Cohort 1

One-day course: Learn how to build Semantic Cache from Scratch for Enterprise RAG with production-grade implementation on GCP and Redis

Hamza Farooq

Founder & CEO Traversaal.ai | Adjunct Professor UCLA & Stanford

Enterprise RAG with Semantic Cache & GCP

1. Knowledge Enhancement:&nbsp;&nbsp;- Participants will acquire a thorough understanding of the architecture and features that differentiate enterprise RAG from traditional RAG systems. &nbsp;&nbsp;- They will grasp the intricacies of memory storage in an enterprise context and its integration with semantic caching, enhancing their knowledge of system efficiency and scalability. 2. Practical Implementation Skills:&nbsp;&nbsp;- Participants will develop hands-on skills in building semantic caching from scratch, understanding the core concepts, and implementing them with real-world examples. &nbsp;&nbsp;- The practical sessions using Redis and GCP will equip students with the ability to set up and configure semantic caching, leveraging the benefits of fast performance and low latency. 3. Problem-Solving Proficiency:&nbsp;&nbsp;- Participants will be empowered to address complex challenges related to semantic caching by considering factors such as context, query policies, and distance metrics. &nbsp;&nbsp;- The course will provide insights into optimizing semantic caching systems, allowing students to develop problem-solving proficiency for various scenarios. 4. Integration of Cutting-Edge Technologies:&nbsp;&nbsp;- Participants will gain exposure to cutting-edge technologies, including Redis, Google Cloud Platform, and Vertex AI, understanding their roles in enhancing semantic caching capabilities. &nbsp;&nbsp;- The integration of Google's Vertex AI for coherent text responses will give students insights into the latest advancements in the field. Participants will get access to our home-brewed Online LLM for free Course Prerequisites: Proficiency in Python and a solid understanding of RAGs, as well as Encoder and Decoder models. If you feel the need for a more foundational course, consider checking out my other offering on LLMs: https://maven.com/boring-bot/ml-system-design Tools utilized in this course include VS Code, UNIX terminal, Jupyter Notebooks, and Conda package management, ensuring a hands-on and practical learning experience.

Gain a deep understanding of enterprise RAG architecture and semantic cache

You are well verse in LLMs and would like to take a deeper dive

You are ready to deploy your own SOTA AI Models and like to see how they work

You have learned all about RAGs and would like to move to production-grade application

Who is this course for

What you’ll get out of this course

A profound knowledge of advanced enterprise RAG architecture, memory storage integration, and the intricacies of semantic caching, empowering them to comprehend and navigate complex systems.

Comprehensive Understanding:

Practical expertise in building semantic caching from scratch using Redis and GCP, enabling participants to implement effective caching solutions in real-world scenarios.

Hands-On Implementation Skills:

Competence in addressing intricate challenges associated with semantic caching by considering context, query policies, and implementing optimization strategies.

Problem-Solving Proficiency:

Proficiency in integrating cutting-edge technologies such as Redis, Google Cloud Platform, and Vertex AI, allowing participants to leverage the latest advancements in the field for enhanced performance and coherent text responses.

Cutting-Edge Technology Integration:

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First Module

Second Module

Third Module

Course syllabus

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Meet your instructor

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Tuesdays & Thursdays

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May 7, 2022

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Weekly projects

Course schedule

This course builds on live workshops and hands-on projects

Active hands-on learning

You’ll be interacting with other learners through breakout rooms and project teams

Interactive and project-based

Join a community of like-minded people who want to learn and grow alongside you

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