BTech in AI and Data Analytics


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:

  1. Mathematical Foundations: Delve deep into the mathematical underpinnings of data science and artificial intelligence, laying a robust groundwork for advanced analysis and modelling.
  2. 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.
  3. Learning Algorithms and Statistical Inferencing: Master the art of algorithmic design and statistical inference, essential for extracting meaningful insights from vast datasets.
  4. Programming Skills: Hone programming skills tailored for crafting cutting-edge data science and AI solutions, leveraging the latest tools and languages.
  5. 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.
  6. Systems Thinking: Cultivate a systems thinking mindset crucial for deploying machine learning solutions effectively within real-world contexts.
  7. Mathematical Modeling and Simulation: Harness the power of mathematical modelling, computational methods, and simulation techniques to simulate and analyze complex systems.
  8. Application to Real-world Problems: Apply data analytics and AI techniques to tackle real-world challenges across diverse domains, fostering innovation and impact.
  9. 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

Foundations of Linear AlgebraCoreScience9
Calculus for EngineersCoreScience9
Programming and Data StructuresCoreComputation9
Programming LaboratoryCoreComputation6
Basics of Engineering PrinciplesCoreEngineering9
Life Skills ICoreGeneral4
Ecology and EnvironmentCoreGeneral2
NSO / NCC / NSSElectiveGeneral2
Recreation IElectiveGeneral2
Workshop ICoreEngineering3

Semester II

Introduction to Computational ChemistryCoreScience9
Probability & Statistics for EngineersCoreScience10
Optimization for EngineersCoreEngineering9
Optimization Lab*CoreEngineering6
Life Skills IICoreGeneral2
Recreation IICoreGeneral2
NSO / NCC / NSSElectiveGeneral2
Computational Methods for DSCoreProfessional10

Semester III

Introduction to Computational PhysicsCoreScience9
Machine Learning ICoreProfessional9
Machine Learning LabCoreProfessional6
Introduction to Computational BiologyCoreScience9
Data Curation and VisualizationCoreProfessional9
Entrepreneurship CourseCoreManagement9

Semester IV

Algorithms for Data ScienceCoreProfessional9
Introduction to Computer SystemsCoreProfessional9
Artificial IntelligenceCoreProfessional9
AI LabCoreProfessional6
Physics ElectiveElectiveScience9
Free (Unallotted) ElectiveElectiveFree9

Semester V

Machine Learning IICoreProfessional9
ML ops LabCoreProfessional6
Core Basket – IElectiveProfessional9
Dept. ElectiveElectiveProfessional9
Deep LearningCoreProfessional9
DL LabCoreProfessional6

Semester VI

Free (Unallotted) ElectiveElectiveFree9
Free (Unallotted) ElectiveElectiveFree9
Humanities CourseElectiveHumanities9
Free (Unallotted) ElectiveElectiveFree9
Free (Unallotted) ElectiveElectiveFree9

Semester VII

Online & Reinforcement LearningCoreProfessional9
Core Basket – IIElectiveProfessional9
Responsible AICoreProfessional9
Dept. ElectiveElectiveProfessional9
Humanities ElectiveElectiveHumanities9
Project ICoreProfessional9

Semester VIII

Project II / ElectiveElectiveProfessional18
Professional EthicsCoreGeneral2
Humanities ElectiveElectiveHumanities9