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We are delighted to introduce our newly minted BTech course in AI & Data Analytics (AIDA), an exciting journey into the realms of data science and artificial intelligence. BTech AIDA is meticulously crafted to equip students with the key skills and knowledge necessary to thrive in the dynamic landscape of modern technology. This unique programme is designed to cultivate expertise in diverse facets of AI and data analytics, offering a panoramic view of its applications across industries.
At the heart of AIDA lie nine key outcomes, each serving as a pillar upon which students will build their proficiency:
- Mathematical Foundations: Delve deep into the mathematical underpinnings of data science and artificial intelligence, laying a robust groundwork for advanced analysis and modelling.
- ML / AI Models: Explore a spectrum of models, ranging from mathematical and statistical to network architectures, empowering students to develop sophisticated solutions to complex problems.
- Learning Algorithms and Statistical Inferencing: Master the art of algorithmic design and statistical inference, essential for extracting meaningful insights from vast datasets.
- Programming Skills: Hone programming skills tailored for crafting cutting-edge data science and AI solutions, leveraging the latest tools and languages.
- Data Acquisition and Pre-processing: Learn the intricacies of acquiring, pre-processing, and curating data, essential for ensuring its quality and relevance in analytical endeavors.
- Systems Thinking: Cultivate a systems thinking mindset crucial for deploying machine learning solutions effectively within real-world contexts.
- Mathematical Modeling and Simulation: Harness the power of mathematical modelling, computational methods, and simulation techniques to simulate and analyze complex systems.
- Application to Real-world Problems: Apply data analytics and AI techniques to tackle real-world challenges across diverse domains, fostering innovation and impact.
- Fair and Responsible AI: Embrace the principles of fairness and responsibility in AI development, ensuring ethical and equitable deployment of technology.
AIDA offers unparalleled flexibility, allowing students to tailor their learning journey through a wide range of electives from within the department and outside. From delving into the intricacies of Speech & Language Technology and Computer Vision to exploring Applications in Control & Detection and Time-Series Analysis, students have the opportunity to delve deeper into areas of personal passion and interest.
Our core curriculum is meticulously designed to provide a comprehensive foundation in AI and data analytics, covering a diverse array of subjects essential for success in this field. From foundational courses in linear algebra and calculus to specialized modules in machine learning, deep learning, and reinforcement learning, students are equipped with a robust toolkit to tackle the varied challenges in this discipline.
Furthermore, practical experience is ingrained into the curriculum through laboratory sessions, workshops, and real-world projects, ensuring students graduate not only with theoretical knowledge but also with hands-on expertise ready for immediate application in the industry.
Join us on this transformative journey into the realm of AI and data analytics, where innovation knows no bounds, and the possibilities are limitless. Welcome to AIDA, where the future is waiting to be shaped by your brilliance!
Detailed Curriculum
Semester I
Course | Category | Credits | |
Foundations of Linear Algebra | Core | Science | 9 |
Calculus for Engineers | Core | Science | 9 |
Programming and Data Structures | Core | Computation | 9 |
Programming Laboratory | Core | Computation | 6 |
Basics of Engineering Principles | Core | Engineering | 9 |
Life Skills I | Core | General | 4 |
Ecology and Environment | Core | General | 2 |
NSO / NCC / NSS | Elective | General | 2 |
Recreation I | Elective | General | 2 |
Workshop I | Core | Engineering | 3 |
Semester II
Course | Category | Credits | |
Introduction to Computational Chemistry | Core | Science | 9 |
Probability & Statistics for Engineers | Core | Science | 10 |
Optimization for Engineers | Core | Engineering | 9 |
Optimization Lab* | Core | Engineering | 6 |
Life Skills II | Core | General | 2 |
Recreation II | Core | General | 2 |
NSO / NCC / NSS | Elective | General | 2 |
Computational Methods for DS | Core | Professional | 10 |
Semester III
Course | Category | Credits | |
Introduction to Computational Physics | Core | Science | 9 |
Machine Learning I | Core | Professional | 9 |
Machine Learning Lab | Core | Professional | 6 |
Introduction to Computational Biology | Core | Science | 9 |
Data Curation and Visualization | Core | Professional | 9 |
Entrepreneurship Course | Core | Management | 9 |
Semester IV
Course | Category | Credits | |
Algorithms for Data Science | Core | Professional | 9 |
Introduction to Computer Systems | Core | Professional | 9 |
Artificial Intelligence | Core | Professional | 9 |
AI Lab | Core | Professional | 6 |
Physics Elective | Elective | Science | 9 |
Free (Unallotted) Elective | Elective | Free | 9 |
Semester V
Course | Category | Credits | |
Databases | Core | Professional | 9 |
Machine Learning II | Core | Professional | 9 |
ML ops Lab | Core | Professional | 6 |
Core Basket – I | Elective | Professional | 9 |
Dept. Elective | Elective | Professional | 9 |
Deep Learning | Core | Professional | 9 |
DL Lab | Core | Professional | 6 |
Semester VI
Course | Category | Credits | |
Free (Unallotted) Elective | Elective | Free | 9 |
Free (Unallotted) Elective | Elective | Free | 9 |
Humanities Course | Elective | Humanities | 9 |
Free (Unallotted) Elective | Elective | Free | 9 |
Free (Unallotted) Elective | Elective | Free | 9 |
Semester VII
Course | Category | Credits | |
Online & Reinforcement Learning | Core | Professional | 9 |
Core Basket – II | Elective | Professional | 9 |
Responsible AI | Core | Professional | 9 |
Dept. Elective | Elective | Professional | 9 |
Humanities Elective | Elective | Humanities | 9 |
Project I | Core | Professional | 9 |
Semester VIII
Course | Category | Credits | |
Project II / Elective | Elective | Professional | 18 |
Elective | Elective | Free | 9 |
Professional Ethics | Core | General | 2 |
Humanities Elective | Elective | Humanities | 9 |