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Gemini for Data Scientists and Analysts

In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.

Duet AI was renamed to Gemini, our next-generation model.

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What's inside

Syllabus

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Covers important industry standard tools for data analysis and machine learning

Includes hands-on labs for practical experience

Teaches up-to-date skills and knowledge related to AI and data analysis

Helps students understand how to use innovative AI tools to analyze data

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Reviews summary

Gemini for data analysis in bigquery

According to students, this course offers a highly practical introduction to Gemini for data professionals, emphasizing hands-on labs within BigQuery. Learners appreciate its focus on real-world applications like sales prediction and customer analysis, making it relevant for those looking to leverage generative AI in their data workflows. While it provides a clear understanding of Gemini's capabilities, some found that a foundational understanding of BigQuery or data analytics concepts is beneficial to fully keep pace. The course is seen as a focused guide for specific use cases rather than a comprehensive AI theory course.

Covers specific applications rather than broad theoretical concepts.

"The course is great for its specific use cases like sales prediction."

"Don't expect a deep dive into LLM architecture; it's very applied."

"It's excellent for understanding how Gemini helps with BigQuery tasks, but not a general AI course."

Benefits learners with some prior BigQuery or data analysis background.

"I found it moved quickly; prior BigQuery experience was helpful."

"Beginners might need to brush up on SQL/BigQuery basics first."

"While I found it valuable, a basic understanding of data analytics is beneficial."

Keeps learners updated on cutting-edge generative AI tools.

"It's great to see a course covering Gemini right now."

"This course is highly relevant for anyone in data science today."

"I appreciate learning about the latest AI features from Google Cloud."

Provides valuable practical experience with Google Cloud tools.

"The hands-on labs really solidified my understanding of Gemini."

"I enjoyed the labs in BigQuery; they were very relevant."

"The exercises helped me learn by doing, which is essential for this topic."

Directly apply Gemini to real-world data analysis tasks.

"I could immediately see how to use Gemini in my daily workflow."

"The labs were very helpful for practical understanding."

"This course showed me how to apply generative AI in a business context."

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 Gemini for Data Scientists and Analysts with these activities:

Compile Course Materials

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Prepare for class by gathering and organizing all relevant materials.

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Review syllabus and identify required materials.
Locate and obtain textbooks, workbooks, and other resources.
Set up a designated study space and file system for materials.

Attend Industry Webinars or Conferences

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Expand your knowledge and connect with professionals by attending industry events.

Browse courses on Networking

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Research upcoming webinars or conferences.
Register for the event and mark it on your calendar.
Actively participate in discussions and take notes.

Explore Gemini Tutorials

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Supplement your understanding by following guided tutorials and exercises on Gemini.

Browse courses on Gemini

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Access the Google Cloud Training tutorials.
Follow along with the step-by-step instructions.
Complete the hands-on exercises to practice Gemini.

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Attend a Hands-on Workshop on Gemini

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Deepen your understanding of Gemini by attending a hands-on workshop.

Browse courses on Gemini

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Identify and register for a relevant workshop.
Prepare for the workshop by completing any prerequisites.
Attend the workshop and actively participate in exercises.
Connect with other attendees and industry experts.

Practice Data Analysis with BigQuery

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Reinforce your skills by completing practice exercises in BigQuery.

Browse courses on BigQuery

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Set up a BigQuery sandbox environment.
Run SQL queries to analyze sample datasets.
Interpret the results and draw insights from the data.

Volunteer at a Data-Driven Organization

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Gain practical experience and contribute to the community by volunteering at a data-driven organization.

Browse courses on Data Analysis

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Identify organizations that align with your interests.
Contact the organization and inquire about volunteer opportunities.
Commit to a regular volunteer schedule.
Engage in data-related activities and support the organization's mission.

Develop a Customer Segmentation Model

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Apply your knowledge by creating a project to identify and categorize new customers.

Browse courses on Supervised Learning

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Define the project scope and objectives.
Gather and prepare customer data from BigQuery.
Develop and train a machine learning model using Gemini.
Evaluate the model's performance and accuracy.
Present your findings and recommendations.

Create a Data Analysis Presentation

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Enhance your communication skills by creating a presentation on your data analysis findings.

Browse courses on Data Visualization

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Summarize your analysis and findings.
Create data visualizations to illustrate your insights.
Develop a clear and concise narrative.
Practice delivering your presentation.
Share your presentation with peers or a wider audience.

Career center

Learners who complete Gemini for Data Scientists and Analysts will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Gemini for Data Scientists and Analysts.

AI Engineering

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Serves as the definitive engineering blueprint for building production applications on multimodal foundation models like Google Gemini, covering long-context prompting, retrieval-augmented generation, agentic tool calling, evaluation pipelines, and latency optimization.

Gemini for Data Scientists and Analysts

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What's inside

Syllabus

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Reviews summary

Gemini for data analysis in bigquery

Activities

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