M Tech - Artificial Intelligence
and Data Science (AI & DS)

Artificial Intelligence (AI) and Data Science (DS) are closely related fields that often overlap but have distinct focuses and methodologies. They provide robust and scalable solutions to real-world complex problems. Data Science focuses on the systematic extraction, processing, and analysis of large volumes of data using statistical and computational methods. On the other hand, Artificial Intelligence uses advanced algorithms, deep learning models, and predictive systems to simulate human intelligence and automate decision-making processes. Together, they drive innovation across industries such as healthcare, finance, agriculture, education, and autonomous systems, transforming how data is utilised, interpreted, and acted upon.

• For Semester I, core subjects such as Artificial Intelligence, Data Science and Management, Data Structures & Algorithms for Problem Solving, Python for Data Science, and Deep Learningare introduced. In addition, students gain hands-on exposure through the Algorithms and AI Laboratory and are introduced to academic research principles through Research Methodology and IPR (Online). These courses together build a strong foundational understanding of the AI-DS domain, comprising 18 credits.
• For Semester II, the focus shifts to applied technologies and real-world integration. Subjects include Internet of Things and Applications, Advanced Operating Systems, and Big Data Analytics, enabling students to explore how AI and DS interact with connected devices and distributed systems. Additionally, students undertake a Mini Project with Seminar, select two Professional Elective Coursesbased on their interest, and complete practical work through the Big Data Analytics Laboratory. A Skill Enhancement for Research online module also supports their research preparedness. This semester accounts for 22 credits.
• For Semester III, students engage in three online courses (each of 12 weeks duration)approved as Professional Electives. These are offered through leading MOOC platforms and are selected in line with the latest industry demands. Alongside, students begin a Research Internship / Industry Internship / Startup Phase-I, where they apply their classroom learning in a practical, real-world or research-based environment. This semester comprises 12 credits.
• Students initiate their Project Work – Phase Iin Semester III, which is based on their internship exposure and guided by faculty mentors or industry professionals. This prepares them for final implementation and evaluation in the next phase.
• Semester IVis fully dedicated to Project Work – Phase II and the continuation of the internship or research project. The project is evaluated through a detailed report submission and a final viva voce. This semester carries 16 credits, marking the culmination of the program and demonstrating the student’s ability to apply knowledge to real-world problems.

Internship and Certification Programmes

• Internships are an integral part of the AI & DS curriculum. They provide students with exposure to practical tools, frameworks, and environments that are widely used in the industry. The internship experience not only enhances technical proficiency but also improves teamwork, problem-solving, and project execution skills.
• Domains where students can pursue internships include:
  Machine Learning and Deep Learning– for building intelligent prediction models and neural networks
  • Natural Language Processing (NLP) – for applications in chatbots, speech recognition, and sentiment analysis
  • Computer Vision – for facial recognition, medical imaging, and real-time video analytics
  • Data Analytics and Business Intelligence – for creating dashboards, visualisations, and decision-making reports
  • Big Data and Data Engineering – for building scalable data pipelines and working with distributed systems like Hadoop and Spark
  • Reinforcement Learning – for training autonomous agents using reward-based systems
  • Robotics and Autonomous Systems – integrating AI algorithms with real-world control systems

The curriculum also encourages students to take up online certification courses in trending technologies through platforms like Coursera, edX, and NPTEL, further enhancing their employability and industry-readiness.