ML EngineerBeginner to Intermediate

Foundations of Machine Learning

A rigorous first-principles track that takes you from ML basics to a deployable capstone.

12 Weeks15 modules4 Mini Projects + Capstone

What you'll build4 outcomes

01Model real problems using supervised and unsupervised techniques.
02Use NumPy and core Python tooling for ML workflows.
03Evaluate models with practical metrics and generalization checks.
04Complete mini projects and a capstone with measurable outcomes.

Full curriculum15 items · 5 projects

01Course Introduction

02Introduction to ML & the Language of Data

03Foundational Tools : Basics of NumPy

04Supervised Learning I : Linear Regression & Optimization

05Supervised Learning II : Classification & Decision Boundaries

06Mini Project 00 : Linear Regression

Project

07Supervised Learning III : Model Evaluation

08Regularization & Generalization Control

09Unsupervised Learning I : Clustering Algorithms

10Unsupervised Learning II : Dimensionality Reduction

11Mini Project 01 : Ensemble Machine Learning

Project

12Hands-on Introduction to Reinforcement Learning

13Mini Project 02 : Unsupervised Learning

Project

14Capstone Project Part 1 : Project Scoping & EDA

Project

15Capstone Project Part 2 : Modeling, Evaluation & Tuning

Project

Instructor

Isuru Alagiyawanna

Lead Instructor & Head of AI Engineering

Isuru leads Zuu Crew AI's technical direction and curriculum design. He has trained students and professionals across practical machine learning, MLOps, and AI engineering systems with a strong emphasis on shipping production-grade work.

BSc Electronic & Telecom Engineering (University of Moratuwa)MSc Big Data Analytics (Robert Gordon University, UK)Head of AI Engineering : Veracity GroupTensorFlow · AWS ML Engineer · IBM AI Specialist

Foundations of Machine Learning

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