This program begins with Python programming fundamentals required for AI development, including data structures, functions, object-oriented programming, file handling, and exception handling. Learners then move into Natural Language Processing, covering text preprocessing, text representation techniques, and word embeddings.

The course advances into deep learning concepts such as ANN, RNN, LSTM, Encoder-Decoder architectures, Attention mechanisms, and Transformers. Learners will gain hands-on experience using TensorFlow, Keras, and modern NLP evaluation metrics.

In the Generative AI modules, learners will explore Large Language Models (LLMs), prompt engineering, vector databases, LangChain, fine-tuning techniques, and Retrieval-Augmented Generation (RAG). The program concludes with advanced RAG techniques, AI agents, production deployment using Streamlit, Docker, AWS, and CI/CD pipelines, along with multiple end-to-end capstone projects.

• One Program. Complete AI Stack.
  Master Python, NLP, Deep Learning, and Generative AI in one structured, industry-ready road-map.

• Beginner to Gen - AI Engineer Journey
  Start with Python fundamentals and progress step-by-step to LLMs, RAG systems, and AI Agents.

• Hands-On, Project-Driven Learning
  Build real-world applications such as chatbots, document Q&A systems, semantic search, and AI assistants.

• Industry-Aligned Curriculum
  Covers modern AI stacks including Transformers, Prompt Engineering, Vector Databases, LangChain, and LLM fine-tuning.

• Advanced Generative AI & RAG Expertise
  Master Hybrid Retrieval, Agentic RAG, Multimodal RAG, Guardrails, Observability, and RAG evaluation using RAGAS.

• Production-Grade Deployment Skills
  Learn to deploy and scale AI applications using Streamlit, Docker, AWS, and CI/CD pipelines.

• Modern Tools & Open-Source Ecosystem
  Work with TensorFlow, Keras, Hugging Face, OpenAI APIs, FAISS, ChromaDB, and LangChain.

• Business-Centric Use Cases
  Apply AI to real-world scenarios like enterprise search, customer support automation, and intelligent assistants.

• Capstone-Focused Learning
  Showcase multiple end-to-end projects that demonstrate real-world problem-solving and production readiness.

• Career-Ready Skillset
  Prepare for high-demand roles such as AI Engineer, NLP Engineer, GenAI Developer, and ML Engineer.