Build Datasets & Train LLMs that Drive Real Business Value

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Module 1: Introduction

Course Goals & Structure The LinkedIn Model Example Applying These Skills Elsewhere

Module 2: Foundational Concepts of LLMs

Transformer Architecture Pre-Training vs Fine-Tuning vs Alignment Identifying a Domain Why Datasets Differentiate

Module 3: Data Collection Strategies & Multi-Tier Engagement

Scraping & TOS Compliance Understanding Gradients Finding our Engagement Gradient Translating to Other Domains

Module 4: The Psychology of Feature Development

Why Features Matter Brainstorming Minimal Features vs. Advanced features Minimal Features in LinkedIn Data Generalizing to Other Domains

Module 5: Data Labeling & Automated Feature Extraction

Labeling Scripts for Basic Features Structure Classification Tonality Classification Topic and Opinion Extraction Micro-Importance Validation

Module 6: Testing Feature Importance

Scenario-Based Prompt Tests Permutation Importance & Correlation Embedding & Clustering Analysis Carrying Over to Your domain

Module 7: Advanced Feature Engineering & Analysis

Advanced Feature Engineering Narrative Flow Classification Pacing Classification Sentiment Arc Classification Topic Transition Classification Balancing & Augmentation Advanced Features in Your Domain

Module 8: Prompt Generation & Final Dataset Construction

Designing Model Prompts Merge Features into Dataset

Module 9: SFT Fine-Tuning

Selecting a Base Model LoRA / QLoRA An Introduction to SFT Supervised Fine-Tuning our Model When to Tweak Hyperparameters When to go Large with Large Language Models

Module 10: GRPO-Based Refinement (Advanced RL Techniques)

Why SFT Isn't Enough RL Approaches (PPO, DPO, etc.)GRPO Concepts & Rationale Refining the SFT Model with GRPO Validation & Avoiding Overfitting

Module 11: Deployment & Inference

Model Serving Small Front-End for Testing Edge Cases & Monitoring

Module 12: Maintenance & Continuous Improvement

Continuous Improvement Versioning & Pivoting General Tips for Other Domains

Module 13: Project Showcase & Wrap-Up

Final Demo Transitioning to Any Domain Thank you!

Build Datasets & Train LLMs that Drive Real Business Value

Learn how to create domain‐specific datasets for large language models, so you can build a true AI moat your competitors can't copy.