Machine Learning
Machine Learning
Master the ML workflow from data to deployed models.
Overview
- Master the end-to-end machine-learning workflow
- Perform exploratory data analysis and feature engineering
- Build supervised, unsupervised and deep-learning models
- Deploy models to production
About this Program
Learn how machines predict, adapt and drive tech innovation — from Python and EDA to supervised, unsupervised and deep learning, ending with model deployment.
Key Highlights
3-month, self-paced program
Double certification on completion
1:1 mentorship from industry experts
Real-world, project-based learning
Internship-readiness built in
Free job-assistance portal
Learning Objectives
Frame business problems as ML tasks
Train, tune and evaluate models rigorously
Engineer features and handle real-world data
Deploy a trained model as a usable service
Course Curriculum
ML & Python Essentials
- ML overview, Python, data structures and visualization.
Exploratory Data Analysis & Feature Engineering
- Profiling data and crafting features.
Supervised Learning
- Regression and classification techniques.
Unsupervised Learning
- Clustering and anomaly detection.
Deep Learning & Neural Networks
- Fundamentals of neural networks.
ML Deployment & Production Engineering
- Packaging and serving models.
AI Tools & Business Applications
- Applying ML to business problems.
Career Launchpad & Resume Prep
- Portfolio, resume and interview prep.
Tools & Technologies
Python
NumPy
Pandas
Matplotlib
Scikit-learn
Projects You'll Build
Data Cleaning with AI Code Interpreter
Automated data-cleaning workflow.
House Price Prediction App
A regression model with a simple UI.
Recommendation System
A content/collaborative recommender.
Ready to take the next step? Get in touch and begin your journey @ just ₹8999!