AI & Data Analytics
Artificial Intelligence (AI)
Aligned with common introductory AI syllabi, this course covers supervised learning, model evaluation, neural-network basics, and responsible AI considerations. Weekly labs build intuition through small datasets and standard libraries so learners can continue toward ML engineering or data science roles.
Duration3 months
Class Size34 students
LevelBeginner to Advanced
Eligibility Requirements
- 12th grade or equivalent
- Comfort with basic math (algebra)
- Laptop with reasonable RAM for labs
What You Will Learn
- Frame business problems as ML tasks
- Train and evaluate classification/regression models
- Understand neural network fundamentals
- Use vectorized tooling (e.g. NumPy-style workflows)
- Interpret metrics and avoid common leakage pitfalls
- Discuss ethics, bias, and data privacy at a practical level
Course Curriculum
5 modules covering all essential topics