Minor in Artificial Intelligence & Data Science
Qualifier Test Date
January 11, 2026
Program Duration
9 Months
Eligibility
12th Pass and Above
Learning Mode
Online
Time Commitment
8-10 Hours/week
2.8K+ students have already registered
Qualifier Test Date
January 11, 2026
Program Duration
9 Months
Eligibility
12th Pass and Above
Learning Mode
Online
Time Commitment
8-10 Hours/week
Why choose this course?
Learn Like an IITian, Excel Like a Global Leader
Covers foundational to advanced AI & DS topics.
Suitable for students with basic programming and math knowledge.
Receive resume reviews, career coaching, and placement support to land your dream role. (Eligibility: 7+ CGPA and 65% attendance).
Apply knowledge to real-world problems and connect with peers.
Receive an official certificate from CCE, IIT Mandi, to enhance your career prospects.
Gain 15 Minor Credits from CCE, IIT Mandi, upon successful Course Completion.
Comprehensive Curriculum
Covers foundational to advanced AI & DS topics.
Beginner-Friendly
Suitable for students with basic programming and math knowledge.
Placement Opportunities
Receive resume reviews, career coaching, and placement support to land your dream role. (Eligibility: 7+ CGPA and 65% attendance).
Capstone Project
Apply knowledge to real-world problems and connect with peers.
Showcase IIT Certificate*
Receive an official certificate from CCE, IIT Mandi, to enhance your career prospects.
Credit from IIT Mandi
Gain 15 Minor Credits from CCE, IIT Mandi, upon successful Course Completion.
*Certificate Eligibility: Minimum 65% overall attendance and 30% marks in cumulative evaluations score
What will you learn?
The AI and Data Science program by CCE, IIT Mandi, a 15-credit course, offers a comprehensive curriculum covering foundational programming, mathematics, and statistics, progressing to advanced topics like machine learning, neural networks, and big data analytics. Designed for beginners with basic knowledge, it is taught by renowned IIT professors, ensuring high-quality learning and career-ready skills. The program includes practical applications, capstone projects, and expertise in cutting-edge AI and data science techniques, preparing students for high-demand roles in this transformative field.
Toolkit
Course Details
Duration
9 Months
Course Mode
Online
Certification
From CCE, IIT Mandi
- • Learn core linear algebra concepts like vectors, matrices, echelon form, and solving systems of linear equations.
- • Understand vector spaces, basis, linear transformations, and projections crucial for AI and ML models.
- • Build calculus foundations including functions, gradients, partial derivatives, and the Jacobian and Hessian matrices.
- • Grasp key probability concepts such as conditional probability, Bayes’ theorem, random variables, and joint distributions.
- • Introduce core supervised learning concepts, including regression and classification.
- • Cover essential unsupervised learning methods, particularly clustering and dimensionality reduction.
- • Introduce ensemble methods and model selection strategies.
- • Provide a strong basis in evaluation metrics and best practices for validating machine learning models.
- • Master the fundamentals of deep neural networks and advanced architectures (CNNs, RNNs, transformers).
- • Understand and implement generative models (VAEs, GANs) for creative AI applications.
- • Explore specialized AI topics: NLP, computer vision, and reinforcement learning.
- • Develop insight into research frontiers and future directions in AI.
Projects
Product-Image Classifier (CNN)
Flipkart’s catalog team wants to auto-categorise product images into Apparel, Electronics, and Home. You train a small CNN on a public Indian e-commerce image dataset using free Colab GPU, push validation accuracy past 85%, and produce a confusion-matrix breakdown that names exactly which category pairs the model still fumbles — and why.
DECISION OUTPUT
Trained classifier with documented confusion patterns the catalog team can route to manual review.
Customer-Churn Predictor & API
Build a churn-prediction model for a D2C customer dataset. Engineer RFM features (recency, frequency, monetary), train a gradient-boosting classifier, deploy as a FastAPI endpoint, and write the model card — including the ethical considerations around retention targeting that any real product team will probe in your interview.
DECISION OUTPUT
A deployable churn predictor with a documented model card you can defend to a hiring panel.
*Note: The project deliverables or case studies for your batch may differ, as per the decision of the Institute or Course Faculty
