Inaugural Batch
Build your AI/ML career with
Certification in
Artificial Intelligence and Machine Learning
Program
Career Potential
The #1 fastest-growing career field in 2026
AI/ML roles grew 163% in one year. The demand is real, salaries are high, and the talent gap is wide open
1.3M+
New global AI/ML roles
₹5.5–28 LPA
Salary Range by Experience
43.76%
India AI market growth rate
(CAGR 2025–2031)
Industries with demand in this field
Organisations hiring in this field
career roadmap
One career, 3 progressive tiers.
From foundations to specialization, an IIT-certified roadmap built for real-world careers.
Foundation
Build core programming, data handling, and statistics skills using Python, SQL, and NumPy. Learn ML fundamentals, including supervised learning, model evaluation, and data visualization.
Module wise curriculum
module 1
Python for AI/ML
Build programming fluency with Python, control flow, and data structures.
module 2
SQL & Data Foundations
Retrieve, filter, and structure data from real-world relational databases.
module 3
NumPy & Pandas Essentials
Load, clean, transform, and restructure datasets for ML workflows.
module 4
EDA & Visualization
Inspect patterns, spot anomalies, and communicate findings through charts.
module 5
Statistics for ML
Build intuition for probability, distributions, variance, and uncertainty.
module 6
ML Fundamentals
Understand supervised learning, model evaluation, and overfitting basics.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"Python, SQL, EDA — in the right order, with the right depth. Someone who's built this foundation is genuinely ready to add value on day one."
Roles unlocked
Core Expertise
Master the mathematics behind ML algorithms and go deeper into supervised learning, model evaluation, and ensemble methods. Progress into neural networks and deep learning, building hands-on proficiency with PyTorch and TensorFlow to train, debug, and deploy production-grade models.
Module wise curriculum
module 1
Applied Math for ML
Build intuition for vectors, gradients, optimization, and distance metrics.
module 2
Supervised Learning
Build predictive systems using core regression and classification approaches.
module 3
Model Evaluation
Choose metrics, inspect failures, and build reproducible ML pipelines.
module 4
Advanced ML Methods
Train ensembles, tune models, and explore clustering and anomaly detection.
module 5
Deep Learning Basics
Learn neural networks, backpropagation, loss functions, and training loops.
module 6
Deep Learning in Practice
Implement deep learning workflows hands-on using PyTorch or TensorFlow.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"The curriculum mirrors what modern ML teams actually build - from rigorous model evaluation to deep learning in production. This is the kind of training that closes the gap between classroom and industry."
Roles unlocked
industry specialization
Dive into the world of Large Language Models, prompt engineering, and generative AI. Learn to build semantic search systems using embeddings and vector databases, design end-to-end RAG pipelines, evaluate LLM outputs for hallucination and quality, and ship real-world GenAI applications
Module wise curriculum
module 1
LLMs & Prompt Engineering
Learn transformer architecture, LLM basics, and practical prompting patterns.
module 2
Embeddings & Vector Search
Understand text embeddings, semantic retrieval, and vector database fundamentals.
module 3
RAG & GenAI Applications
Build RAG pipelines, evaluate LLM outputs, and handle hallucination failure modes.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"Prompt engineering, RAG, and GenAI evaluation are exactly what hiring teams look for in 2026. This specialization builds the applied skills that take engineers from knowing LLMs to actually shipping with them."
Roles unlocked
Build core programming, data handling, and statistics skills using Python, SQL, and NumPy. Learn ML fundamentals, including supervised learning, model evaluation, and data visualization.
Module wise curriculum
module 1
Python for AI/ML
Build programming fluency with Python, control flow, and data structures.
module 2
SQL & Data Foundations
Retrieve, filter, and structure data from real-world relational databases.
module 3
NumPy & Pandas Essentials
Load, clean, transform, and restructure datasets for ML workflows.
module 4
EDA & Visualization
Inspect patterns, spot anomalies, and communicate findings through charts.
module 5
Statistics for ML
Build intuition for probability, distributions, variance, and uncertainty.
module 6
ML Fundamentals
Understand supervised learning, model evaluation, and overfitting basics.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"Python, SQL, EDA — in the right order, with the right depth. Someone who's built this foundation is genuinely ready to add value on day one."
Roles unlocked
Master the mathematics behind ML algorithms and go deeper into supervised learning, model evaluation, and ensemble methods. Progress into neural networks and deep learning, building hands-on proficiency with PyTorch and TensorFlow to train, debug, and deploy production-grade models.
Module wise curriculum
module 1
Applied Math for ML
Build intuition for vectors, gradients, optimization, and distance metrics.
module 2
Supervised Learning
Build predictive systems using core regression and classification approaches.
module 3
Model Evaluation
Choose metrics, inspect failures, and build reproducible ML pipelines.
module 4
Advanced ML Methods
Train ensembles, tune models, and explore clustering and anomaly detection.
module 5
Deep Learning Basics
Learn neural networks, backpropagation, loss functions, and training loops.
module 6
Deep Learning in Practice
Implement deep learning workflows hands-on using PyTorch or TensorFlow.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"The curriculum mirrors what modern ML teams actually build - from rigorous model evaluation to deep learning in production. This is the kind of training that closes the gap between classroom and industry."
Roles unlocked
Dive into the world of Large Language Models, prompt engineering, and generative AI. Learn to build semantic search systems using embeddings and vector databases, design end-to-end RAG pipelines, evaluate LLM outputs for hallucination and quality, and ship real-world GenAI applications
Module wise curriculum
module 1
LLMs & Prompt Engineering
Learn transformer architecture, LLM basics, and practical prompting patterns.
module 2
Embeddings & Vector Search
Understand text embeddings, semantic retrieval, and vector database fundamentals.
module 3
RAG & GenAI Applications
Build RAG pipelines, evaluate LLM outputs, and handle hallucination failure modes.
tools acquired
hear from industry experts
Praveen Kumar Puniaf
Senior Data Science Consultant
"Prompt engineering, RAG, and GenAI evaluation are exactly what hiring teams look for in 2026. This specialization builds the applied skills that take engineers from knowing LLMs to actually shipping with them."
Roles unlocked
Meet Your Faculty
Built by experts. Taught by practitioners
A handpicked team of engineers, researchers, and industry leaders guiding your AI career.
Dr. Indu Joshi
Assistant Professor, IIT Mandi
PhD, IIT Delhi. Postdoc at Inria France and TU Munich. President of India Silver Medalist. Deep Learning specialist.
Priyansh Saxena
MLE III @GoDaddy
Technology and research professional with experience across data science, analytics, and emerging technologies.passionate about leveraging data-driven insights to solve complex problems and drive impactful outcomes
Praveen Kumar Punia
Senior Data Science Consultant @ MU sigma
Praveen Kumar Punia is a Decision Science professional with over 5 years of experience, specializing in data analytics and business intelligence.
Dr. Indu Joshi
Assistant Professor, IIT Mandi
PhD, IIT Delhi. Postdoc at Inria France and TU Munich. President of India Silver Medalist. Deep Learning specialist.
Priyansh Saxena
MLE III @GoDaddy
Technology and research professional with experience across data science, analytics, and emerging technologies.passionate about leveraging data-driven insights to solve complex problems and drive impactful outcomes
Praveen Kumar Punia
Senior Data Science Consultant @ MU sigma
Praveen Kumar Punia is a Decision Science professional with over 5 years of experience, specializing in data analytics and business intelligence.
*Note: Instructor may change subject to availability
Message From Head, CCE IIT Mandi
Prof. Tushar Jain
Head, Centre for Continuing Education
The curriculum begins with strong foundations in programming, data handling, and machine learning concepts, followed by core applied learning in model development, evaluation, and deep learning. It culminates in specialization areas such as Generative AI, transformers, and modern AI application workflows, reflecting the latest advancements in the field.
With a strong emphasis on hands-on learning, industry-relevant tools, and disciplined problem-solving approaches, this programme aims to prepare learners for emerging roles in machine learning, and applied AI.
We believe this initiative will enable learners to not only understand AI-ML systems but also apply them effectively in real-world scenarios, contributing meaningfully to the evolving technology landscape.
the differentiator
Industry readiness is built in, not bolted on.
The final tier isn't just coursework — it's a launchpad. Here's what sets this career path apart from every other program.
Project Casestudy
Industry Endorsed Capstone Project
Build a strong AI/ ML portfolio that showcases your skills
2 Days
Campus
Immersion at
IIT Mandi
Certification by CCE, IIT Mandi
Minimum 65% overall attendance and 30% marks in cumulative evaluations score
Placement Opportunity fulfilled by Masai
Interview Access & Career Support Eligibility: 7+ CGPA and 65% attendance
Learn from the best faculty in the industry
Why Choose This Program?
Here's what actually gets you hired
We talked to 100+ hiring managers. Not one asked "which certificate do you have?" We built the course to cover what they actually look for.
What this course actually builds
Structured progression from basics to job-ready skills
End-to-end projects on real industry datasets
Industry-standard tools used in actual jobs
RAG, LLMs, and prompt engineering included
Roles unlocked as you progress through the program
What most courses give you
Standalone modules with no career trajectory
Toy datasets with no business context
Outdated or limited toolset coverage
Stops at traditional ML, no GenAI
Certificate only after full course completion