Learners' Galaxy

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!