Snowflake Cortex for LLMs, RAG, and Search

Snowflake 2024    |    Expert
  • 12 videos | 1h 36m 14s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 2 users Rating 5.0 of 2 users (2)
Snowflake Cortex is a suite of AI-related features that facilitate working with large language models (LLMs). These include Snowflake Copilot, AI-powered Universal Search, and Cortex Search for Retrieval Augmented Generation (RAG). In this course, learn how to use Snowflake Cortex to work with LLMs, adjust hyperparameters to control LLM output, and use the COMPLETE Cortex LLM function. Next, discover how to use Cortex LLM functions directly from SQL and Python and utilize advanced features like Snowflake Copilot, Universal Search, and Document AI for user experience enhancement through AI-driven search and document processing. Finally, explore how to customize LLMs through Cortex Fine-Tuning and implement Retrieval Augmented Generation using Cortex Search. Upon course completion, you will be able to work with LLMs in Snowflake Cortex.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline the features and functionality of snowflake cortex llms
    Recognize how to use temperature and top-p hyperparameters to determine the predictability of llm output
    Identify how to use the cortex llm complete, extract_answer, summarize, sentiment, and translate functions
    Use the complete cortex llm function with different types of roles
    Utilize the temperature, max_p, and guardrails properties to control the attributes of responses from the complete cortex llm function
  • Invoke the extract_answer, summarize, sentiment, and translate functions from sql
    Invoke the complete, extract_answer, summarize, sentiment, and translate functions from python
    Recognize the functionality of snowflake copilot, universal search, and document ai
    Identify the uses and steps involved in using cortex fine-tuning with prompt completion pairs in snowflake
    Outline retrieval augmented generation (rag) and the use of cortex search for rag
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 45s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 8m 40s
    After completing this video, you will be able to outline the features and functionality of Snowflake Cortex LLMs. FREE ACCESS
  • Locked
    3.  Control Model Creativity and Predictability
    10m 59s
    Upon completion of this video, you will be able to recognize how to use temperature and top-p hyperparameters to determine the predictability of LLM output. FREE ACCESS
  • Locked
    4.  Use Cortex LLM Functions from SQL
    11m 6s
    Through this video, you will be able to identify how to use the Cortex LLM COMPLETE, EXTRACT_ANSWER, SUMMARIZE, SENTIMENT, and TRANSLATE functions. FREE ACCESS
  • Locked
    5.  Invoking the Cortex LLM COMPLETE Function
    12m 5s
    Learn how to use the COMPLETE Cortex LLM function with different types of roles. FREE ACCESS
  • Locked
    6.  Controlling the Creativity and Predictability of LLM Responses
    10m 34s
    During this video, discover how to utilize the temperature, max_p, and guardrails properties to control the attributes of responses from the COMPLETE Cortex LLM function. FREE ACCESS
  • Locked
    7.  Using Cortex Functions from SQL
    9m 54s
    Find out how to invoke the EXTRACT_ANSWER, SUMMARIZE, SENTIMENT, and TRANSLATE functions from SQL. FREE ACCESS
  • Locked
    8.  Using Cortex Functions from Python
    11m 25s
    In this video, you will learn how to invoke the COMPLETE, EXTRACT_ANSWER, SUMMARIZE, SENTIMENT, and TRANSLATE functions from Python. FREE ACCESS
  • Locked
    9.  Snowflake Copilot, Universal Search, and Document AI
    7m 20s
    Through this video, you will be able to recognize the functionality of Snowflake Copilot, Universal Search, and Document AI. FREE ACCESS
  • Locked
    10.  Cortex Fine-Tuning
    2m 53s
    After completing this video, you will be able to identify the uses and steps involved in using Cortex Fine-Tuning with prompt completion pairs in Snowflake. FREE ACCESS
  • Locked
    11.  Retrieval Augmented Generation (RAG) and Cortex Search
    7m 33s
    Upon completion of this video, you will be able to outline Retrieval Augmented Generation (RAG) and the use of Cortex Search for RAG. FREE ACCESS
  • Locked
    12.  Course Summary
    2m
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Book Cloud Native AI and Machine Learning on AWS: Use SageMaker for building ML models, Automate MLOps, and Take Advantage of Numerous AWS AI Services
Course Snowflake Forecasting Models and the AI & ML Studio
Course Snowpark ML APIs and the Model Registry
Rating 5.0 of 2 users Rating 5.0 of 2 users (2)