Course Overview
Artificial Intelligence is evolving rapidly, and at the heart of this transformation are Generative AI, Natural Language Processing (NLP), and Multi-Agent Architectures. This course is designed to help you build real-world AI applications, from training language models to creating autonomous agents that work together seamlessly.
We start with NLP fundamentals, covering text processing, sentiment analysis, and named entity recognition (NER) using industry-standard tools like NLTK and Stanford NER. You’ll then dive into Deep Learning, exploring neural networks, recurrent models (LSTMs), and the Transformer architecture, including BERT and attention mechanisms.
Next, we demystify Large Language Models (LLMs), covering Hugging Face, prompt engineering, RAG, and fine-tuning LLMs. You’ll learn how to implement LLM agents with reasoning capabilities, understand LLMOps for deployment and scaling, and explore GenAI engineering tools like LangChain and AutoGen.
Beyond text, you’ll explore AI-driven image generation using CNNs, GANs, and diffusion models. Finally, you’ll master multi-agent architectures, learning how to build, orchestrate, and scale autonomous AI agents.
With 15+ hands-on projects, a capstone AI application, and career support, this live course equips you with everything needed to launch a career in Generative AI and agentic systems. Let’s build the future together!
What you will learn
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Learn Advanced Gen- AI Skills Learn LLMs, RAG, LangChain, LlamaIndex, and Prompt Engineering.
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Hands-On Learning with 15+ Real-World Projects Build and deploy AI applications using Flask, Streamlit, and Cloud Platforms.
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Learn from Industry Experts Get hands-on mentorship from seasoned industry professionals.
Instructor(s)
Shubham Pandey
Trainer
Shubham is a senior AI leader and practitioner with 15+ years of experience designing and deploying enterprise-scale AI systems spanning predictive intelligence, large generative models, RAG architectures, and multi-agent frameworks. His work consistently bridges cutting-edge research with real-world, production-grade implementation.
With deep hands-on expertise in machine learning, LLM engineering, and applied data science, he has built scalable AI platforms that deliver measurable business outcomes—from forecasting and decision intelligence to generative automation and autonomous workflows.
A passionate educator, Shubham teaches Statistics, Machine Learning, Deep Learning, Generative AI, and agentic system design with a strong emphasis on practical, industry-ready application. His training programs delivered to Fortune 500 organizations and global engineering, data, and product teams have upskilled thousands of professionals and accelerated enterprise AI adoption.
Generative AI Engineer
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