge the essential mathematical foundations required for Machine Learning including Linear Algebra, Optimization, Calculus, and Probability Theory.
Practical AI Applications
Connect theoretical concepts with practical engineering problems using Python programming, simple machine learning models, and real-world datasets.
Preparation for Advanced AI Projects
Prepare students to apply Artificial Intelligence techniques in future coursework, engineering design projects, and research activities in years three and four.
SPARK-101 Hackathon
The course ends with a hackathon-style event. Participants must participate successfully in the hackathon in order to receive their participation certificates. Watch this page for more details on the hackathon (SPARK101).