D24
Data & AIAdvanced10 weeks
Machine Learning
Design, train, and deploy machine learning models with hands-on projects covering classification, regression, and clustering.
What you'll learn
Supervised learning: classification and regression
Unsupervised learning and clustering techniques
Model tuning, validation, and deployment basics
An end-to-end ML project from raw data to prediction
Course details
Duration
10 weeks
Best for
Learners comfortable with Python who want to build predictive models
On completion
Verified certificate & placement assistance
Course Curriculum
A module-by-module breakdown of what you'll cover in Machine Learning.
01
ML Foundations
Weeks 1–3- Types of machine learning
- Data preparation for ML
- Bias-variance tradeoff
02
Supervised Learning
Weeks 4–5- Regression models in depth
- Classification algorithms
- Decision trees and ensembles
03
Unsupervised Learning
Weeks 6–8- Clustering techniques
- Dimensionality reduction
- Anomaly detection
04
Deployment & Projects
Weeks 9–10- Model tuning and validation
- Deploying models with simple APIs
- Capstone project across the ML lifecycle
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
Python
sklScikit-learn
PdPandas
NpNumPy
JnJupyter Notebook
Hands-on Projects
This is project-based learning — you'll build real, portfolio-ready work as you go, not just watch lectures.
Customer segmentation with clustering
Fraud detection classifier
Sales forecasting model
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Student Reviews
“Solid, practical coverage of the algorithms that actually get used in production, not just toy examples.”
Naveen Raj
Data Engineer
“The projects forced me to think about real deployment concerns, which most courses skip entirely.”
Shruti Pillai
Analytics Lead
Enroll in Machine Learning
Fill out this form and our team will confirm your seat and next batch dates. The course is pre-selected — no need to search for it again.
