In this module, we will build an understanding of basic concepts such as text representation, NLP tasks such as classification, QA and language modeling

This module's focus is the transformer architecture that not only disrupted the NLP space but also computer vision and more. We will cover multi-stage training steps like pre-training and fine-tuning through models like BERT and GPT2

In this module, we will cover the impact of scale on the training process along with advanced techniques like PEFT, LoRA and RLHF through hands-on examples

This module covers real-world aspects of LLMs in production. Right from developing better prompts to developing RAGs and looking at frameworks like DSPy.

In this module, we will cover the latest frontiers like tool calling through MCP, agentic capabilities and what lies ahead of us.

• Basics/hands-on experience of working with python
• Basic understanding of Deep Neural Networks (pytorch preferrably)
• Access to google-colab or similar python environment with GPU access