Advanced Generative AI
Master the state of the art in Generative AI. This course covers Prompt Engineering patterns, Retrieval Augmented Generation (RAG), vector databases (ChromaDB, Pinecone), LangChain and LlamaIndex frameworks, API orchestrations, and parameter-efficient fine-tuning (PEFT/LoRA) of open-source models like Llama-3.
Program Highlights
Target Audience
Developers, IT Professionals, and Data Engineers seeking to implement LLM technologies in corporate databases.
Prerequisites
Good python programming foundation. Experience with APIs is helpful.
Job Roles & Careers
Generative AI Engineer, LLM Developer, NLP Solution Specialist.
Salary Outlook
₹7.5 LPA - ₹18 LPA
Detailed Course Syllabus
- OpenAI, Anthropic, Gemini, and Local (Ollama) API setup
- Prompt Patterns: Few-shot, Chain-of-thought, Self-consistency
- Structured outputs: JSON schema generation and validation libraries
- Chains, Router chains, and custom prompt templates
- Memory management: Conversational Buffer, Summary Memory
- LlamaIndex Document Ingestion, Nodes, and Index Engines
- Chunking strategies: Recursive character, semantic chunking
- Embedding models, Cosine similarity, Euclidean distance metrics
- Vector Databases: ChromaDB, Pinecone, Milvus setup and queries
- Advanced RAG: Query translation, reranking, hybrid search (Sparse + Dense)
- Running HuggingFace models locally (Llama, Mistral, Gemma)
- Model quantization: GGUF, AWQ, GPTQ formats
- Parameter Efficient Fine-Tuning (PEFT): LoRA, QLoRA, dataset preparation, training run
- LLM security: Prompt Injection prevention, toxicity filtering
- Guardrails setup (NeMo Guardrails, Llama Guard)
- Deploying LLM apps using vLLM, Streamlit, and cloud containers
Batches & Timings
Weekday Batch
Monday - Friday (8:00 AM - 10:00 AM)
Weekend Batch
Saturday & Sunday (1:00 PM - 5:00 PM)
Career Benefits & Outcomes
Building custom semantic search engines on enterprise PDF knowledge bases
Hands-on quantization and fine-tuning on Google Colab/Kaggle GPUs
Learning techniques to mitigate LLM hallucinations
Mock technical rounds addressing architecture design of Generative systems
Direct corporate network intros for AI consulting roles
Quick Summary
- Duration: 2 Months
- Format: Classroom & Online
- Placement Support: 100% Assistance
- Batch: Weekday / Weekend
- Live Projects: Enterprise Projects
Quick Enquiry
Have questions? Ask our academic counselors.