CSE ( AI & Data Science)
Program Overview
The B.Tech in Computer Science & Engineering (Artificial Intelligence & Data Science) at Dayananda Sagar University (DSU) is designed to prepare students for the next generation of intelligent computing, data-driven innovation, and AI-powered applications.
The program combines strong foundations in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Generative AI, Computer Vision, Natural Language Processing, Cloud Computing and Edge AI with hands-on exposure to industry-relevant technologies.
With DSU's growing NVIDIA-powered AI ecosystem, students can move beyond conventional classroom learning and gain experience across the AI technology stack—from GPU-accelerated computing and CUDA programming to large-scale AI model training, deployment and real-world intelligent applications.
DSU's NVIDIA AI ecosystem includes an enterprise-class AI Factory featuring 20 NVIDIA DGX B200 nodes and 160 GPUs, providing a production-oriented environment for AI learning, research and innovation. Students can explore technologies and workflows used in modern AI development, including CUDA, PyTorch, TensorFlow, RAPIDS and TensorRT.
The program is designed around an AI-first, industry-aligned learning model, enabling students to develop, accelerate and deploy intelligent solutions across domains such as healthcare, autonomous systems, computer vision, natural language, enterprise AI, robotics, finance and data-intensive applications.
Why Choose CSE (AI & Data Science) at DSU?
- NVIDIA-Powered AI Learning Ecosystem
Students gain exposure to an advanced NVIDIA AI computing environment, including DGX B200 infrastructure, GPU computing and accelerated AI workflows.
The AI Factory provides an environment where students can progress from foundational AI concepts to large-scale model development and production-oriented AI applications.
- Learn the Complete AI Technology Stack
Students gain exposure to AI Technology Stack comprising the tools used to develop, train, evaluate, and deploy AI solutions.
DSU's current AI & DS curriculum specifically includes tools such as Python, NumPy, Pandas, and Scikit-learn for data processing and ML; TensorFlow and PyTorch for DL; Hugging Face and LLM APIs for Generative AI and NLP; OpenCV and YOLO for computer vision; SHAP and Grad-CAM for explainable AI; Flower and TensorFlow Federated for FL; and Docker, Git, MLflow, and cloud platforms for deployment and MLOps.
- From AI Fundamentals to Production-Scale AI
The curriculum offers a progressive learning pathway from AI fundamentals and core concepts to advanced model development, deployment, optimization, and production-scale AI systems.
Students build practical expertise through hands-on projects, GPU computing, Generative AI, MLOps, and industry applications.
Students can begin with programming, mathematics, statistics and data science and progressively move toward GPU-accelerated model training, AI inference and production AI systems.
- NVIDIA Deep Learning Institute Exposure
Through its NVIDIA ecosystem, students can access learning opportunities around GPU programming, deep learning and accelerated computing.
The present curriculum offers NVIDIA Deep Learning Institute (DLI) workshops as part of the department's industry-oriented learning ecosystem.
- Industry-Aligned Curriculum
An Industry-Aligned Curriculum is designed to bridge the gap between academic learning and current industry requirements by integrating emerging technologies, practical skills, real-world projects, internships, industry certifications, and hands-on laboratory experience.
It emphasizes AI, Data Science, Cloud Computing, Generative AI, Cybersecurity, MLOps, and Software Engineering, while developing problem-solving, teamwork, communication, and professional skills.
These areas are reflected in DSU's current 2026 AI&DS curriculum.
- Build Real-World AI Systems
Build Real-World AI Systems focuses on developing practical AI solutions that address real-world problems through hands-on projects, industry datasets, ML models, deployment tools, and end-to-end AI workflows.
Students gain experience in problem identification, data processing, model development, evaluation, deployment, and system optimization.
DSU's AI Factory learning model specifically highlights applications in autonomous robots, medical AI, natural language, computer vision, data science and industry research.
- Research and Innovation
Research and Innovation focuses on encouraging students to explore emerging technologies, identify real-world problems, develop novel AI solutions, and conduct experimental research.
The curriculum promotes critical thinking, creativity, scientific investigation, research publications, patents, and innovative projects.
Students can participate in research projects, innovation challenges, publications, hackathons and start-up initiatives.
- Industry and Internship Opportunities
The department's current program material identifies collaborations and learning ecosystems involving organizations such as IBM, AWS Academy, Microsoft and NVIDIA, supporting industry projects, internships and research-oriented assignments.
Students can gain practical exposure through internships, industry training, expert sessions and project-based learning.
- Career-Ready AI Professionals
Career-Ready AI Professionals focuses on developing graduates with technical expertise, practical experience, problem-solving abilities, industry knowledge, and professional skills required for AI and Data Science careers.
It emphasizes hands-on projects, internships, certifications, communication skills, and industry-oriented training.
- The DSU Advantage
- From Classroom to AI Factory
Why Choose AI & Data Science for the Future?
Artificial Intelligence is moving from isolated models to large-scale, accelerated and intelligent computing systems.
The future of AI will require professionals who understand not only algorithms and data, but also GPU computing, AI infrastructure, model training, inference, deployment and intelligent applications.
At DSU, students can build these capabilities through an AI-first ecosystem supported by NVIDIA infrastructure and an industry-aligned curriculum.
The DSU Advantage provides a strong NVIDIA-powered AI ecosystem with 20 NVIDIA DGX B200 nodes and 160 GPUs, enabling hands-on learning in CUDA, GPU-accelerated computing, PyTorch, TensorFlow, RAPIDS, and TensorRT.
Students gain exposure to Generative AI, Agentic AI, Computer Vision, NLP, MLOps, High-Performance Computing, Robotics, and Edge AI using Jetson platforms.
The ecosystem is further strengthened through industry projects, internships, research, and innovation opportunities.
From Classroom to AI Factory represents a learning journey that transforms academic knowledge into industry-ready AI solutions.
Students progress from theoretical concepts and hands-on laboratory work to real-world projects, research, deployment, and scalable AI system development.
At DSU, CSE (AI & DS) is positioned to give students an opportunity to learn AI using technologies that extend from fundamental programming and data science to GPU-accelerated computing and production-scale AI systems.
The objective is not simply to teach students how to build an AI model.
It is to prepare them to build the AI systems of the future.
