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Master Vector Database – ChromaDB

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Master Vector Database – ChromaDB, available at $54.99, has an average rating of 4.5, with 24 lectures, based on 13 reviews, and has 122 subscribers.

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You will learn about Learn integration Vector databases with LangChain, Open AI Master Embeddings Transformer Models for vector embedding, Generative AI, Open AI API Usage Understand the fundamentals of vector databases and their role in AI, generative AI, and LLM (Language Model Models) Implement code along exercises to build and optimize vector indexing systems for real-world applications This course is ideal for individuals who are Anyone who want to explore the world of AI and Vector Database or Anyone who want to step into Vector Database world with practical learning or Data engineers, database administrators and data professionals curious about the emerging field of vector databases or Software developers interested in integrating vector databases into their applications. It is particularly useful for Anyone who want to explore the world of AI and Vector Database or Anyone who want to step into Vector Database world with practical learning or Data engineers, database administrators and data professionals curious about the emerging field of vector databases or Software developers interested in integrating vector databases into their applications.

Enroll now: Master Vector Database – ChromaDB

Summary

Title: Master Vector Database – ChromaDB

Price: $54.99

Average Rating: 4.5

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

  • Learn integration Vector databases with LangChain, Open AI
  • Master Embeddings
  • Transformer Models for vector embedding, Generative AI, Open AI API Usage
  • Understand the fundamentals of vector databases and their role in AI, generative AI, and LLM (Language Model Models)
  • Implement code along exercises to build and optimize vector indexing systems for real-world applications

Who Should Attend

  • Anyone who want to explore the world of AI and Vector Database
  • Anyone who want to step into Vector Database world with practical learning
  • Data engineers, database administrators and data professionals curious about the emerging field of vector databases
  • Software developers interested in integrating vector databases into their applications.

Target Audiences

  • Anyone who want to explore the world of AI and Vector Database
  • Anyone who want to step into Vector Database world with practical learning
  • Data engineers, database administrators and data professionals curious about the emerging field of vector databases
  • Software developers interested in integrating vector databases into their applications.

Welcome to the Master Vector Database course – ChromaDB!

Are you ready to unlock the power of ChromaDB and take your data handling skills to the next level? Look no further! This course is designed to equip you with all the tools and techniques you need to become a master of vector databases.

In this course, you’ll dive into the fascinating world of ChromaDB, starting with an introduction that will lay the foundation for your journey. From there, you’ll learn various methods on how to efficiently manage collections and add document-associated embeddings.

But that’s just the beginning! Ever struggled with querying data effectively? Not anymore! We’ll teach you how to query data with precision using filters like ‘where’ and even delve into querying multiple documents using the powerful Langchain + ChromaDB combination.

And it doesn’t stop there! Get ready to explore advanced topics such as storing and querying stock companies data, semantic search using duckdb+parquet, and even mastering multimodal image embedding search techniques.

But wait, there’s more! Ever wanted to perform local vector database searches seamlessly? We’ll show you how it’s done using the dynamic trio of ChromaDB, Langchain, and OpenAI.

And that’s not all! Brace yourself for an exciting exploration into the world of RAG with ChromaDB and OpenAI/GPT Model integration, as well as leveraging ChromaDB with Gemini Pro embedding model.

So, if you’re ready to elevate your skills, expand your knowledge, and become a true expert in vector databases, then this course is tailor-made for you. Don’t miss out on this incredible opportunity to become a master of ChromaDB.

Enroll now and let’s embark on this exhilarating journey together!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Vector Database

Lecture 2: Vectors and Embeddings

Lecture 3: Explain Vector Database like I'm 5

Chapter 2: ChromaDB

Lecture 1: Introduction to ChromaDB

Lecture 2: Methods on collections

Lecture 3: Storing "The Matrix" collections

Lecture 4: Adding document associated embeddings

Lecture 5: Query data with 'where' filter

Chapter 3: Query multiple documents – ChromaDB + Langchain

Lecture 1: ChromaDB + Langchain – QA on multiple documents – Part 1

Lecture 2: ChromaDB + Langchain – QA on multiple documents – Part 2

Chapter 4: Store and Query Stock Companies Data

Lecture 1: setup database, and getting data from wikipedia

Lecture 2: query stock companies data with filters

Chapter 5: Semantic Search, Duckdb+parquet with ChromaDB

Lecture 1: Storing Knowledgebase information with Duckdb+parquet

Lecture 2: Running semantic searches with filters, use different embedding model

Chapter 6: Multimodal image embedding search

Lecture 1: setup environment, data, chromadb database

Lecture 2: Image search using embedding model

Lecture 3: Finding items within an image using model

Lecture 4: Using metadatas to enhance your queries

Chapter 7: Local Vector Database with ChromaDB + langChain + OpenAI

Lecture 1: Query FED Speech data with local vectorDB, OpenAI and Langchain

Chapter 8: Streamlit + ChromaDB + LangChain – Summarize any document

Lecture 1: ChromaDB + Langchain to summarize a PDF document – Part 1

Lecture 2: ChromaDB + Langchain to summarize a PDF document – Part 2

Chapter 9: RAG with ChromaDB and OpenAI/GPT model

Lecture 1: RAG on wikipedia articles using GPT 3.5 model

Chapter 10: ChromaDB with Gemini Pro embedding model

Lecture 1: Using Gemini Pro embedding model for chromaDB

Chapter 11: Congratulations and Thank You!

Lecture 1: Your feedback is very valuable!

Instructors

  • Adnan Waheed
    Adnan Waheed
    Founder KlickAnalytics and ex-Bloomberg employee

Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 0 votes
  • 3 stars: 2 votes
  • 4 stars: 4 votes
  • 5 stars: 7 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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