Course Description:

This intermediate-level course focuses on the practical implementation of LLMs in business operations. Participants will learn how to fine-tune pre-trained models for specific business needs, integrate LLMs into existing systems, and evaluate their performance.

 

Recommended Skills:

• Basic understanding of LLMs and NLP concepts.
• Familiarity with programming (Python preferred) and basic data handling.
• Experience with basic machine learning or data science concepts.
• OR
• Taken Introduction to Large Language Models (LLMs) for Business
• Taken Python for Data

 

What Will Be Gained:

• Skills to fine-tune and adapt LLMs for specific business tasks.
• Knowledge of integrating LLMs into business applications.
• Ability to evaluate and optimize LLM performance.
• Hands-on experience with LLM platforms and tools.

 

Course Outline:

Day 1: Preparing for LLM Integration

• Recap of LLM Fundamentals
• Defining Business Objectives and Use Cases for LLMs
• Data Requirements and Preparation
• Introduction to APIs and Integration Methods

 

Day 2: Fine-Tuning LLMs

• Introduction to Transfer Learning and Fine-Tuning
• Fine-Tuning a Pre-trained LLM with Custom Data
• Best Practices for Fine-Tuning and Validation
• Evaluating Model Performance and Accuracy

 

Day 3: Integrating LLMs into Business Workflows

• APIs, Cloud Services, and On-Premises
• Integrating LLMs into Customer Support Systems
• Building a Simple LLM-Driven Application
• Monitoring and Maintaining LLMs in Production

 

Day 4: Advanced Applications and Optimization

• Sentiment Analysis, Predictive Text, Personalization
• Optimizing LLM Performance and Reducing Latency
• Ensuring Robustness and Handling Edge Cases
• Designing an LLM Solution for a Business Problem