LECTURE 1 Introduction to LLMs 
_ Introduction
_ LLMs Foundations
_ What is an LLM? (Overview, Transformer architecture, Encoder + Decoder Architecture, etc.)

LECTURE 2 Applications and Limitations of LLMs 
_ Continuation of LLM Foundations
_ Examples of LLMs, Tokenization and Embedding
_ Limitations of LLMs
– Knowledge Cutoff, Domain Specific Challenges, Solutions
_ Running LLM Locally

LECTURE 3 Advanced Techniques with LLMs 
_ Prompt Engineering
_ Exploration of techniques such as zero-shot learning, few-shot learning, etc.
_ Fine-Tuning Introduction
_ Introduction to Fine-Tuning, PEFT

LECTURE 4 Quantization and Sharding for LLMs 
_ Introduction to Quantization
_ What is Quantization?
_ Benefits of Quantization in LLMs
_ Practical Examples of Quantization in Finance
_ Introduction to Sharding
_ What is Sharding?
_ How Sharding Optimizes LLM Performance
_ Implementing Sharding in Financial LLM Applications

LECTURE 5 Fine-Tuning and RAG Introduction
_ Continuation of Fine-Tuning
_ RLHF, LoRa, QLoRa, Practical Examples
_ DPO,KTO
_ RAG (Retrieval-Augmented Generation)
_ RAG Explanation, Why to Use RAG?

LECTURE 6 Deep Dive into RAG and Evaluation 
_ Continuation of RAG
_ RAG Components, Last RAG Advancement Techniques, Practical Examples
_ Evaluation
_ Introduction to LLM Evaluation, Evaluation Metrics and Methods, Using Trulens

LECTURE 7 LLMs Agents, AI Safety and Finance Examples
_ LLM Agents
_ Introduction to LLM Agents in Finance
_ Use Cases and Implementation Strategies
_ Building and Deploying LLM Agents for Financial Services
_ AI Safety
_ Understanding AI Safety
_ Tools and Strategies for AI Safety
_ AI Safety in Finance
_ LLMs in Finance: Practical Examples
_ Financial Report Parsing, Sentiment Analysis

LECTURE 8 Practical Applications and Real World Project
_ Continuation of LLMs in Finance: Practical Examples
_ Extracting Insights: Trends and Analysis, Trading
_ Real World Project
_ Option 1: Parsing Financial Rep

LECTURE 9 Real World Project
_ Continuation of Real World Project
_ Completion of chosen project