Minor in Artificial Intelligence & Data Science by CCE, IIT Mandi

Minor in Artificial Intelligence
& Data Science
by
CCE, IIT Mandi

A 15-credit minor foundational course, designed to equip beginners with essential skills for high-demand careers in AI and data-driven decision-making.

  • Open to beginners with basic programming and mathematics skills.
  • Foundational and advanced concepts taught by renowned IIT professors.
  • Unlock high-demand careers in AI & Data science with hands-on skills and insights.

Batch Starts

20th March

Available Seats

220 Pan India

Program Duration

09 Months

1

Admission Process

One clear path, one clear goal: your tech career.

Our admission process is simple and super fast with just 3 steps.You can start learning in the next few minutes.

Start here.

Clear Qualifier Test

You must pass the exam to confirm your seat for the program.

Complete Onboarding

Only shortlisted candidates go through the onboarding process.

Start Learning

Learn from India’s top educators and stand out from the crowd.

Qualifier test details

To join this program, you must clear the qualifier test on your allotted date.

Topics Covered

  • Mathematics
  • Basic Progamming
  • Problem Solving Ability
  • Statistics

Registration Process

  • Pay ₹99 and choose your slot
  • Unlock free mock test and practice before your final exam
  • 100% refund if you don’t qualify or if you qualify but choose not to enroll after counseling.

Things to remember

  • The duration of the test is 60 minutes.
  • You can take the test only once at your allotted time & slot.
  • The test can only be taken on a desktop/laptop on Google chrome browser
2

What will you learn?

The AI and Data Science program by IIT Mandi, a 15-credit course equivalent to a minor degree, 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.

The Skills You’ll Gain

Programming Proficiency
Data Analysis and Visualization
Big Data Handling
Deep Learning Skills
Machine Learning Expertise
Problem-Solving with AI

Course Details

Trimester duration

9 months, 3 trimester

Commitment

10 hrs per week

Trimester break

2 breaks of 2 weeks each

Course Credits

15 Credits

MTH
101

Mathematics for Data Science

Master the mathematical backbone of AI and Data Science, exploring linear algebra, calculus, probability, and optimization to build a strong analytical foundation for modeling, problem-solving, and decision-making in complex data-driven scenarios.

Linear Algebra
Calculus
Probability & Statistics
Optimization
Eigenvectors & Orthogonality
Gradients
Covariance & Correlation
Conditional Probability & Bayes’ Theorem

Example Projects

Project 1 : Personal Loan Approval Prediction System

Develop a machine learning model to predict whether a loan application will be approved based on applicant details, enabling efficient decision-making in financial institutions.

  • Supervised Learning: Classification techniques (Logistic Regression, Decision Trees, SVMs)

  • Model Evaluation: Precision, Recall, F1-score, ROC-AUC

  • Feature Engineering: Handling categorical data, outliers, and missing values

  • Cross-Validation & Hyperparameter Tuning: Ensuring robust and optimized models

  • Industry Application: Credit risk analysis and customer evaluation in finance

    • Project 2 :  Customer Churn Prediction for SaaS Platforms

    Build a machine learning model to predict whether a customer will stop using a subscription-based service, helping companies improve retention strategies.

  • Supervised Learning: Classification methods (Random Forests, Gradient Boosting, Logistic Regression)

  • Feature Engineering: Temporal features, behavior tracking, and interaction patterns

  • Ensemble Learning: Techniques like bagging and boosting for improved accuracy

  • Evaluation Metrics: Accuracy, Precision-Recall Curve, ROC-AUC

  • Business Impact: Insights into customer behavior and retention improvement

    • Example Projects

    Project 3 :  Real-Time Traffic Pattern Clustering

    Create an unsupervised learning model to cluster traffic patterns using real-world traffic data, aiding in congestion management and route optimization

  • Unsupervised Learning: Clustering algorithms (K-Means, Gaussian Mixture Models)

  • Dimensionality Reduction: PCA for visualization and feature compression

  • Model Validation: Silhouette score, Elbow Method

  • Data Handling: Preprocessing large-scale time-series traffic data

  • Practical Utility: Applications in smart cities and transportation systems

    • Project 4 : Intelligent Image Captioning System

    Develop a deep learning-based system to generate descriptive captions for images by integrating Convolutional Neural Networks (CNNs) with Recurrent Neural Networks (RNNs).

  • Deep Learning Architectures: CNNs for feature extraction, RNNs/LSTMs for sequence generation

  • Transformers: Incorporating attention mechanisms for improved accuracy

  • Generative Models: Image-to-text mapping using sequence modeling

  • Practical Applications: AI-powered image description in accessibility tools and media platforms

  • Frameworks: PyTorch or TensorFlow for implementation

    • Example Projects

    Project 5 :  AI-Powered Chatbot for Sentiment-Aware Customer Support

    Build a machine learning model to predict whether a customer will stop using a subscription-based service, helping companies improve retention strategies.

  • NLP Techniques: Tokenization, word embeddings, and transformer-based models (e.g., BERT, GPT)

  • Reinforcement Learning: Fine-tuning response generation for improved interaction quality

  • Evaluation Metrics: BLEU score, perplexity, and sentiment classification accuracy

  • Practical Applications: Customer service automation with sentiment-aware responses

  • Industry Relevance: High demand in e-commerce and SaaS sectors

    • Project 6 : Real-Time Object Detection and Tracking

    Build a real-time object detection and tracking system using YOLO (You Only Look Once) and apply it to scenarios like traffic monitoring or surveillance.

  • Deep Learning Architectures: CNNs for detection and feature extraction

  • Advanced Techniques: YOLO/SSD for real-time performance

  • Computer Vision Applications: Object tracking, bounding box prediction, and classification

  • Optimization: Model quantization for deployment on edge devices

  • Industry Application: Smart cities, autonomous vehicles, and security systems

    • Meet our fabulous mentors from IIT

    Indu Joshi

    Assistant Professor @ IIT Mandi

    Biometrics, Medical Image Analysis, Computational Biology, Deep Learning

    Experience

    4+ yrs

    Citations

    293

    Mentorship from industry experts

    Arul Francis

    Associate Director Global Commercial Data Science & AI Engineering

    @ AstraZeneca

    Gaurav Kandel

    Data Scientist

    @ FinBox

    Sriram Desai

    SDE

    @ ByteDance

    Saket Dwivedi

    Stadd ML Engineer

    @ Cureskin

    3

    Who is this course for?

    Anyone interested to up skill in AI or DS, aspiring Data Scientists and AI Engineers looking to switch from Programming to AI or DS

    Undergraduate students who want to enhance their skills in Data Science and AI while continuing their main studies.

    Aspiring professionals and innovators who aim to use AI and data-driven insights to create impactful solutions.

    Tech enthusiasts who wish to establish a strong foundation in AI tools and techniques to remain industry-ready.

    Career Pathways After This Course

    Data Scientist
    AI Engineer
    Tech Entrepreneur
    Quantitative Analyst
    ML Engineer
    Software Developer
    4

    Why choose this course?

    Expert Faculty: Learn from IIT Mandi’s top professors with industry experience
    Comprehensive Curriculum: Covers foundational to advanced AI & DS topics.
    Beginner-Friendly: Suitable for students with basic programming and math knowledge.
    Job-Ready Skills: Gain expertise in machine learning, data analytics, and more.
    Capstone Project: Apply knowledge to real-world problems and connect with peers.
    Showcase IIT Certificate: Receive an official certificate from IIT Mandi to enhance your career prospects.
    5

    Fee Structure

    Option 1

    Upfront

    Option 2

    EMI

    (Through Our NBFC Partners)

    Qualifier Test Fee
    ₹99
    ₹99
    Secure Seat Fee

    ( Non-refundable)

    ₹4,000
    ₹4,000
    Remaining Course Fee

    ( Non-refundable)

    ₹66,000
    ₹8,800 x 9

    (months)

    Total
    ₹70,099
    ₹83,299

    (*100% refund if you don’t qualify or if you qualify but choose not to enroll after counseling.)