With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).
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With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).
With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).
This micro course gives aspiring data scientists, ML engineers, gen-AI engineers, software developers, and other data-oriented roles the in-demand skills for performing vector searches in relational databases.
Businesses use vector search with relational databases to improve information retrieval via advanced similarity matching. You’ll gain hands-on experience working with PostgreSQL as your relational database platform and Python and JavaScript to vectorize data, create embeddings and collections, and load data, including bulk insertion techniques. Plus, you’ll provide similarity search recommendations using techniques such as cosine similarity.
This micro course is part of the IBM Vector Database Fundamentals specialization, designed for professionals building on their NoSQL and relational database experience to work with vector databases.
So, enroll today and get set to power your career with highly sought-after relational vector database skills.
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Activities
SQL querying fundamentals recap
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Refreshes basic querying skills, which are foundational to this course
Browse courses on
SQL
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Review the syntax of basic SQL queries
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Write sample queries to retrieve data
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Practice using aggregate functions
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Try using subqueries
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Explore using joins
Create a comprehensive course notebook
Show steps
Organize and synthesize course materials to enhance retention.
Show steps
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Gather lecture notes, slides, assignments, and other course materials
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Organize materials into logical sections and subsections
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Annotate materials with your own notes and summaries
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Create a table of contents and index for easy navigation
Create a comprehensive study guide
Show steps
Consolidate and summarize key concepts from the course for easy reference.
Show steps
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Gather all course materials (notes, slides, assignments).
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Identify and organize main topics and subtopics.
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Summarize key concepts and examples in a concise manner.
Three other activities
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Show all six activities
Work through vector similarity examples
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Improve your understanding of vector similarity measures by practicing with examples.
Browse courses on
Cosine Similarity
Show steps
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Review the different vector similarity measures
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Calculate the similarity between two vectors using each measure
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Interpret the results and identify the most appropriate measure for your application
Build a vector-powered recommendation system
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Apply vector search concepts to create a real-world recommendation engine.
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Recommendation Systems
Show steps
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Design the data model for storing vectorized product data.
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Implement vector search functionality using a relational database.
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Develop a user interface for browsing and searching products.
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Evaluate the performance and accuracy of the recommendation system.
Write a blog post or article on a vector database topic
Show steps
Deepen your understanding and showcase your knowledge by creating content on vector databases.
Show steps
-
Choose a specific topic related to vector databases that you are passionate about
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Conduct thorough research to gather insights and information
-
Organize your content into a logical structure with an introduction, body, and conclusion
-
Write clear and engaging prose that effectively conveys your knowledge
SQL querying fundamentals recap
Show steps
Refreshes basic querying skills, which are foundational to this course
Browse courses on
SQL
Show steps
- Review the syntax of basic SQL queries
- Write sample queries to retrieve data
- Practice using aggregate functions
- Try using subqueries
- Explore using joins
Create a comprehensive course notebook
Show steps
Organize and synthesize course materials to enhance retention.
Show steps
- Gather lecture notes, slides, assignments, and other course materials
- Organize materials into logical sections and subsections
- Annotate materials with your own notes and summaries
- Create a table of contents and index for easy navigation
Create a comprehensive study guide
Show steps
Consolidate and summarize key concepts from the course for easy reference.
Show steps
- Gather all course materials (notes, slides, assignments).
- Identify and organize main topics and subtopics.
- Summarize key concepts and examples in a concise manner.
Work through vector similarity examples
Show steps
Improve your understanding of vector similarity measures by practicing with examples.
Browse courses on
Cosine Similarity
Show steps
- Review the different vector similarity measures
- Calculate the similarity between two vectors using each measure
- Interpret the results and identify the most appropriate measure for your application
Build a vector-powered recommendation system
Show steps
Apply vector search concepts to create a real-world recommendation engine.
Browse courses on
Recommendation Systems
Show steps
- Design the data model for storing vectorized product data.
- Implement vector search functionality using a relational database.
- Develop a user interface for browsing and searching products.
- Evaluate the performance and accuracy of the recommendation system.
Write a blog post or article on a vector database topic
Show steps
Deepen your understanding and showcase your knowledge by creating content on vector databases.
Show steps
- Choose a specific topic related to vector databases that you are passionate about
- Conduct thorough research to gather insights and information
- Organize your content into a logical structure with an introduction, body, and conclusion
- Write clear and engaging prose that effectively conveys your knowledge
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