The most comprehensive program. Covers the entire stack — from transformer architecture and model fine-tuning to RAG systems, multimodal AI, MLOps, and production deployment. Designed for students targeting AI engineer, ML engineer, or GenAI developer roles at product companies and AI startups.
Self-attention, positional encoding, encoder-decoder models. Understand GPT, BERT, and T5 from the ground up — not just use them, but know how they work.
Vision-language models, image generation (diffusion models), text-to-speech, speech-to-text. Build applications that understand and generate across text, image, and audio.
Build, train, and fine-tune neural networks. Model serialization, transfer learning, and adapting pre-trained models for domain-specific tasks.
CI/CD for ML, containerization, model monitoring, drift detection, GPU optimization, and cost management. Ship AI systems, not just notebooks.
Build retrieval-augmented generation pipelines — embeddings, vector search, LangChain, hybrid retrieval. The architecture behind enterprise AI search and Q&A systems.
Build real applications — chatbots, code assistants, content generation platforms, knowledge management systems. These patterns used by companies in production.
Build autonomous agents with planning, tool use, and multi-step reasoning. Orchestrate multiple agents for complex real-world workflows.
Design, build, test, and deploy a complete GenAI application — RAG system, AI assistant, or creative AI tool. Portfolio-ready with architecture documentation.
E-305, Industrial Area, Sahibzada Ajit Singh Nagar, Punjab 160055, IN
