Final Year AI & DS Capstone & Advanced Engineering
Large Language Model Operations, Computer Vision Systems, and Research Thesis Frameworks
The Final Year degree track synthesizes undergraduate technical training into applied capstone engineering, state-of-the-art generative modeling, machine learning operations (MLOps), and research thesis publications.
Capstone Research & Advanced Frontiers
Final Year students engage in industrial-grade project implementations and advanced theoretical domains:
Final Year Capstone Domains
- Natural Language Processing & Generative LLMs: Transformer self-attention architectures, positional embeddings, fine-tuning mechanisms (LoRA, QLoRA), and retrieval-augmented generation (RAG) pipelines.
- Computer Vision Systems: Object detection (YOLO, Faster R-CNN), semantic segmentation (U-Net), 3D scene reconstruction, and real-time video stream processing.
- Machine Learning Operations (MLOps): Automated model training pipelines, CI/CD for ML models, feature stores, drift detection, and production model monitoring.
- Major Capstone Engineering Thesis: Empirical research design, peer-reviewed paper writing, baseline benchmarking, and hardware acceleration deployment.
Repository Schedule & Thesis Guidelines
Capstone project guidelines, documentation templates, latex IEEE paper formats, and advanced seminar slide decks compiled by Sarthak Pawar will be made available as final year academic sessions open.
Repository Notice: All project templates and paper guidelines hosted on this platform adhere strictly to university thesis guidelines and open-source software licensing standards.