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Work with Gemini Models in BigQuery

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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What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
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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Reviews summary

Gemini models in bigquery: a practical dive

According to learners, this course offers a highly relevant and practical introduction to using Gemini models within BigQuery. It provides step-by-step guidance through hands-on coding solutions, leveraging both SQL queries and Python notebooks for generative AI tasks. Students appreciate the course's focus on a real-world customer relationship management use case, making the learning directly applicable. While it serves as an excellent foundational course for those familiar with SQL and Python, some suggest that learners seeking more in-depth advanced topics might need supplementary resources. Overall, it's considered a high-quality offering from Google Cloud, ideal for professionals looking to integrate cutting-edge AI into their BigQuery workflows.
High-quality content expected from Google Cloud.
"As expected from Google Cloud, the material is top-notch and very well-produced."
"The explanations are clear and precise, typical of Google's training materials."
"I trust the quality of courses published by Google Cloud for their accuracy and relevance."
Provides a well-structured problem-solving workflow.
"The step-by-step guidance really clarified the entire workflow for me."
"I liked how the course breaks down complex AI/ML tasks into manageable steps."
"It helped me understand the whole process from business problem to AI solution using Gemini."
Offers hands-on coding and real-world scenarios.
"The hands-on BigQuery labs and Python notebooks were excellent for practice."
"I valued the practical use case approach to solving real business problems."
"Being able to directly apply SQL queries and Python in BigQuery is a massive plus for me."
Explores highly relevant generative AI models.
"It's great to learn about Gemini models right now, very timely for my career."
"This course covers a crucial and future-proof skill set in AI/ML that I need."
"I appreciate how current the content is, directly applicable to modern AI trends."
Provides a strong introduction, not an exhaustive deep dive.
"It's a great overview to get started with Gemini, but I'll need more advanced resources later."
"I wish some topics were explored in greater detail, especially for experienced AI/ML users."
"Good for getting acquainted with the basics, but don't expect to become an expert overnight."
Best for those with prior SQL and Python skills.
"I found it beneficial because I already had a strong SQL background going in."
"This course was a bit challenging since I wasn't already familiar with Python or BigQuery basics."
"It's clearly for data professionals, not absolute beginners in programming or cloud."

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.
Browse courses on Statistics
Show steps
  • 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.
Browse courses on BigQuery
Show steps
  • 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.
Show steps
  • Design the data model
  • Load data into BigQuery
  • Transform and aggregate data
  • Visualize data using dashboards
Four other activities
Expand to see all activities and additional details
Show all seven activities
SQL and Python Coding Exercises
Solve coding exercises in both SQL and Python to solidify your understanding of Gemini models.
Browse courses on SQL
Show steps
  • 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.
Browse courses on Customer Relationship Management
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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Course image
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Traffic lights
Read about what's good
what should give you pause
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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