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Google Cloud Training
This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.
Register for this course and see more details by visiting:
OpenCourser.com/course/uphpvd/vector
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What's inside
Syllabus
Vector Search and Embeddings
This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills and knowledge relevant to industry
Employs hands-on activities to make learning engaging
Instructors are from Google Cloud Training and oversee labs
Teaches advanced skills for those seeking expertise
Covers ideas that may benefit other subjects
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Vector Search and Embeddings with these
activities:
Brush up on your Python programming skills
Show steps
Ensure a solid foundation in Python programming, which is essential for working with vector search and text embeddings.
Browse courses on
Python
Show steps
-
Review the basics of Python syntax and data structures.
-
Practice writing Python code to manipulate text data and perform simple vector operations.
Review the basics of natural language processing
Show steps
Sharpen your understanding of NLP concepts and techniques before starting the course to enhance your comprehension.
Browse courses on
Natural Language Processing
Show steps
-
Revisit key NLP concepts, including tokenization, stemming, and lemmatization.
-
Review different NLP algorithms, such as TF-IDF and word embeddings.
Connect with experts in the field of vector search
Show steps
Expand your knowledge and gain valuable insights by connecting with experts who can provide guidance and support during and after the course.
Browse courses on
Vector Search
Show steps
-
Attend industry events or online forums related to vector search.
-
Reach out to professionals on LinkedIn or other networking platforms.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Attend Vector Search Meetup
Show steps
Connects students with Vector Search professionals and exposes them to industry trends, expanding their knowledge and professional network.
Browse courses on
Networking
Show steps
-
Find a Local Vector Search Meetup
-
Attend Vector Search Meetup
-
Participate in Vector Search Discussions
Organize and review course materials
Show steps
Stay organized and engaged by regularly reviewing and summarizing key course materials, helping you retain information and prepare for assessments.
Show steps
-
Create a system for organizing notes, assignments, and other course materials.
-
Set aside dedicated time to review and summarize the materials.
Complete a tutorial on vector search using Vertex AI
Show steps
Enhance your practical skills by following a guided tutorial that walks you through the process of building and deploying a vector search system with Vertex AI.
Browse courses on
Vector Search
Show steps
-
Find an online tutorial that covers building a vector search system with Vertex AI.
-
Follow the steps in the tutorial to create a dataset, train a model, and deploy the system.
Solve practice problems on vector search and text embeddings
Show steps
Deepen your understanding of vector search and text embeddings by solving challenging practice problems that test your knowledge and skills.
Browse courses on
Vector Search
Show steps
-
Find online practice problems or coding challenges related to vector search and text embeddings.
-
Attempt to solve the problems independently, referring to course materials or external resources as needed.
-
Review your solutions and identify areas for improvement.
Attend a workshop on advanced vector search techniques
Show steps
Enhance your skills and knowledge by attending a workshop that delves into advanced techniques and applications of vector search in the industry.
Browse courses on
Vector Search
Show steps
-
Research and identify relevant workshops or conferences.
-
Register and attend the workshop, actively participating in discussions and taking notes.
-
Follow up with the organizers or speakers to connect with experts and explore further learning opportunities.
Build a simple vector search application using the concepts learned in the course
Show steps
Solidify your understanding by applying the course concepts to build a real-world vector search application that demonstrates your skills.
Browse courses on
Vector Search
Show steps
-
Identify a specific problem or use case for your vector search application.
-
Design and implement the application using the techniques and technologies covered in the course.
-
Evaluate the performance of your application and make improvements as needed.
Contribute to open-source projects related to vector search
Show steps
Go beyond the classroom and make a meaningful impact by contributing to open-source projects that advance the field of vector search.
Browse courses on
Vector Search
Show steps
-
Identify open-source projects that align with your interests and skills.
-
Join the project's community, get involved in discussions, and identify areas where you can contribute.
-
Submit code contributions, bug reports, or documentation improvements.
Brush up on your Python programming skills
Show steps
Ensure a solid foundation in Python programming, which is essential for working with vector search and text embeddings.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review the basics of Python syntax and data structures.
- Practice writing Python code to manipulate text data and perform simple vector operations.
Review the basics of natural language processing
Show steps
Sharpen your understanding of NLP concepts and techniques before starting the course to enhance your comprehension.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Revisit key NLP concepts, including tokenization, stemming, and lemmatization.
- Review different NLP algorithms, such as TF-IDF and word embeddings.
Connect with experts in the field of vector search
Show steps
Expand your knowledge and gain valuable insights by connecting with experts who can provide guidance and support during and after the course.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Attend industry events or online forums related to vector search.
- Reach out to professionals on LinkedIn or other networking platforms.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Attend Vector Search Meetup
Show steps
Connects students with Vector Search professionals and exposes them to industry trends, expanding their knowledge and professional network.
Browse courses on
Networking
Show steps
Show steps
Show steps
- Find a Local Vector Search Meetup
- Attend Vector Search Meetup
- Participate in Vector Search Discussions
Organize and review course materials
Show steps
Stay organized and engaged by regularly reviewing and summarizing key course materials, helping you retain information and prepare for assessments.
Show steps
Show steps
Show steps
- Create a system for organizing notes, assignments, and other course materials.
- Set aside dedicated time to review and summarize the materials.
Complete a tutorial on vector search using Vertex AI
Show steps
Enhance your practical skills by following a guided tutorial that walks you through the process of building and deploying a vector search system with Vertex AI.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Find an online tutorial that covers building a vector search system with Vertex AI.
- Follow the steps in the tutorial to create a dataset, train a model, and deploy the system.
Solve practice problems on vector search and text embeddings
Show steps
Deepen your understanding of vector search and text embeddings by solving challenging practice problems that test your knowledge and skills.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Find online practice problems or coding challenges related to vector search and text embeddings.
- Attempt to solve the problems independently, referring to course materials or external resources as needed.
- Review your solutions and identify areas for improvement.
Attend a workshop on advanced vector search techniques
Show steps
Enhance your skills and knowledge by attending a workshop that delves into advanced techniques and applications of vector search in the industry.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Research and identify relevant workshops or conferences.
- Register and attend the workshop, actively participating in discussions and taking notes.
- Follow up with the organizers or speakers to connect with experts and explore further learning opportunities.
Build a simple vector search application using the concepts learned in the course
Show steps
Solidify your understanding by applying the course concepts to build a real-world vector search application that demonstrates your skills.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Identify a specific problem or use case for your vector search application.
- Design and implement the application using the techniques and technologies covered in the course.
- Evaluate the performance of your application and make improvements as needed.
Contribute to open-source projects related to vector search
Show steps
Go beyond the classroom and make a meaningful impact by contributing to open-source projects that advance the field of vector search.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Identify open-source projects that align with your interests and skills.
- Join the project's community, get involved in discussions, and identify areas where you can contribute.
- Submit code contributions, bug reports, or documentation improvements.
Career center
Learners who complete Vector Search and Embeddings will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. They use their knowledge of computer science and mathematics to develop models that can learn from data and make predictions. The Vector Search and Embeddings course can help prepare you for a career as a Machine Learning Engineer by teaching you the basics of vector search and text embeddings. This knowledge can be used to build powerful models that can understand the meaning of text data and make predictions about future events.
Data Scientist
Data Scientist
Data Scientists collect, organize, and analyze large datasets in order to understand the world around us. They use their knowledge of statistics and computer science to develop models that can make predictions about future events. The Vector Search and Embeddings course can help prepare you for a career as a Data Scientist by teaching you the basics of vector search and text embeddings. This knowledge can be used to build powerful models that can understand the meaning of text data and make predictions about future events.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, building, and maintaining software systems. They use their knowledge of computer science to develop software that meets the needs of users. The Vector Search and Embeddings course can help prepare you for a career as a Software Engineer by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop software that can understand the meaning of text data and make predictions about future events.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. They use their knowledge of statistics and computer science to identify trends and patterns in data. The Vector Search and Embeddings course can help prepare you for a career as a Data Analyst by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop models that can understand the meaning of text data and make predictions about future events.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with their products and services. They use their knowledge of customer service and technology to resolve problems and build relationships with customers. The Vector Search and Embeddings course can help prepare you for a career as a Customer Success Manager by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop solutions that can understand the meaning of text data and make predictions about future events.
UX Designer
UX Designer
UX Designers are responsible for designing the user experience for websites and apps. They use their knowledge of human behavior and psychology to create interfaces that are easy to use and understand. The Vector Search and Embeddings course can help prepare you for a career as a UX Designer by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop interfaces that can understand the meaning of text data and make predictions about future events.
Recruiter
Recruiter
Recruiters are responsible for finding and hiring new employees. They use their knowledge of human resources and technology to screen candidates and identify the best matches for open positions. The Vector Search and Embeddings course can help prepare you for a career as a Recruiter by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop screening tools that can understand the meaning of text data and make predictions about future events.
Information Architect
Information Architect
Information Architects are responsible for designing and organizing information systems. They use their knowledge of information science and computer science to develop systems that are easy to use and understand. The Vector Search and Embeddings course can help prepare you for a career as an Information Architect by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop systems that can understand the meaning of text data and make predictions about future events.
Sales Engineer
Sales Engineer
Sales Engineers are responsible for selling products and services to businesses. They use their knowledge of technology and sales to create proposals and close deals. The Vector Search and Embeddings course can help prepare you for a career as a Sales Engineer by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop proposals that can understand the meaning of text data and make predictions about future events.
Content Strategist
Content Strategist
Content Strategists are responsible for developing and managing content for websites, apps, and other digital platforms. They use their knowledge of marketing and writing to create content that is engaging and informative. The Vector Search and Embeddings course can help prepare you for a career as a Content Strategist by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop content that can understand the meaning of text data and make predictions about future events.
Technical Support Specialist
Technical Support Specialist
Technical Support Specialists are responsible for providing technical support to customers. They use their knowledge of technology and problem-solving to resolve issues and answer questions. The Vector Search and Embeddings course can help prepare you for a career as a Technical Support Specialist by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop tools that can understand the meaning of text data and make predictions about future events.
Digital Marketer
Digital Marketer
Digital Marketers are responsible for promoting products and services online. They use their knowledge of marketing and technology to create campaigns that reach target audiences. The Vector Search and Embeddings course can help prepare you for a career as a Digital Marketer by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop campaigns that can understand the meaning of text data and make predictions about future events.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying ways to improve them. They use their knowledge of business and technology to develop solutions that meet the needs of the business. The Vector Search and Embeddings course can help prepare you for a career as a Business Analyst by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop solutions that can understand the meaning of text data and make predictions about future events.
Product Manager
Product Manager
Product Managers are responsible for developing and managing products. They use their knowledge of business and technology to develop products that meet the needs of users. The Vector Search and Embeddings course can help prepare you for a career as a Product Manager by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop products that can understand the meaning of text data and make predictions about future events.
Technical Writer
Technical Writer
Technical Writers are responsible for writing documentation for software and other technical products. They use their knowledge of writing and technology to create documentation that is clear and easy to understand. The Vector Search and Embeddings course can help prepare you for a career as a Technical Writer by teaching you the basics of vector search and text embeddings. This knowledge can be used to develop documentation that can understand the meaning of text data and make predictions about future events.
For more career information including salaries, visit:
OpenCourser.com/course/uphpvd/vector
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Vector Search and Embeddings.
Save
Classic textbook on deep learning. It covers a wide range of topics, from foundational concepts to advanced techniques.
Classic textbook on pattern recognition and machine learning. It covers a wide range of topics, from foundational concepts to advanced techniques.
Provides a practical guide to using PyTorch for natural language processing tasks. It covers a wide range of topics, from foundational concepts to advanced techniques.
Practical guide to using TensorFlow for deep learning. It covers a wide range of topics, from foundational concepts to advanced techniques.
This important book provides a comprehensive introduction to interpretable machine learning, covering techniques for understanding and explaining the predictions of complex models, including linear models and deep learning models.
This highly regarded book provides a comprehensive overview of deep learning with Python, covering fundamental concepts, architectures, and applications, offering a solid foundation for understanding and implementing deep learning models.
Provides an introduction to Bayesian reasoning and machine learning. It covers a wide range of topics, from foundational concepts to advanced techniques.
Provides a practical guide to using Scikit-Learn, Keras, and TensorFlow for machine learning tasks. It covers a wide range of topics, from foundational concepts to advanced techniques.
Provides an introduction to machine learning. It covers a wide range of topics, from foundational concepts to advanced techniques.
Provides a practical guide to data science. It covers a wide range of topics, from data cleaning to machine learning.
Practical guide to using Pandas for data analysis. It covers a wide range of topics, from data cleaning to data visualization.
Provides a practical guide to using R for machine learning tasks. It covers a wide range of topics, from foundational concepts to advanced techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/uphpvd/vector
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Transcripts
Español
Français
Português
Deutsch
中文
العربية
한국어
日本語
हिंदी
Bahasa Indonesia
Good to know
Develops skills and knowledge relevant to industry
Employs hands-on activities to make learning engaging
Instructors are from Google Cloud Training and oversee labs
Teaches advanced skills for those seeking expertise
Covers ideas that may benefit other subjects
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