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Weights & Biases Weights & Biases

Weights & Biases AI Academy

Welcome to the W&B AI Academy! This repository contains materials for learning AI, organized by topic. These materials are designed to complement our online courses but can also be useful on their own.

🤖 Large Language Models (LLMs)

Course Instructor Description
🆕 RAG++ Bharat Ramanathan
MLE @ W&B

Ayush Thakur
MLE @ W&B

Meor Amer
Developer Advocate @ Cohere

Charles Pierse
Head of Weaviate Labs
Practical RAG techniques for engineers: production-ready solutions to optimize performance, cut costs, and enhance accuracy.
🆕 Developer's guide to LLM prompting Anish Shah
MLE @ W&B

Teodora Danilovic
Prompt Engineer @ AutogenAI
Everything you need to get started with prompt engineering, from system prompts to model-specific strategies.
LLM Engineering: Structured Outputs Jason Liu
Independent Consultant
Improve LLM engineering skills, learn about structured JSON output handling, function calling, and complex validations.
Building LLM-Powered Apps Darek Kłeczek
MLE @ W&B

Bharat Ramanathan
MLE @ W&B

Thomas Capelle
MLE @ W&B

Shreya Rajpal
Creator of Guardrails AI

Anton Troynikov
Co-Founder of Chroma

Shahram Anver
Co-Creator of Rebuff
Learn to build LLM-powered applications using LLM APIs, Langchain, and W&B LLM tooling.
Training and Fine-tuning LLMs Darek Kłeczek
MLE @ W&B

Ayush Thakur
MLE @ W&B

Jonathan Frankle
Chief Scientist @ MosaicML

Weiwei Yang
Principal SDE Manager @ Microsoft Research

Mark Saroufim
PyTorch Engineer @ Meta
Explore LLM architecture, training techniques, and fine-tuning methods, including LoRA and RLHF.
Evaluate and Debug Generative AI Carey Phelps
Founding Product Manager @ W&B
Practice evaluating and debugging Generative AI work using the W&B AI Developer Platform.

🚀 MLOps

Course Instructor Description
Model CI/CD Noa Schwartz
Product Manager @ W&B

Darek Kłeczek
MLE @ W&B

Hamel Husain
Founder @ Parlance Labs
Overcome model chaos, automate workflows, ensure governance, and streamline the end-to-end model lifecycle.
Effective MLOps: Model Development Thomas Capelle
MLE @ W&B

Darek Kłeczek
MLE @ W&B

Hamel Husain
Founder @ Parlance Labs
Learn to accelerate and scale model development, improve productivity, and ensure reproducibility.
CI/CD for Machine Learning (GitOps) Hamel Husain
Founder @ Parlance Labs
Streamline ML workflows using GitHub Actions and integrate W&B experiment tracking.
Data Validation in Production ML Pipelines Shreya Shankar
PhD student @ UC Berkeley
Build robust production ML pipelines, detect data drift, and manage data quality.
ML for Business Decision Optimization Dan Becker
Optimize business decisions and translate ML predictions into actionable insights.

📊 W&B Tools

Course Instructor Description
W&B 101 Scott Condron
MLE @ W&B
Introduction to W&B with a focus on experiment tracking, visualization, and optimization.
W&B 201: Model Registry Ken Lee
MLE @ W&B
Advanced model management using W&B for logging, registering, and managing ML models.

🌍 International Courses

Course Language Description
효율적인 MLOps: 모델 개발 Korean Comprehensive program on bringing ML models to life, optimizing performance, and preparing for primetime.
効果的なMLOps: モデル開発 Japanese Learn to accelerate and scale model development, improve productivity, and ensure reproducibility.

🏫 Resources for Educators

🧮 Math for ML

For more information and to enroll in courses, visit the W&B AI Academy website.

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