Proof Download

Here’s What You Get

 

Core Curriculum & Approach

Week-by-Week Overview (based on course descriptions) 

• Weeks 1–2 (Foundations & Evaluation):

  • Generate synthetic test data to benchmark retrieval precision and recall.

  • Implement fast, unit‑test style evaluations.

  • Segment query types and prioritize improvements by impact and volume.

• Weeks 3–4 (Retrieval & Routing):

  • Build specialized indices (e.g. documents, tables, images).

  • Combine lexical (BM25) and semantic (embeddings) search, with rerankers.

  • Use query routing to dispatch queries to the optimal retriever or tool.

• Week 5 (Embeddings & Fine-tuning):

  • Fine-tune embedding or reranker models with your domain data.

  • Establish feedback loops and data collection for future refinement.

• Week 6 (UX, Prompting & Productization):

  • Design feedback mechanisms—explicit and implicit—to capture user impressions.

  • Use streaming responses, cite sources, and apply prompt engineering techniques (e.g., chain-of-thought, few‑shot transitions).

  • Optimize presentation, UI/UX flows, and latency perceptions.

Six Proven Strategies Article

Jason’s popular article outlines six pillars of improvement:

1. Synthetic data flywheel

2. Query segmentation

3. Specialized indices

4. Query routing & tool orchestration

5. Metadata leverage

6. Continuous feedback loops and presentation refinement

Instructor & Track Record

• Jason Liu has several years of experience building scalable search and recommendation systems. He teaches and advises on RAG at companies like Anthropic, Adobe, and startups across multiple industries

• Testimonials from students (e.g., senior engineers at Adobe, Red Hat, Anthropic) emphasize the hands-on, operational value of his frameworks

Why This Course Stands Out

• Emphasizes practical, data-first workflows rather than theory.

• Focuses on leading indicators like precision/recall and experiment velocity to drive improvement

• Strong architecture guidance: e.g., using specialized embeddings, rerankers, query routing, and feedback design.

• Helps teams develop a continuous improvement flywheel for real-world deployment and user satisfaction.

 

Should You Enroll?

Great fit if you:

• Already have a deployed RAG system that needs improvement.

• Want a structured, step-by-step optimization framework.

• Need real-world advice on metrics, feedback collection, and UX integration.

Maybe not if you’re just experimenting—start first with the free crash course or his blog writings before committing to the full program.

Explore More Resources

• “How to Improve RAG Applications: 6 Proven Strategies” — foundational guide on improving RAG pipelines

• “The RAG Playbook” — visual flywheel and deep process overview

• Blog post “What is Retrieval Augmented Generation?” — explains benefits and principles of RAG systems

 

See More: David Ghiyam – Courses Bundle

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