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Course Outline
Introduction to High-Dimensional Data
- Understanding the concept of data dimensions
- The critical role of dimensionality in AI and machine learning
Foundations of Vector Databases
- Defining vector databases
- Exploring key features and advantages
- Comparing vector databases with traditional database systems
Managing Vector Data
- Categorizing types of vector data
- Performing fundamental vector operations
- An overview of vector embeddings
Indexing and Retrieval Strategies
- Implementing basic indexing techniques
- Executing elementary similarity searches
- Exploring practical applications of similarity retrieval
Vector Databases in the AI Landscape
- Mechanisms by which vector databases support AI workloads
- Overview of simple AI applications leveraging vector databases
- Emerging trends and future directions in vector database technology
Practical Application
- Building a small-scale vector database
- Practicing data indexing and search retrieval
- Analyzing real-world implementation scenarios
Wrap-Up and Future Pathways
Requirements
- Basic knowledge of database principles
- No prior machine learning experience is necessary
Target Audience
- Software developers
- Database administrators
14 Hours
