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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 learn how to use LangChain to store documents as embeddings in a vector store. You will use the LangChain framework to split a set of documents into chunks, vectorize (embed) each chunk and then store the embeddings in a vector database.

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What's inside

Syllabus

Create Text Embeddings for a Vector Store using LangChain

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops a deep understanding of using LangChain and vector stores to create text embeddings in a vector store
Strong, industry-recognized instructors who hold vast experience in the topic of the course
Suitable for beginners seeking to build a foundation in using LangChain and vector stores to create text embeddings
Opportunity for hands-on practice in a Google Cloud environment, enhancing comprehension and retention
Taught by Google Cloud Training, a highly recognized provider who ensures the relevance and credibility of the course content
Provides practical lessons and interactive labs, fostering more effective learning through hands-on experience

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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 Create Text Embeddings for a Vector Store using LangChain with these activities:
Review your notes and assignments from previous courses related to vector vectorization and langchain
Refresh your knowledge of relevant concepts covered in previous courses to strengthen your foundation before starting this course.
Browse courses on LangChain
Show steps
  • Gather your notes and assignments from previous courses.
  • Review the materials and focus on key concepts related to vector vectorization and langchain.
Review vector vectorization and langchain in natural language processing
Revisit the basics of vector vectorization and langchain to strengthen your foundation before starting the course.
Browse courses on LangChain
Show steps
  • Review your notes on vector vectorization.
  • Revisit the documentation for langchain.
  • Complete a few practice exercises on vector vectorization and langchain.
Join a study group or participate in a discussion forum to connect with other learners
Enhance your learning experience by connecting with other learners, sharing knowledge, and discussing the course material.
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  • Find a study group or discussion forum related to the course.
  • Participate in discussions and ask questions.
  • Share your knowledge and insights with other learners.
Three other activities
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Follow a guided tutorial on using LangChain to store embeddings in a vector store
Supplement your learning with a guided tutorial that provides step-by-step instructions on the specific topic of the course.
Show steps
  • Find a reputable tutorial on using LangChain.
  • Follow the tutorial step by step.
  • Experiment with the code and try different options.
Complete a series of practice drills on using LangChain to store embeddings in a vector store
Reinforce your understanding by completing a series of practice drills that test your ability to apply the concepts of the course.
Show steps
  • Find a set of practice drills on using LangChain.
  • Complete the drills, checking your answers against the provided solutions.
  • Review the solutions to identify areas where you need improvement.
Build a prototype application that uses LangChain to store embeddings in a vector store
Apply your learning by creating a tangible deliverable that demonstrates your ability to use the concepts of the course in a practical setting.
Show steps
  • Design the architecture of your application.
  • Implement the application using LangChain.
  • Test the application to ensure that it works as intended.

Career center

Learners who complete Create Text Embeddings for a Vector Store using LangChain will develop knowledge and skills that may be useful to these careers:

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