Name: Systematically Improving RAG Applications - Bonus Content
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Systematically Improving RAG Applications - Bonus Content

Systematically Improving RAG Applications: Bonus Content - Enrich your learning experience with access to exceptional materials from prior cohorts, including workshops, guest lectures, and Q&A sessions. Dive into a wealth of practical cases, best practices, and in-depth technical analyses.

Cohort 1

Workshops

Engage in six practical workshops from the first cohort that complement the main program:

Workshop 1
Workshop 2
Workshop 3
Workshop 4
Workshop 5
Workshop 6

Guest Lectures

Listen to insightful lectures from experts at leading AI companies:

Building Dynamic AI Memory Systems - Personalization by Sam Whitmore
Text Chunking in RAG - Insights by Anton from ChromaDB
Custom RAG Evaluations - With Vespa.ai
Multimodal RAG, Hybrid Search & Re-ranking Tips - With LanceDB and Unstructured
Leveraging User Feedback - Experiences from Zapier Central
Guide to RAG Complexity - Featured by Cohere and Modal Labs
Boosting BM25 with Generative AI - Doug Turnbull

Office Hours

Engage with experts through a series of Q&A sessions addressing practical challenges such as:

Building scalable RAG systems
Query optimization and routing
Fine-tuning re-rankers
Exploring alternative search methods: ColBERT, SPLADE
Implementing DAGs and serverless architecture
Specialized sessions for the APAC region

Cohort 2

Guest Lectures

New insights from the second cohort's guest expert sessions:

Evolving workflows for RAG optimization
Lexical Love - Shared by John Berriman
Common Mistakes with Evals - Clarified by Hamel Husain
Workflow Agents - A deep dive by Jerry Liu (LlamaIndex)
Query Routing - Perspective by Anton Troynikov (ChromaDB)
Fine-Tuning for Enterprise Search - Insights from the Glean team

About the Author: Jason Liu

Jason Liu is an experienced AI engineer with over six years of experience developing search and recommendation systems in both academic and commercial environments. His portfolio includes developing computer vision models at the University of Waterloo, shaping content policy at Facebook, and building recommendation engines at Stitch Fix, which brought the company an additional $50 million in revenue. Over the past year, he has consulted for dozens of startups, helping take their RAG solutions from prototypes to systems ready for industrial deployment. Jason is also the author of the open-source Instructor Python library, designed for building advanced RAG workflows.

Watch Online 28 lessons

0:00

#1: Cohort 1 Guest Lectures Building Dynamic AI Memory Systems Sam Whitmore's Approach to Personalization

All Course Lessons (28)

#	Lesson Title	Duration
1	Cohort 1 Guest Lectures Building Dynamic AI Memory Systems Sam Whitmore's Approach to Personalization Demo	55:45
2	Cohort 1 Guest Lectures Text Chunking in RAG Essential Guide with Anton from ChromaDB	01:01:30
3	Cohort 1 Guest Lectures Custom RAG Evaluations w Vespa.ai	53:38
4	Cohort 1 Guest Lectures Multimodal RAG, Hybrid Search & Re-ranking Tips with LanceDB and Unstructured	59:05
5	Cohort 1 Guest Lectures Leveraging User Feedback for Better RAG Systems Lessons from Zapier Central	55:17
6	Cohort 1 Guest Lectures Cohere's Guide to RAG Complexity and Tips from Modal Labs	01:08:24
7	Cohort 1 Guest Lectures Boosting BM25 with Generative AI Insights from Doug Turnbull	58:12
8	Cohort 1 Office Hours Beyond Dense Embeddings Exploring Colbert, SPLADE, & Advanced Retrieval Techniques Office Hours	25:32
9	Cohort 1 Office Hours Building Resilient RAG Systems for Large-Scale Data Office Hours	01:00:09
10	Cohort 1 Office Hours Building Scalable Systems with DAGs and Serverless for RAG APAC Office Hours	59:01
11	Cohort 1 Office Hours Data Flywheels & Fine-Tuning Re-Rankers for Retrieval Systems Office Hours	29:17
12	Cohort 1 Office Hours Evaluating Agent Performance and Planning Reliability in AI Systems APAC Office Hours	47:42
13	Cohort 1 Office Hours Handling Real-Time Insights & Advanced Retrieval Challenges APAC Office Hours	51:37
14	Cohort 1 Office Hours Optimizing Planner and Feedback Mechanisms in RAG Systems APAC Office Hours	44:25
15	Cohort 1 Office Hours Smart Routing and Query Optimization for Advanced Retrieval Systems Office Hours	42:23
16	Cohort 1 Office Hours Using AI to Streamline Query Understanding & User Feedback Office Hours	44:33
17	Cohort 2 Guest Lectures Building document workflow agents with Jerry Liu from Llama Index	44:28
18	Cohort 2 Guest Lectures Building scalable RAG applications Evolving workflows for sharing and optimization [Ankur Goyal]	45:20
19	Cohort 2 Guest Lectures Common Mistakes People Make with Evals [Hamel Husain]	40:34
20	Cohort 2 Guest Lectures Inside Glean Fine-Tuning Embedding Models for Optimized AI and Enterprise Search	47:25
21	Cohort 2 Guest Lectures Lexical Love Rediscovering the Power of Text in RAG [John Berryman]	46:28
22	Cohort 2 Guest Lectures Organizing Your Data for Query Routing [Anton Troynikov from ChromaDB]	44:55
23	RAG Cohort 1 - Workshop 1	01:00:00
24	RAG Cohort 1 - Workshop 2	01:38:02
25	RAG Cohort 1 - Workshop 3	01:05:01
26	RAG Cohort 1 - Workshop 4	58:20
27	RAG Cohort 1 - Workshop 5	57:37
28	RAG Cohort 1 - Workshop 6	01:05:44

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