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Google Cloud Training

This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.

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Syllabus

Work with Gemini Models in BigQuery
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks, which makes it accessible to learners with different programming backgrounds
Uses a practical use case involving customer relationship management, which makes it relatable to learners in the business field
Designed for learners interested in exploring the intersection of AI/ML and BigQuery, particularly in the context of generative AI tasks
Taught by Google Cloud Training, which has a strong reputation in the field of cloud computing and AI/ML
Covers the workflow of solving a business problem with Gemini models, which is highly relevant to industry practices

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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 Work with Gemini Models in BigQuery with these activities:
Review Statistical Concepts
Review basic statistical concepts to strengthen the foundation for understanding the probabilistic aspects of generative AI models.
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  • Review probability distributions
  • Practice solving probability problems
  • Understand sampling and estimation
  • Review statistical tests
Explore BigQuery ML Features
Complete guided tutorials on BigQuery ML features to familiarize yourself with the platform's capabilities.
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  • Follow tutorials on BigQuery ML
  • Experiment with different models
  • Evaluate model performance
Analyze Sales Data Using BigQuery
Build a project that leverages BigQuery's capabilities to analyze and visualize sales data. This will reinforce your understanding of using BigQuery for data analysis and visualization.
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  • Design the data model
  • Load data into BigQuery
  • Transform and aggregate data
  • Visualize data using dashboards
Four other activities
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SQL and Python Coding Exercises
Solve coding exercises in both SQL and Python to solidify your understanding of Gemini models.
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  • Practice writing SQL queries
  • Practice writing Python code
  • Debug and optimize code
Study Group Discussions
Engage in discussions with your peers to clarify concepts and share insights on Gemini models and their applications.
Show steps
  • Attend study group sessions
  • Participate in discussions
  • Share knowledge and resources
Customer Relationship Management Proposal
Develop a proposal for a customer relationship management solution using Gemini models. This will demonstrate your ability to apply the course concepts to real-world scenarios.
Show steps
  • Present the proposal
  • Define the problem statement
  • Propose a solution using Gemini models
  • Estimate the cost and resources
Gemini Model Implementation Blog Post
Write a detailed blog post explaining the implementation of Gemini models for generative AI tasks. This will help you synthesize your understanding and share knowledge with others.
Show steps
  • Research and gather information
  • Write the blog post
  • Edit and refine the content
  • Publish the blog post

Career center

Learners who complete Work with Gemini Models in BigQuery will develop knowledge and skills that may be useful to these careers:

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