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Victor Dantas

In this course, _Adopting a Data Science Workflow in Google Cloud Platform_, you’ll learn to use various Google Cloud Platform solutions for your data science needs. First, you’ll explore data discovery and ingestion options. Next, you’ll discover BigQuery, Google Cloud’s data warehouse, and Vertex AI, an end-to-end data science and machine learning platform. Finally, you’ll learn how to process data at scale with Dataflow and Dataproc. When you’re finished with this course, you’ll have the skills and knowledge of Google Cloud Platform products needed to adopt an end-to-end data science workflow.

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Teaches skills and knowledge that enable learners to adopt a comprehensive data science workflow on GCP
Covers multiple aspects of data science on GCP, from data discovery to model deployment
Leverages popular GCP services like BigQuery, Vertex AI, Dataflow, and Dataproc, making the learning highly relevant to industry practices
Taught by Victor Dantas, an experienced instructor in data science and cloud computing

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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 Adopting a Data Science Workflow in Google Cloud Platform with these activities:
Review Cloud Platform Basics
Review the fundamentals and core principles of Cloud Platform services to strengthen your foundation for this course.
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  • Read the GCP documentation on key concepts and services.
  • Watch introductory videos and tutorials on GCP.
Compile a Glossary of Data Science Terms
Create a comprehensive glossary of key data science and Cloud Platform terms to enhance your understanding and retention of course concepts.
Show steps
  • Gather data science terms from course materials, online resources, and industry articles.
  • Define each term concisely and clearly.
  • Organize terms alphabetically or by topic.
  • Review the glossary regularly as a reference.
Review data science fundamentals
Get up to speed with data science concepts and techniques to prepare for the course.
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  • Review concepts of probability and statistics
  • Explore data science libraries and tools
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Review Big Query concepts
Help build a stronger knowledge base in data warehousing prior to starting the course
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  • Read articles on BigQuery basics
  • Watch videos on BigQuery use cases
  • Complete an online tutorial on BigQuery
Complete Quickstart Guides for GCP Services
Follow official GCP quickstart guides to gain hands-on experience with key services and build familiarity with their functionality.
Show steps
  • Choose a service you want to explore, such as BigQuery or Vertex AI.
  • Follow the step-by-step instructions in the quickstart guide to set up and use the service.
  • Test and experiment with different features and options.
Follow a data science tutorial series
Solidify your understanding of data science concepts by following a structured tutorial.
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Show steps
  • Identify a reputable data science tutorial series
  • Work through the tutorials and complete the exercises
Join a Study Group for Data Science Discussion
Engage with other learners by joining a study group to discuss course topics, share insights, and collaborate on projects.
Show steps
  • Reach out to classmates or online communities to find or form a study group.
  • Set regular meeting times and a communication platform.
  • Prepare discussion topics based on course materials and assignments.
Follow a tutorial on Vertex AI
Provide hands-on experience with Vertex AI, the end-to-end data science platform
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Show steps
  • Find a tutorial on Vertex AI
  • Follow the tutorial step-by-step
  • Complete the tutorial and review the results
Solve data science coding challenges
Deepen your understanding of data science algorithms and techniques by solving coding challenges.
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Show steps
  • Find a platform or website that offers data science coding challenges
  • Choose challenges that align with the course topics
  • Solve the challenges and review your solutions
Join a data science study group
Connect with other students and discuss course concepts and projects.
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Show steps
  • Find or create a study group with fellow data science students
  • Meet regularly to discuss course materials, share insights, and work on projects
Build a Simple Data Pipeline with Dataflow
Create a project that utilizes Dataflow for data processing to reinforce your understanding of its capabilities and practical applications.
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  • Define a simple data transformation or processing task.
  • Set up a Dataflow pipeline using the Python SDK or Cloud Console.
  • Run the pipeline and monitor its progress.
Build a Dataflow pipeline
Provide practical experience in building a data pipeline using Dataflow
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  • Design the data pipeline
  • Code the data pipeline in Python
  • Deploy the data pipeline to Google Cloud
Build a data science project
Apply your data science skills in a practical setting by building a project.
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Show steps
  • Identify a problem or opportunity that you can address with data science
  • Gather and prepare the necessary data
  • Build and evaluate a data science model
  • Deploy and monitor your model
Write a Blog Post on Data Science Workflow in GCP
Create a blog post that summarizes and elaborates on key concepts of data science workflow in GCP, reinforcing your understanding and allowing you to share knowledge with others.
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Show steps
  • Choose a specific aspect of the data science workflow in GCP to focus on.
  • Conduct research and gather information from course materials and external sources.
  • Write a well-structured and engaging blog post that explains the topic.
  • Share and promote your blog post on relevant platforms.
Develop a data science presentation
Enhance your communication and presentation skills by creating a data science presentation.
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  • Choose a data science topic to present on
  • Gather and analyze the necessary data
  • Create a presentation that effectively communicates your findings
  • Present your findings to an audience
Contribute to an open-source data science project
Gain hands-on experience and connect with the data science community by contributing to an open-source project.
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Show steps
  • Find an open-source data science project that aligns with your interests
  • Review the project's documentation and requirements
  • Identify a way to contribute to the project
  • Submit your contribution for review
Mentor junior data scientists
Sharpen your data science skills and help others by mentoring junior data scientists.
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Show steps
  • Offer your services as a mentor to junior data scientists
  • Meet regularly with your mentees to provide guidance and support
  • Share your knowledge and experience
  • Encourage your mentees to learn and grow

Career center

Learners who complete Adopting a Data Science Workflow in Google Cloud Platform will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in data science and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models to solve business problems. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in machine learning and learn how to use Google Cloud Platform tools to develop and deploy machine learning models. By taking this course, you'll gain the skills and knowledge needed to succeed as a Machine Learning Engineer.
Data Engineer
Data Engineers design and build data pipelines to collect, clean, and store data. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in data engineering and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Data Engineer.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses understand their customers and make informed decisions. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in data analysis and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Data Analyst.
Cloud Architect
Cloud Architects design and manage cloud computing environments. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in cloud computing and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Cloud Architect.
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in business intelligence and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Business Intelligence Analyst.
Data Warehouse Architect
Data Warehouse Architects design and manage data warehouses. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in data warehousing and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Data Warehouse Architect.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help businesses communicate insights and make informed decisions. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in data visualization and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Data Visualization Specialist.
Database Administrator
Database Administrators manage and maintain databases. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in database administration and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Database Administrator.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in software engineering and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Software Engineer.
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in consulting and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Consultant.
Project Manager
Project Managers plan and execute projects. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in project management and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Project Manager.
Business Analyst
Business Analysts analyze business needs and develop solutions to improve business processes. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in business analysis and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Business Analyst.
Teacher
Teachers educate students in a variety of subjects. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in teaching and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Teacher.
Statistician
Statisticians collect, analyze, and interpret data to help businesses understand their customers and make informed decisions. This course, _Adopting a Data Science Workflow in Google Cloud Platform_, can help you build a foundation in statistics and learn how to use Google Cloud Platform tools to manage and analyze data. By taking this course, you'll gain the skills and knowledge needed to succeed as a Statistician.

Reading list

We've selected nine 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 Adopting a Data Science Workflow in Google Cloud Platform.
Provides a practical introduction to machine learning with Python. It covers fundamental concepts, algorithms, and techniques, and provides hands-on examples and exercises.
Presents a probabilistic approach to machine learning, covering fundamental concepts, algorithms, and applications.
Provides a theoretical foundation for machine learning, covering algorithms, optimization techniques, and practical applications.
For learners seeking a broader perspective on data science in a business context, this book would provide valuable insights. It would complement the course's focus on technical implementation by emphasizing the strategic aspects of data science.
Offers a solid foundation in machine learning algorithms, which are covered in the course. It would be particularly helpful for learners seeking a deeper understanding of the theoretical aspects of machine learning.
This accessible guide to data science would be helpful for learners who are new to the field or seeking a gentle introduction. It could provide a foundation for understanding the concepts covered in the course.
For a more technical perspective on machine learning algorithms, this book provides a solid theoretical basis. It would be particularly beneficial for learners with a strong mathematical background.

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