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Duration 14 hours
Course Outline
Foundations of High-Dimensional Data
- Comprehending data dimensions
- Significance in AI and machine learning contexts
Core Concepts of Vector Databases
- Defining vector databases
- Primary features and advantages
- Comparing vector and traditional database models
Manipulating Vector Data
- Categorization of vector data types
- Basic computational operations on vectors
- Overview of vector embeddings
Indexing and Retrieval Strategies
- Foundational indexing approaches
- Executing elementary similarity searches
- Practical applications of similarity search
The Intersection of Vector Databases and AI
- Mechanisms by which vector databases support AI systems
- Basic AI implementations utilizing vector databases
- Emerging trends in vector database technology
Practical Exercises
- Construction of a small-scale vector database
- Indexing and querying vector data
- Analysis of real-world use cases
Conclusion and Path Forward
Requirements
- Basic familiarity with core database principles.
- No prior machine learning experience is necessary.
Target Audience
- Software developers
- Database administrators
