Curriculum
Curriculum
A rigorous B.Tech CSE (AI & Data Science) curriculum strikes a good balance between foundational computer science, specialized AI and Data Science knowledge, real-world application, and research or innovation. Below is a detailed outline, along with focus areas, that align with global standards (like ACM / IEEE guidelines) and meet industry demands.
Focus Areas of CSE(AI & DS): The focus areas of the CSE(AI & DS) include the following:
- Core courses: Develop expertise in AI, data modeling, and analytics: Artificial Intelligence, Machine Learning, Deep Learning, Data Science & Analytics, Natural Language Processing, Computer Vision, Big Data Technologies (e.g., Hadoop, Spark), Data Mining & Warehousing, Time Series and Forecasting, Data Visualization, Reinforcement Learning, Explainable AI, Cloud Computing for AI.
- Advanced Computing & Integration Courses: Internet of Things (IoT) and AI, Edge and Fog Computing, AI for Cybersecurity, Blockchain and AI Integration, AI for Healthcare / Finance / Smart Cities (domain electives), Human-Centered AI, Ethics in AI and Data Governance, MLOps and DevOps for AI deployment, Scalable Systems and Distributed Computing, Quantum Machine Learning.
- Advanced AI & ML: Reinforcement Learning, Generative AI (GANs, Transformers), AI in Robotics..
- Natural Language Processing, Computer Vision & Image Analytics: Multilingual NLP, Chatbots and Conversational AI, Large Language Models (LLMs), Medical Imaging, Surveillance Systems, Augmented Reality.
- Data Engineering & Cloud AI: Data Lakes and Pipelines, Cloud-Native ML Architectures (AWS, Azure, GCP), Serverless AI systems..
Career Options for CSE(Artificial Intelligence & Data Science)
A degree in CSE (AI & DS) opens up endless career possibilities. Some top career options that reputed companies hire after CSE (AI & DS) degree include the following job roles:
- AI Data Analyst
- Product Manager
- Business Analyst
- Data Scientist
- Research Scientist
- Business Intelligence Developer
- Artificial Intelligence / Machine Learning Developer
- Lead Artificial Intelligence / Machine Learning Engineer
- Artificial Intelligence / Machine Learning Architect
- Information Security Analyst, and more.
