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Duration 14 hours
Course Outline
Introduction to High-Dimensional Data
- Conceptual understanding of data dimensions
- Relevance in AI and machine learning contexts
Fundamentals of Vector Databases
- Defining vector databases
- Core features and advantages
- Comparing vector databases with traditional systems
Managing Vector Data
- Categorizing types of vector data
- Executing basic vector operations
- Overview of vector embeddings
Indexing and Search Mechanisms
- Elementary indexing approaches
- Executing fundamental similarity searches
- Practical applications of similarity search
Integration with AI
- How vector databases facilitate AI workflows
- Basic AI solutions leveraging vector databases
- Emerging trends in the field
Practical Workshops
- Building a compact vector database
- Indexing and querying vector data
- Reviewing real-world use cases
Conclusion and Road Ahead
Requirements
- A basic understanding of database principles is expected
- No prior background in machine learning is necessary
Target Audience
- Software developers
- Database administrators
