IIT Mandi Masai Data Science & Machine Learning PDF

Summary

This brochure describes a Minor in Data Science and Machine Learning program at the Indian Institute of Technology Mandi, in partnership with Masai School and NSDC. The program is designed for professionals seeking to develop data science and machine learning skills. It covers topics like mathematics, programming, machine learning fundamentals, and deep learning, culminating in a capstone project.

Full Transcript

Minor in Data Science and Machine Learning CCE, INDIAN INSTITUTE OF TECHNOLOGY, MANDI Overview of the Partnership IIT Mandi, in a transformative collaboration with NSDC and Masai School, proudly presents a groundbreaking partnership to introduce a jointly certified Minor in Data Science and Mach...

Minor in Data Science and Machine Learning CCE, INDIAN INSTITUTE OF TECHNOLOGY, MANDI Overview of the Partnership IIT Mandi, in a transformative collaboration with NSDC and Masai School, proudly presents a groundbreaking partnership to introduce a jointly certified Minor in Data Science and Machine Learning. This alliance brings together the distinguished expertise of three renowned institutions to offer an innovative educational experience tailored for ambitious professionals poised to excel in the tech industry. Minor in Data Science and Machine Learning is meticulously curated to equip learners with the essential skills, knowledge, and industry exposure required to thrive in the ever-evolving tech landscape. Delving into a comprehensive array of modules, including: ▪ Mathematics for Data Science ▪ Programming for Data Engineering ▪ Machine Learning Fundamentals ▪ Deep Learning and Neural Networks ▪ Specialized Topics in AI and ML ▪ The program culminates in impactful Capstone Projects This experiential learning approach ensures that learners not only grasp theoretical concepts but also develop practical, hands-on experience, making them well-equipped to tackle the challenges and opportunities in the realm of Data Science and Machine Learning. Empowering Your Future Minor in Data Science and Machine Learning from CCE, IIT Mandi represents a pioneering course designed for future-readiness. The curriculum co-designed by the faculty of IIT Mandi and Masai School focuses on skills that are crucial to bridge the current skill gap in a bid to improve employability. Key Highlights: ▪ Foundation Course for Each Module ▪ Jointly Designed Curriculum by IIT Mandi faculty and Masai ▪ Access to IIT Mandi Campus (Events, Fests and Graduation) ▪ CCE, IIT Mandi ID Card and Email Address ▪ Industry-tailored Capstone Projects ▪ Masterclasses by Industry Mentors for Real World Insights ▪ Placement Readiness through Portfolios and Interview Prep ▪ Guaranteed Project Interview at IIT Mandi Post Course Completion Campus Immersion Experience the vibrant academic atmosphere of IIT Mandi during the campus immersion program. Students will have the opportunity to interact directly with faculty members and immerse themselves in the scenic beauty of the IIT Mandi campus, enhancing their learning experience with firsthand insights and guidance. Course Objectives Explore Highest Paying Tech Jobs in India Unlock some of the highest paying roles in the tech industry, including AI Engineer, ML Engineer, Business Intelligence Developer, Research Scientist, Data Scientist, Big Data Engineer, Robotics Scientist and more. Forge the Future with the "Skill of the Century" Prepare yourself for the most in-demand job sector with the "Skill of the Century." India is projected to offer 10 Lakh AI-related jobs by 2026, as reported by the Deccan Chronicle. Eligibility Criteria 12th Pass Course Type Part Time Course Credits 24 Credits* Type of Degree Equivalent to a Minor Campus Immersion during Course and Graduation Two 5-Day Sessions Live Classes from IIT Faculty Graduation Ceremony at the IIT Mandi Campus Placement Opportunities Readiness through GitHub Portfolios & Interview Prep Join CCE-IIT Mandi Alumni Community Fees 1,95,000 *Credits earned will be deposited in your Academic Bank of Credit and shall be transferrable in a degree program as per NEP, NCrF, UGC, NCVET approved guidelines. Course Details Trimester Code Course Title Credits Prerequisites Pre - Foundation Course NA None Trimester 1 MTH101 Mathematics for Data Science 4 None 1 CS101 Programming for Data Engineering 2 None Trimester 2 ML101 Machine Learning Fundamentals 4 CS101 2 ML201 Deep Learning and Neural Networks 4 MTH101, ML101 3 AI101 Specialised Topics in AI/ML 6 ML101, ML201, CS101 3 CSE302 Capstone Project 4 None *Subject to change Course Type: Trimester Break: Part Time | Online 2 Weeks Trimester Duration: Timing: 16 Weeks (14 Weeks Sessions + 2 Weeks Project) Mon-Fri (8PM - 9PM) | Sat (11AM - 5PM)* Capstone Project Embark on a transformative 4-month capstone project, guided by industry experts. Apply your knowledge by building practical solutions such as an image classification system, a fraud detection model for identifying fraudulent transactions, a convolutional neural network for precise image categorization, and a personalized recommendation system tailored to user preferences. This hands-on experience is designed to refine your skills and prepare you for real-world challenges. Course Curriculum MTH101 - Mathematics for Data Science 1. Overview of AI and ML: Introduction to AI history, philosophy, and its significance in solving complex problems in various domains. 2. Mathematical Foundations: Linear algebra, calculus, probability, and statistics essentials for AI and ML. CS101 - Programming for Data Engineering 1. Data Manipulation and Analysis: Dive into Pandas for data manipulation: DataFrames, series, data cleaning, and preprocessing techniques. 2. Data Visualization Techniques: Get creative with Matplotlib and Seaborn: Crafting plots, histograms, scatter plots, and interactive visualizations to tell stories with data. ML101 - Machine Learning Fundamentals 1. Supervised Learning: Understanding the principles of supervised learning algorithms including linear regression, logistic regression, and basic classification algorithms. 2. Unsupervised Learning: Introduction to clustering, dimensionality reduction techniques, and association rule mining. 3. Ensemble Techniques and Model Selection: Boosting, bagging, random forest, and bias-variance trade-off. 4. Evaluation Metrics: Metrics for assessing model performance including accuracy, cover precision, recall, F1 score, and ROC-AUC curve. ML201 - Deep Learning and Neural Networks 1. Neural Network Fundamentals: Basics of neural networks, activation functions, and architecture design. 2. Deep Learning Algorithms: Introduction to Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory Networks (LSTMs), and Transformers. 3. Frameworks and Tools: Practical sessions on TensorFlow and PyTorch for building and training deep learning models. 4. Advanced Learning Techniques: Multi-task learning, self-supervised learning, transfer learning, and consistency regularization. 5. Reinforcement Learning: Basics of reinforcement learning, policy optimization, and applications in game playing and robotics. AI101 - Specialized Topics in AI and ML 1. Deep Dive into Generative Adversarial Networks (GANs): Understanding the architecture and working principles of GANs. Applications of GANs in image generation, style transfer, and more. Hands-on projects involving training simple GANs for specific generation tasks. 2. Natural Language Processing (NLP): Techniques for text processing, sentiment analysis, machine translation, and chatbot development. 3. Computer Vision: Fundamentals of image processing, object detection, facial recognition, and image generation with Generative Adversarial Networks (GANs). 4. Advanced Generative Models: Scene Graphs, and Probabilistic Diffusion Models. 5. Exploring Variational Autoencoders (VAEs): Introduction to the concept of autoencoders and their use in generative AI. Detailed look at VAEs and their applications in generating high-quality, diverse data samples. 6. Large Language Models (LLMs): Comprehensive overview of the architecture, training processes, and capabilities of large language models like GPT (Generative Pretrained Transformer) and BERT (Bidirectional Encoder Representations from Transformers). Discussion on their applications in natural language understanding, text generation, and conversational AI. Our Instructors Dr. Indu Joshi Dr. Neetesh Kumar Assistant Professor, IIT Mandi Assistant Professor, IIT Ropar Computing & Electrical Engineering Computer Science & Engineering Experience: 3+ yrs Experience: 9+ yrs Publication: 25 Publication: 61 Citation: 193 Citation: 1022 Dr. Gaurav Kumar Nayak Dr. Rohit Saluja Associate Professor, IIT Roorkee Assistant Professor, IIT Mandi School of Data Science School of Computing & Electrical Engineering Experience: 15+ yrs Experience: 4+ yrs Publication: 22 Publication: 13 Citation: 393 Citation: 178 Mentorship from Industry Experts Pranav Jaipurkar Drishti Mamtani Data Scientist Software Engineer III Admission Process Step 1: Limited Seats: Pay the registration fee and block your seat Step 2: Complete benchmarking test and onboarding process Step 3: Pay the remaining trimester fee and join orientation Step 4: Get your ID Card and Email of CCE, IIT Mandi Evaluation Criteria Problem Solving Communication Demonstrate your ability to Articulate your thoughts tackle real-world challenges effectively, an essential skill logically and creatively. for any professional journey. Logical Thinking Coding Aptitude Showcase your critical Highlight your coding thinking and analytical prowess through hands-on skills in assessing complex coding challenges. scenarios. Trimester & Fees Structure Registration Fee - 5,000 Pre Trimester ▪ Algebra & Functions ▪ Discrete Mathematics ▪ Applications to DS Fee ₹ 60,000/- EXIT ▪ Scorecard with 6 credits Duration Trimester 1 6 Months ▪ Trimester 1 Completion Certification ▪ Mathematics for Data Science ▪ Programming for Data Engineering Trimester 2 Fee EXIT ₹ 60,000/- ▪ Machine Learning Fundamentals ▪ Scorecard with 8 credits ▪ Deep Learning and Neural Networks Duration ▪ Trimester 2 Completion 4 Months Certification Trimester 3 Fee COMPLETE ₹ 70,000/- ▪ Scorecard with 10 credits ▪ Specialised topics in AI/ML ▪ Minor Certification ▪ Capstone Project Duration 4 Months ▪ Job Assurance ▪ Taught by IIT Professors ▪ Taught by Industry Experts Frequently Asked Questions What is the Minor in Data Science and Machine Can the credits from this program be Learning from CCE, IIT Mandi? transferred to learner's college or university? It’s a one year, outcome-driven program created Credits earned will be deposited in your Academic by CCE, IIT Mandi in collaboration with Masai Bank of Credit and shall be transferrable in a School and NSDC to bridge the gap between degree program as per NEP, NCrF, UGC, NCVET industry and academia. The program focuses on approved guidelines. key skills that are crucial to starting a career in Data Science & Machine Learning. Will I get any credits on completing the program? Is prior coding experience required? Yes, the program offers 24 credits that are No prior coding experience is required to join equivalent to a minor. this program. What is the eligibility criteria for the program? How do I know if this program is for me? The eligibility criteria for the program is 12th Minor in Data Science and Machine Learning from pass. However, individuals will have to clear the CCE, IIT Mandi is ideal for anyone who wants to benchmarking test as well. start a career in DS & ML and aspires to experience an IIT-like learning. What is the duration of this program? What is the program fee? The duration of the program is twelve months. The total fee for the Minor in Data Science and Machine Learning from CCE, IIT Mandi is ₹ 195,000. For More Queries [email protected] www.masaischool.com/iit-mandi-ai-ml

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