Gen AI Engineer Course & Curriculum

NCPL's hands-on Gen AI Engineer training — full curriculum, real projects, certification prep, and job placement support. We train, mentor and place you.

Module 1: LLM Foundations & Prompt Engineering

12 hours covering transformers, NLP fundamentals, and prompt engineering techniques.

  • Transformer architecture and attention mechanisms
  • LLM capabilities and limitations
  • Zero-shot, one-shot, and few-shot prompting
  • Chain-of-thought reasoning
  • Prompt templates and optimization
  • Python for AI development
  • Jupyter notebooks and development environments

Module 2: Advanced Architectures & RAG

15 hours on fine-tuning, RAG implementation, and model adaptation techniques.

  • Retrieval-Augmented Generation (RAG)
  • Vector databases and embeddings
  • Fine-tuning techniques (LoRA, QLoRA)
  • Model evaluation and benchmarking
  • LangChain and LlamaIndex frameworks
  • Document processing and chunking strategies
  • Context window optimization

Module 3: Cloud Deployment & Production

13 hours on deploying AI systems to AWS, Azure, and GCP with containerization.

  • AWS Bedrock and SageMaker deployment
  • Azure OpenAI Service integration
  • Google Cloud Vertex AI
  • Docker containerization for AI
  • Kubernetes orchestration
  • CI/CD pipelines for ML
  • Model monitoring and observability

Module 4: Advanced Topics & MLOps

10 hours on AI agents, function calling, and production MLOps practices.

  • AI agents and autonomous systems
  • Function calling and tool use
  • Multi-modal AI applications
  • Model versioning and experiment tracking
  • A/B testing for AI systems
  • Cost optimization strategies
  • Security and compliance considerations