B.Tech. in
Computer Science Engineering Specialization in Artificial Intelligence & Machine Learning (Major) & Cyber Security (Minor)
In Collaboration with
Course Highlights
Introduction
Bachelor of Technology in Computer Science Engineering with a specialization in Artificial Intelligence & Machine Learning is one of the top-notch careers of this new decade. Technology is such a field, which never gets static. It’s a dynamic branch of sweeping innovations and experiments.
While Artificial intelligence is driving towards creating a simulation of human intelligence and behavior, Machine learning on the other hand is a subset of AI that enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed.
According to research, it’s estimated that about 30 percent of all the
B2B companies will be employing AI to boost at least one of their sales
processes. This throws light, on a very important aspect of this field, the
‘job demand’ in the market. With a BTech in the field, one would expect
much higher returns in comparison to other traditional engineering
fields.
Eligibility
Passed 10+2 examination with Physics, Mathematics, and one of the following subjects:
Chemistry / Computer Science / Electronics / Information
Technology / Biology / Informatics Practices / Biotechnology /
Technical Vocational Subject / Agriculture / Engineering
Graphics / Business Studies / Entrepreneurship.
Obtained at least 45% marks (40% for candidates belonging to
reserved categories) in the above subjects taken together.
OR
Passed D.Voc. stream in the same or allied sector.
The university may offer suitable bridge courses such as
Mathematics, Physics, Engineering Drawing, etc., for students
coming from diverse backgrounds to ensure a level playing
field and desired learning outcomes of the program.
Note: Physics and Mathematics are mandatory subjects at the
10+2 level.
Duration
4 Years Full-Time
Tuition Fees
Rs. 98,000 per Semester
*Fees such as Admission, Caution Money, Examination, Hostel, and Transport fees are extra.
Program Details
Computer Vision
Understanding and developing algorithms that enable computers to interpret and process visual information from the world.
Natural Language Processing (NLP)
Techniques and models for machines to understand, interpret, and generate human language.
Generative AI & Prompt Engineering
Creating AI systems that can generate new content such as text, images, or music, and crafting effective prompts to guide AI behavior.
Agentic AI
Designing AI agents that can make autonomous decisions and act proactively in complex environments.
Deep Learning
Advanced neural network architectures and techniques for training AI models on large datasets.
Program Outcome
Develop AI and ML Solutions
Design, implement, and evaluate
AI and machine learning models
for real-world applications across
industries.
Apply Advanced Techniques
Utilize cutting-edge technologies
such as deep learning, natural
language processing, computer
vision, and generative AI to solve
complex problems.
Engineer Intelligent Systems
Build autonomous and agentic AI
systems capable of decision-
making and learning in dynamic
environments.
Analyze and Interpret Data
Extract meaningful insights from
large datasets using statistical
and computational techniques.
Collaborate Effectively
Work in multidisciplinary teams
to develop innovative AI-driven
products and services.
Address Ethical and Social Implications
Recognize and address ethical,
privacy, and societal impacts of
AI technologies.
Engage in Lifelong Learning
Continuously update knowledge
and skills in this rapidly evolving
field through research and
professional development.
Communicate Effectively
Present technical concepts and
solutions clearly to both
technical and non-technical
audiences.
Placement Opportunities
IT & Software Development
Roles: AI/ML Engineer, Software Developer, Data Scientist, NLP Engineer, DevOps Engineer
Top Companies: Google, Microsoft, Amazon, Infosys, TCS, Wipro, HCL
Skills Needed: Python, Java, TensorFlow, PyTorch, Git, API integration
Artificial Intelligence Research & Product Development
Roles: AI/ML Engineer, Software Developer, Data Scientist, NLP Engineer, DevOps Engineer
Top Companies: Google, Microsoft, Amazon, Infosys, TCS, Wipro, HCL
Skills Needed: Python, Java, TensorFlow, PyTorch, Git, API integration
Data Science & Analytics
Roles: Data Analyst, Data Engineer, Business Intelligence Analyst
Companies: Mu Sigma, Fractal Analytics, Accenture, Deloitte, ZS Associates
Skills Needed: SQL, Python/R, Tableau/Power BI, Statistics, Pandas, NumPy
Cybersecurity & Threat Intelligence Roles: Security Analyst, Threat Inte
Roles: Security Analyst, Threat Intelligence Engineer, AI in Security Developer Companies: Palo Alto Networks, Cisco, FireEye,
CrowdStrike Skills Needed: Ethical Hacking, Network Security, AI for anomaly detection, SOC analysis
Robotics & Automation
Roles: Robotics Software Engineer, Automation Engineer, Computer Vision Engineer Companies: Boston Dynamics, GreyOrange, ABB,
NVIDIA
Skills Needed: ROS, OpenCV, Python/C++, TensorFlow, Real-Time Systems
Healthcare & Bioinformatics
Roles: AI Healthcare Analyst, Medical Imaging AI Specialist, Bioinformatics Engineer
Companies: Philips, Siemens Healthineers, GE Healthcare
Skills Needed: Medical datasets, Deep Learning, NLP for EHR, Bioinformatics Tools
FinTech & Banking
Roles: Quant Analyst, Fraud Detection Analyst, Risk Modeling Engineer
Companies: JPMorgan Chase, Goldman Sachs, Paytm, Razorpay
Skills Needed: Python, Financial Modelling, ML algorithms, Risk Assessment tools
EdTech & Online Platforms
Roles: AI Curriculum Developer, Adaptive Learning Engineer, Content Recommendation
Engineer
Companies: BYJU’S, Unacademy, Coursera, upGrad
Skills Needed: Recommendation Systems, Personalization Algorithms, A/B Testing
Government & Defense
Roles: AI Scientist, Research Assistant, Cyber Analyst
Organizations: DRDO, ISRO, NIC, CDAC, BARC
Skills Needed: Strong theoretical foundation, Security clearance, Research aptitude
Startups & Entrepreneurship
Roles: Founders, Co-Founders, AI Solution Architect
Opportunities: Launch AI-based products, ML consultancy, AI SaaS platforms
Support: Incubators (NASSCOM, CIIE, Y Combinator)
Higher Studies and Research
Opportunities: MS/PhD in AI/ML abroad or in IITs/IISc
Exams: GRE, GATE, TOEFL/IELTS
Focus: Research publications, internships, open-source contributions
Lab List
1. Python Programming Lab
Basics of programming, OOPs in Python
2. Data Structures & Algorithms Lab
Implement stacks, queues, trees, graphs
3. Database Management Systems Lab
SQL queries, normalization, transaction control
4. Machine Learning Lab
Linear regression, classification, clustering, SVM, KNN (using Scikit-Learn)
5. Deep Learning Lab
Build ANN, CNN, RNN models using TensorFlow/PyTorch
6. Natural Language Processing (NLP) Lab
Text preprocessing, sentiment analysis, NER, language models
7. Computer Vision Lab
Image filtering, object detection, OpenCV, YOLO models
8. Artificial Intelligence Lab
Search algorithms (A*
, BFS, DFS), Minimax, Game AI, Expert Systems
9. Data Science & Analytics Lab
Data wrangling, EDA, feature engineering with Pandas, visualization
10. Cloud & Edge AI Lab
Deploy AI models using AWS/GCP , use Raspberry Pi/Jetson Nano
11. Ethics & Explainable AI (XAI) Lab (Advanced/Optional)
Use SHAP , LIME, fairness evaluation in models
12. Capstone Project / Research Lab
Final-year end-to-end AI/ML project, often industry or research focused
Where Talent Meets Opportunity:
Our Graduates Are Building Futures with Leading Companies
