Bachelor of Technology

Artificial Intelligence & Data Science | B.Tech (AIDS)

In the last few years, Artificial Intelligence (AI) and Machine Learning (ML) based applications have demonstrated significant improvements in business processes and eventually business success, hence attracting lots of opportunities for further development in this area. Utilization of AI, and ML data science technologies in the automation of many tasks from different business sectors such as healthcare, e-commerce, climatology, Social media and networking, transportation, etc., demands skilled professionals in this domain.

The department aims to develop ability in students to analyze, design, and provide novel AI/ML-based solutions to solve problems from diverse fields. We also focus on building appropriate professional attitudes, ethics, and social concern among students. Ample numbers of opportunities are available in this field for employment and subsequent career growth for the students including, Business Intelligence developers, AI engineers, Big Data architects, Data engineers, Data scientists, application developers, software architects, and many more.

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Key Information


Experienced and proficient faculty with upgraded and advanced teaching methodologies via Google classroom, Virtual labs, Smart board, Microsoft office tool for content delivery. Faculty members follow the efficient course engagement strategies to ensure the active learning from the students.

Our education inspires students to apply in global corporate companies and lead their career path in a better way. They are made aware of their responsibilities towards the betterment of society and are prepared to take on interesting challenges along the way.


  • Growing Demand

    The demand of professionals in the field of AI and Data science are increasing exponentially. Due to the transition from manual processes to automation of processes, organizations started realizing the benefits of AI-DS; almost every business sector is adopting the digital automation and hence huge requirements of AI, DS professionals.

  • Strong Industry Connect

    Industry-Department collaboration helps to build Industrial competent students by providing opportunities to work with leading companies, Government organizations, Public Sector Undertakings, Ministries and Foreign universities for consultancy projects, research projects and internships. Option for Semester long internship is available for getting better industry exposure.

  • Vibrant Student Life

    Multicultural and vibrant campus life with numerous technical and cultural events in building proactive students. Well established and profoundly active professional student bodies of the department (Codecell, CSI) help the student to have not only to develop technical skills but leadership and entrepreneurship skills.

  • Project Based Learning

    Students exposure to innovative project development under the able guidance of faculty members, leading to accolades at national contests like Smart Indian Hackathon, Robocon etc. help to inculcate critical thinking, creative thinking and entrepreneur skills.

  • Cutting Edge Laboratories Infrastructure

    Sophisticated cutting edge laboratories with the latest infrastructure for parallel computing, cloud computing, Penetration Testing and Internet of Things provide quality academic experience for students.


Semester I Semester II
Course Group C Course Group C
Theory courses Theory courses
Applied Mathematics - I Applied Mathematics - II
Engineering Chemistry Engineering Physics
Engineering Drawing Engineering Mechanics
Elements of Electrical and Electronics Engineering  
Lab/Tutorial courses Lab/Tutorial courses
Python Programming Programming in C
Engineering Chemistry Laboratory Engineering Physics Laboratory
Elements of Electrical & Electronics Engineering Laboratory Engineering Mechanics Laboratory
Project-Based Learning Project-Based Learning
Basic Workshop Practice - I Presentation & Communication Skills
Engineering Drawing Laboratory Basic Workshop Practice - II
Exposure Course* Exposure Course*
Course Group P Course Group P
Theory courses Theory courses
Applied Mathematics - I Applied Mathematics - II
Engineering Physics Engineering Chemistry
Engineering Mechanics Engineering Drawing
  Elements of Electrical & Electronics Engineering
Lab/Tutorial courses Lab/Tutorial courses
Python Programming Programming in C
Engineering Physics Laboratory Engineering Chemistry Laboratory
Engineering Mechanics Laboratory Engineering Drawing Laboratory
Project-Based Learning Elements of Electrical & Electronics Engineering Laboratory
Presentation & Communication Skills Project-Based Learning
Basic Workshop Practice - I Basic Workshop Practice - II
Exposure Course* Exposure Course*

Note- Students will be assigned either course group C or P in semester I irrespective of their branch of study. Accordingly, they will have the other course group (P or C) in semester II

*mandatory non-credit course to be selected from a variety of courses from sports (indoor and outdoor), music, dance, creative art, culture, religion, yoga, broadcasting, film-making etc.

Semester III Semester IV
Core Course Core Course
Discrete & Applied Mathematics Probability, Statistics & Optimization Techniques
Data Structures Design & Analysis of Algorithms
Database Management Systems Advanced Databases
Data Communication and Networking Object oriented Software Engineering
Information Theory & Coding Fundamentals of Data Science
Programming Laboratory : Java / Python /C++ Competitive Programming
  Web Programming - I
Semester V Semester VI
Core Course Core Course
Operating Systems Cloud Computing
Artificial Intelligence Machine Learning
Web Programming - II Natural Language Processing
Information and Network Security  
Department Elective-I Department Elective-II
Internet of Things Neural Network & Fuzzy Systems
Software Testing and Quality Assurance Digital Image Processing
Cyber Laws Vulnerability Analysis and Penetration testing
Devops Data Warehousing and Analytics
Computer Graphics And Virtual Reality Geographical Information Systems
Open Elective Technical – I/ Online SWAYAM/Coursera Course Open Elective Technical – I/ Online SWAYAM/Coursera Course
Open Elective Humanities/ Management Open Elective Humanities/ Management
Semester VII Semester VIII
Core Course Core Course
Deep Learning Project –II
Project –I  
Department Elective -III Department Elective -V
Computer Vision / Soft Computing Information Retrieval
Business Analytics Semantic Web
HPC for AI/ML Malware Analysis
UI Programming Massive online data Analytics
Advanced Computer Networks Robotics and AI
Department Elective-IV Department Elective-VI
Algorithms for Big Data Analytics Pattern Recognition
Spatial Data Analytics MLops
Digital Forensics Ethical AI
Digital Marketing Graph and Network Analysis
Blockchain Development Framework Metaverse

Programme Outcomes

After successful completion of the program an Electronics Engineering Graduate will be able to:

Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health and safety and the cultural, societal, and environmental considerations.

Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data,and synthesis of the information to provide valid conclusions.

Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.

Apply reasoning informed by the contextual knowledge to assess societal, cultural, environmental, health, safety and legal issues relevant to the professional engineering practice; understanding the need of sustainable development.

Recognize/ study/analyze/provide solutions to real- life problems of multidisciplinary nature from diverse fields

Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary settings.

Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend & write effective reports and design documentation, make effective presentations and give and receive clear instructions.

Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Career Paths

  • Business Intelligence developers
  • AI engineers
  • Big Data architects
  • Data engineers
  • Data scientists
  • application developers
  • software architects
  • Computer Programmer
  • Network Engineer
  • IT Consultant
  • Software Designer
  • Systems Analyst
  • Scientific Researcher
  • Database Administrator
  • Researcher & Academician
  • Software Testing Engineer
  • IT Manager
  • SEO Expert
  • Games Developer
  • Mobile Application Developer
  • Web Application Developer
  • UI/UX Designer
  • Network Administrator
  • Business Analyst
  • System Administrator
  • Cyber Security Analyst
  • Computer Forensic Analyst

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