Systematically Improve Your RAG Applications¶

Elevate your Retrieval-Augmented Generation (RAG) systems with our comprehensive course launching in February 2024. Learn to build a powerful flywheel for continuous improvement in your AI applications, guided by industry experts.

Students from Notable Companies:¶

Amazon, Google, OpenAI, Stanford University, University of California, Berkeley, Adobe, Shopify, ClickUp, GitLab, Zapier, Novo Nordisk, DraftKings, ProtonMail, Miro, Bain & Company, Klaviyo

Not ready for a course? Check out my free RAG Playbook¶

Not ready to invest in a paid course yet? Start with my free RAG Playbook newsletter course. You'll get bite-sized lessons delivered straight to your inbox, covering the fundamentals of RAG systems and practical tips for improvement.

Free 6 Day RAG Crash Course

Once you're comfortable with the basics and ready to take your RAG skills to the next level, consider enrolling in our comprehensive course in February 2024.

What You'll Learn¶

Our six-week program is designed to take you from RAG basics to advanced implementation strategies. Perfect for those who deployed RAG systems and want to improve them and cover the last mile of RAG. Here's a breakdown of what you can expect:

Weeks 1-2: Foundations and Evaluation¶

• Synthetic Data Generation: Learn to create high-quality synthetic data for rapid testing and development. Understand the importance of diversity in your test sets and how to avoid common pitfalls.
• Fast Evaluation Techniques: Implement quick, iterative improvements using unit test-like evaluations. Focus on basic retrieval metrics like precision and recall to optimize your system efficiently.
• Query Segmentation: Discover how to categorize and analyze user queries to identify patterns and gaps in your system's performance. Learn to prioritize improvements based on impact, volume, and success likelihood.
• Metrics That Matter: Understand the difference between leading and lagging metrics. Learn how to set actionable goals that drive real improvements in your RAG system.

Weeks 3-4: Advanced Retrieval and Routing¶

• Specialized Indices: Build targeted indices for different content types (documents, images, tables) to improve retrieval accuracy. Learn advanced techniques for handling multimodal data.
• Query Routing: Implement sophisticated query routing systems using parallel function calling. Understand how to select the right tools and APIs for different query types.
• Combining Search Methods: Master the art of blending lexical, semantic, and metadata-based search for optimal results. Learn when and how to use re-rankers effectively.
• Structured Data Extraction: Explore techniques for extracting and leveraging structured data from various sources to enhance your RAG capabilities.

Week 5: Fine-tuning and Embeddings¶

• Embedding Model Optimization: Learn when and how to fine-tune embedding models for your specific use case. Understand the impact of domain-specific data on model performance.
• Data Collection Strategies: Implement effective feedback mechanisms and logging systems to gather valuable data for future improvements.
• Re-ranker Implementation: Discover how to fine-tune and implement re-rankers for better search results. Learn about the latest advancements in ranking technologies.
• Representation Learning: Dive deep into the nuances of creating effective representations for various entities in your system, from user queries to document summaries.

Week 6: Product Design and User Experience¶

• Feedback Collection: Design intuitive and effective feedback mechanisms to continuously improve your system. Learn how to incentivize user feedback without disrupting the experience.
• Streaming Implementations: Implement streaming for improved user experience and perceived performance. Understand the psychological impacts of responsiveness on user satisfaction.
• Advanced Prompting Techniques: Master the art of crafting effective prompts, including chain-of-thought reasoning and dynamic few-shot learning.
• UI/UX Best Practices: Explore cutting-edge UI/UX designs for RAG applications, including innovative ways to display citations, confidence levels, and alternative answers.

Why This Course?¶

In the rapidly evolving field of AI and machine learning, staying ahead means mastering the fundamentals while keeping pace with the latest advancements. Our course offers:

• Practical, Hands-on Learning: Every concept is accompanied by real-world examples and exercises. You'll be implementing and testing ideas from day one.
• Industry-Relevant Case Studies: Learn from actual scenarios encountered in production environments at leading tech companies.
• Expert Instruction: Benefit from 12 hours of dedicated time with instructors who have years of experience in building and optimizing RAG systems.
• Community of Professionals: Connect with a diverse group of peers from companies like Amazon, Adobe, and Zapier. Share insights, challenges, and solutions in a collaborative environment.
• Cutting-edge Content: Stay updated with the latest trends and technologies in RAG, including advanced embedding techniques, multi-modal retrieval, and emerging evaluation metrics.
• Personalized Feedback: Receive tailored advice on your specific RAG challenges through interactive Q&A sessions and project reviews.

Why Now?¶

The field of Retrieval-Augmented Generation is at a critical juncture:

• Equal Playing Field: RAG is a relatively new technology, meaning everyone is starting from a similar point. This is your chance to become an early expert.
• Rapid Evolution: The techniques and best practices in RAG are evolving quickly. Learning now puts you at the forefront of this wave.
• Competitive Advantage: Understanding RAG deeply can give you and your organization a significant edge in developing more effective, efficient, and reliable AI systems.
• Increasing Demand: As more companies realize the potential of RAG in enhancing their AI capabilities, the demand for skilled professionals is skyrocketing.
• Foundation for Future AI: The principles learned in RAG form a solid foundation for understanding and implementing future advancements in AI and machine learning.

By enrolling now, you're not just learning a current technology – you're positioning yourself as a leader in the next generation of AI applications.

Will It Stay Relevant?¶

In the fast-paced world of AI, it's natural to wonder about the long-term relevance of what you learn. Our course is designed with this in mind:

• Timeless Problem-Solving Skills: The core of our curriculum focuses on analytical and problem-solving skills that remain valuable regardless of technological changes.
• Adaptable Fundamentals: We teach the underlying principles of RAG systems, enabling you to quickly adapt to new tools and techniques as they emerge.
• Continuous Learning Framework: You'll learn how to set up systems for ongoing improvement and adaptation, ensuring your skills stay relevant.
• Future-Proofing Strategies: Understand how to evaluate and integrate new technologies rapidly, keeping your RAG systems at the cutting edge.
• Emphasis on First Principles: By focusing on the foundational concepts behind RAG, you'll be equipped to understand and leverage future advancements effectively.

Our goal is not just to teach you the RAG techniques of today, but to give you the tools and mindset to evolve with the field, ensuring your skills remain cutting-edge for years to come.

Enroll now on Maven (starts Feb 4)

What People Are Saying¶

Max (Software Engineer, Launch School)¶

⭐⭐⭐⭐⭐ "Practical lessons from every lecture... learning from a community on the vanguard of this emerging field."

Christopher (Senior Data/AI Architect, Procurement Sciences AI)¶

⭐⭐⭐⭐⭐ "Excellent job of stressing the fundamentals... useful metric tools to measure and improve RAG systems."

Vitor (Staff Software Engineer, Zapier)¶

⭐⭐⭐⭐⭐ "Jason and Dan help set you on the right path... emphasis on looking at your data and building a metrics-based flywheel."

Moose (Founder & CEO, Sociail, Inc.)¶

⭐⭐⭐⭐⭐ "A game-changer! ... They've got this knack for breaking down complex RAG concepts into a framework that just clicks."

Ashutosh (Senior Principal Scientist, Adobe)¶

⭐⭐⭐⭐⭐ "Practical and grounded in actual industry experience... like getting the inside scoop from folks who've been in the trenches."

Mani (Senior Principal Software Engineer, Red Hat)¶

⭐⭐⭐⭐⭐ "System-oriented approach... Highly relevant, directly applicable, and save time in building prototypes."

Our Guarantee¶

We're so confident in the value of this course that we offer a money-back guarantee. If you don't feel you're making significant progress in improving your RAG applications after 4 weeks, we'll refund your course fee, no questions asked.

Expert RAG Consulting Available¶

For those seeking more personalized guidance, I also offer custom AI solutions backed by my 8 years of experience at companies like Stitchfix, Meta, and NYU.

Specialties: - Developing self-improving AI systems - Building advanced multimodal search systems - Creating robust testing frameworks for search and recommendation systems - Strategic AI research planning and company evaluation

Service Tiers: 1. Ongoing Support: $9,500/month 2. Strategic Planning: Starting at $50,000 for 3 months 3. Comprehensive Solutions: Starting at $120,000 for 3 months

Learn More About Consulting