Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 0 Minute(s)
Language
English
Taught by
Idan Gabrieli
Rating
4 views
Course Overview
Master the Basics of Feature Vector, Vector Embeddings, Vector Search, and Vector Databases for AI Applications
Vectors - Unlock the Secret to AI's Superpower
Ever wondered how AI can recommend the perfect movie, generate stunningly accurate answers, or understand your natural language queries? The magic lies in vectors, embeddings, and vector databases —the backbone of modern semantic search and Generative AI. This course demystifies these cutting-edge concepts, making them accessible to absolute beginners like you!
What You’ll Learn
Vectorizing Data: Learn how raw information is transformed into powerful, searchable numerical representations using vectors.
Semantic Search: Explore how AI finds the most relevant content based on meaning, not keywords.
Vector Databases: Dive into the technology that stores and retrieves vectorized data efficiently for AI applications.
Market Applications: Discover how vector databases power cutting-edge solutions in AI-driven fields like recommendation systems, image and video search, and semantic search.
By the end of this course, you’ll know how to apply these concepts to real-world scenarios like chatbots, recommendation engines, and generative AI models.
Why This Course?
Beginner-Friendly: No prior AI or database experience is needed.
Real-World Applications: Learn through examples that directly relate to today’s most exciting AI advancements.
Generative AI Focus: Tailored for those eager to harness AI’s potential in applications like GPT-powered tools and semantic search engines.
Don’t just use AI—understand the technology that makes it possible. Enroll now and take your first step into the fascinating world of vector embeddings and vector databases!
Course Content
- 5 section(s)
- 25 lecture(s)
- Section 1 Getting Started
- Section 2 The World of Vectors
- Section 3 Vector Databases
- Section 4 Market Use Cases with Vector DBs
- Section 5 Course Summary
What You’ll Learn
- Understand the Concept of Vectorizing Unstructured Data
- Explore Vector Spaces and Similarity Metrics
- Learn the Fundamentals of Vector Search
- Discover Vector Databases
- Use Case: Semantic Search
- Use Case: Recommendation Systems
- Use Case: LLMs and Retrieval-Augmented Generation (RAG)
- Use Case: Anomaly Detection
- Use Case: Image and Video Search
Reviews
-
YYves Le Breton
This was an EXCELLENT course! All the basics you need to understand how unstructured information can be turned into numbers/vectors that can be used to compare complex things and find answers that would not be possible with traditional search methods. I really liked the structure of the course materials, the quizzes and the teaching style of the instructor. Thank you Idan.
-
NNarayanan Muthuswamy
Happy
-
AAndrew Sandrini Vaz
Very good to understand better thr role of vector databases in AI and how they work. This oiurse was very eye-opening for me and I believe it's a must for anyone that wants to work in this area. The explanations are clear and easy to understand.
-
JJeffrey Park
clear and simple explanation! must have this course who doesn't know about vector databases
