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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will use text embeddings and Vertex AI vector search to find similar documents based on their text content.
Register for this course and see more details by visiting:
OpenCourser.com/course/dpvcpj/getting
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What's inside
Syllabus
Getting Started with Vector Search and Embeddings
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches vector search and embeddings, which are in-demand skills in AI and data science
Provides hands-on labs in the Google Cloud console, offering practical experience
Taught by Google Cloud Training, indicating industry expertise and credibility
Self-paced format allows learners to progress at their own speed and schedule
Designed for learners with some experience in text processing and AI concepts
Save this course
Save Getting Started with Vector Search and Embeddings to your list so you can find it easily later:
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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 Getting Started with Vector Search and Embeddings with these
activities:
Review Course Materials
Show steps
Reviewing materials from the course and related resources can help strengthen your grasp of the concepts.
Browse courses on
Vector Search
Show steps
-
Review the course syllabus.
-
Read the assigned textbooks and articles.
-
Watch the video lectures.
-
Complete the practice exercises.
YouTube Tutorials
Show steps
YouTube tutorials can provide extra visual aids beyond the course's materials.
Browse courses on
Vector Search
Show steps
-
Watch this tutorial: https://www.youtube.com/watch?v=-28FgEgL9WA
-
Try the tutorial out yourself using a free tier Google Cloud account.
Vector Search Practicals
Show steps
These practical exercises will give you hands-on experience with the material you'll learn in the course.
Browse courses on
Vector Search
Show steps
-
Complete the 'Getting Started' tutorial.
-
Complete the 'Vector Search with Embeddings' tutorial.
-
Complete the 'Building a Vector Index' tutorial.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study Group
Show steps
Find others taking the course and meet up to discuss the material and work on problems together.
Browse courses on
Vector Search
Show steps
-
Find a few other students in the course.
-
Choose a time and place to meet.
-
Discuss the course material.
-
Work on problems together.
Attend a Meetup
Show steps
Meetup events can be a great way to connect with others in the field and learn about the latest trends.
Browse courses on
Vector Search
Show steps
-
Find a Meetup group that focuses on Vector Search or a related topic.
-
Attend a Meetup event.
-
Introduce yourself to others and ask questions.
-
Share your own knowledge and experience.
Build a Vector Search App
Show steps
Challenge yourself by starting to create your own Vector Search application.
Browse courses on
Vector Search
Show steps
-
Come up with a problem that you can solve using Vector Search.
-
Research how to implement Vector Search in Python.
-
Start coding! Use Google Cloud's free tier to keep your costs down.
-
Deploy your app to the cloud and test it out.
Write a Blog Post
Show steps
Write a blog post summarizing what you learned in the course.
Browse courses on
Vector Search
Show steps
-
Come up with a catchy title and outline.
-
Write the first draft.
-
Edit and revise.
-
Share your post with the world!
Review Course Materials
Show steps
Reviewing materials from the course and related resources can help strengthen your grasp of the concepts.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Review the course syllabus.
- Read the assigned textbooks and articles.
- Watch the video lectures.
- Complete the practice exercises.
YouTube Tutorials
Show steps
YouTube tutorials can provide extra visual aids beyond the course's materials.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Watch this tutorial: https://www.youtube.com/watch?v=-28FgEgL9WA
- Try the tutorial out yourself using a free tier Google Cloud account.
Vector Search Practicals
Show steps
These practical exercises will give you hands-on experience with the material you'll learn in the course.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Complete the 'Getting Started' tutorial.
- Complete the 'Vector Search with Embeddings' tutorial.
- Complete the 'Building a Vector Index' tutorial.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study Group
Show steps
Find others taking the course and meet up to discuss the material and work on problems together.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Find a few other students in the course.
- Choose a time and place to meet.
- Discuss the course material.
- Work on problems together.
Attend a Meetup
Show steps
Meetup events can be a great way to connect with others in the field and learn about the latest trends.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Find a Meetup group that focuses on Vector Search or a related topic.
- Attend a Meetup event.
- Introduce yourself to others and ask questions.
- Share your own knowledge and experience.
Build a Vector Search App
Show steps
Challenge yourself by starting to create your own Vector Search application.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Come up with a problem that you can solve using Vector Search.
- Research how to implement Vector Search in Python.
- Start coding! Use Google Cloud's free tier to keep your costs down.
- Deploy your app to the cloud and test it out.
Write a Blog Post
Show steps
Write a blog post summarizing what you learned in the course.
Browse courses on
Vector Search
Show steps
Show steps
Show steps
- Come up with a catchy title and outline.
- Write the first draft.
- Edit and revise.
- Share your post with the world!
Career center
Learners who complete Getting Started with 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 build and maintain machine learning systems. They must be familiar with a variety of machine learning algorithms and techniques, including vector search and embeddings. The course Getting Started with Vector Search and Embeddings can help those entering the field understand the practical applications of these technologies in real-world systems.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They may use vector search and embeddings to develop trading strategies and risk models. The course Getting Started with Vector Search and Embeddings can help Quantitative Analysts build a strong foundation in these technologies and gain a competitive edge in the field.
Data Scientist
Data Scientist
Data Scientists develop complex modeling solutions to solve business problems. They use their expertise in machine learning, mathematics, and statistics to build predictive models, which rely heavily on vector search and embeddings. Taking the course Getting Started with Vector Search and Embeddings can help one entering the field build a strong foundation in these technologies.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They may specialize in a particular area of software development, such as machine learning or data science. The course Getting Started with Vector Search and Embeddings can help Software Engineers develop the skills they need to work with these technologies in their applications.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They may use vector search and embeddings to develop optimization models and supply chain management systems. The course Getting Started with Vector Search and Embeddings can help Operations Research Analysts develop the skills they need to use these technologies in their work.
Data Architect
Data Architect
Data Architects design and develop data management systems. They must have a deep understanding of data modeling and data storage technologies. The course Getting Started with Vector Search and Embeddings can help Data Architects develop the skills they need to use these technologies in their work.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They must have a deep understanding of the market and the customer needs. The course Getting Started with Vector Search and Embeddings can help Product Managers develop the skills they need to understand how customers interact with their products and identify opportunities for improvement.
Cybersecurity Analyst
Cybersecurity Analyst
Cybersecurity Analysts protect computer systems and networks from unauthorized access and attack. They may use vector search and embeddings to develop intrusion detection systems and malware analysis tools. The course Getting Started with Vector Search and Embeddings can help Cybersecurity Analysts develop the skills they need to use these technologies in their work.
Compliance Analyst
Compliance Analyst
Compliance Analysts ensure that organizations comply with laws and regulations. They may use vector search and embeddings to develop compliance monitoring systems. The course Getting Started with Vector Search and Embeddings can help Compliance Analysts develop the skills they need to use these technologies in their work.
Fraud Analyst
Fraud Analyst
Fraud Analysts investigate and prevent fraud. They may use vector search and embeddings to develop fraud detection models. The course Getting Started with Vector Search and Embeddings can help Fraud Analysts develop the skills they need to use these technologies in their work.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems. They may use vector search and embeddings to develop data-driven solutions. The course Getting Started with Vector Search and Embeddings can help Business Analysts develop the skills they need to use these technologies in their work.
Data Analyst
Data Analyst
Data Analysts use their programming skills to solve business problems with data. They may focus on statistical modeling, data visualization, or machine learning, which are all skills that are developed through the course Getting Started with Vector Search and Embeddings. A good foundation in data analysis can help someone embarking on a career as a Data Analyst understand the theoretical basis of their work.
Database Administrator
Database Administrator
Database Administrators are responsible for the maintenance and performance of databases. They must have a deep understanding of database technologies. The course Getting Started with Vector Search and Embeddings can help Database Administrators develop the skills they need to use these technologies in their work.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access and attack. They may use vector search and embeddings to develop intrusion detection systems and malware analysis tools. The course Getting Started with Vector Search and Embeddings can help Information Security Analysts develop the skills they need to use these technologies in their work.
Risk Analyst
Risk Analyst
Risk Analysts assess and manage risks. They may use vector search and embeddings to develop risk models. The course Getting Started with Vector Search and Embeddings can help Risk Analysts develop the skills they need to use these technologies in their work.
For more career information including salaries, visit:
OpenCourser.com/course/dpvcpj/getting
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
Getting Started with Vector Search and Embeddings.
Provides a comprehensive introduction to deep learning for natural language processing, covering the basics of deep learning, NLP, and more. It valuable resource for anyone looking to learn more about deep learning for NLP and its applications.
Provides a comprehensive introduction to natural language processing, covering the basics of text processing, machine learning for NLP, and more. It valuable resource for anyone looking to learn more about NLP and its applications.
Provides a thorough introduction to deep learning and its applications. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. The book also includes a chapter on using deep learning for natural language processing.
Provides a comprehensive overview of natural language processing (NLP) and its applications. It covers a wide range of topics, including text classification, text clustering, and sentiment analysis. The book also includes a chapter on using the Natural Language Toolkit (NLTK) for NLP tasks.
Provides a comprehensive introduction to machine learning for text, covering the basics of NLP, machine learning for NLP, and more. It valuable resource for anyone looking to learn more about machine learning for text and its applications.
Provides a practical introduction to machine learning using the R programming language. It covers a wide range of topics, including data preprocessing, model fitting, and model evaluation. The book also includes a chapter on using machine learning for natural language processing.
Provides a comprehensive overview of information retrieval (IR) and its applications. It covers a wide range of topics, including text indexing, text ranking, and information filtering. The book also includes a chapter on using IR for natural language processing.
Provides a comprehensive introduction to the mathematics behind machine learning, covering the basics of linear algebra, calculus, and more. It valuable resource for anyone looking to learn more about the mathematical foundations of machine learning.
Provides a comprehensive introduction to pattern recognition and machine learning, covering the basics of supervised learning, unsupervised learning, and more. It valuable resource for anyone looking to learn more about pattern recognition and machine learning and their applications.
Provides a comprehensive introduction to the statistical foundations of natural language processing, covering the basics of probability, statistics, and more. It valuable resource for anyone looking to learn more about the statistical foundations of NLP and its applications.
Provides a comprehensive introduction to speech and language processing, covering the basics of speech recognition, natural language processing, and more. It valuable resource for anyone looking to learn more about speech and language processing and its applications.
Save
Provides a comprehensive introduction to computer vision, covering the basics of image processing, computer vision algorithms, and more. It valuable resource for anyone looking to learn more about computer vision and its applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/dpvcpj/getting
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Effort
90 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches vector search and embeddings, which are in-demand skills in AI and data science
Provides hands-on labs in the Google Cloud console, offering practical experience
Taught by Google Cloud Training, indicating industry expertise and credibility
Self-paced format allows learners to progress at their own speed and schedule
Designed for learners with some experience in text processing and AI concepts
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