Snowflake Generative AI

Übersicht

Are you looking to build a career in AI? Or get hands-on experience with Snowflake for your next project?

Whether you’re a student, early career professional, or an experienced data professional, this program will enable you to acquire the practical skills you’ll need to be competitive in the job market to land your next job, or to grow your existing career as a data professional. Created and delivered by Snowflake’s own developer advocates, this program emphasizes hands-on learning with a lots of in-product exercises to give you the confidence you’ll need to tackle real-life, on-the job, projects.

You will learn:

How to build applications to implement common AI tasks such as summarization, translation, sentiment analysis, and text classification How to perform prompt engineering and inference programmatically with foundation model families including Llama, Mistral, and Anthropic How to fine-tune a foundation model to distill the capability of a larger model into a smaller one, or to train a model to respond in desired style How to ask questions of your structured data using natural language, with Text-to-SQL How to build and evaluate RAG applications to get answers from unstructured data

Lehrplan

• Introduction to Snowflake Generative AI
Overview of Snowflake and its AI capabilities
Course objectives and outcomes
• Fundamentals of AI in Snowflake
Introduction to AI tasks: summarization, translation, sentiment analysis, and text classification
Case studies and real-world applications
• Hands-on with Snowflake
Navigating the Snowflake environment
Setting up your development workspace
• Building AI Applications
Implementing common AI tasks in Snowflake
Developing applications for summarization and translation
Creating sentiment analysis and text classification tools
• Prompt Engineering and Inference
Introduction to foundation model families: Llama, Mistral, and Anthropic
Techniques for prompt engineering
Programmatic inference with foundation models
• Fine-Tuning Foundation Models
Distillation of large models into smaller, efficient ones
Training models for specific response styles
• Natural Language Processing with Text-to-SQL
Concepts of Text-to-SQL
Implementing queries with natural language
• Building and Evaluating Retrieval-Augmented Generation (RAG) Applications
Understanding RAG applications
Techniques for extracting information from unstructured data
Evaluation metrics for RAG applications
• Capstone Project
Designing and implementing a project using Snowflake Generative AI
Presenting project outcomes and solutions
• Career Development in AI
Tips for leveraging Snowflake skills in the job market
Networking and professional growth strategies
• Conclusion and Future Trends
Recap of key learnings
Discussion on emerging trends in AI and Snowflake technology

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Unterrichtet von

Snowflake Northstar

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Fachgebiete

Business