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Google Career Certificates

This course is the eighth and final course in the Google Data Analytics Certificate. You’ll have the opportunity to complete a case study, which will help prepare you for your data analytics job hunt. Case studies are commonly used by employers to assess analytical skills. For your case study, you’ll choose an analytics-based scenario. You’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. You’ll also learn about useful job hunting skills, common interview questions and responses, and materials to build a portfolio online. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

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This course is the eighth and final course in the Google Data Analytics Certificate. You’ll have the opportunity to complete a case study, which will help prepare you for your data analytics job hunt. Case studies are commonly used by employers to assess analytical skills. For your case study, you’ll choose an analytics-based scenario. You’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. You’ll also learn about useful job hunting skills, common interview questions and responses, and materials to build a portfolio online. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, learners will:

- Learn the benefits and uses of case studies and portfolios in the job search.

- Explore real world job interview scenarios and common interview questions.

- Discover how case studies can be a part of the job interview process.

- Examine and consider different case study scenarios.

- Have the chance to complete your own case study for your portfolio.

Enroll now

What's inside

Syllabus

Learn about capstone basics
A capstone is a crowning achievement. In this part of the course, you’ll be introduced to capstone projects, case studies, and portfolios, and will learn how they help employers better understand your skills and capabilities. You’ll also have an opportunity to explore the online portfolios of real data analysts.
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Optional: Build your portfolio
In this part of the course, you’ll review two possible tracks to complete your case study. You can use a dataset from one of the business cases provided or search for a public dataset to develop a business case for an area of personal interest. In addition, you'll be introduced to several platforms for hosting your completed case study.
Optional: Use your portfolio
Your portfolio is meant to be seen and explored. In this part of the course, you’ll learn how to discuss your portfolio and highlight specific skills in interview scenarios. You’ll also create and practice an elevator pitch for your case study. Finally, you’ll discover how to position yourself as a top applicant for data analyst jobs with useful and practical interview tips.
Put your certificate to work
Earning your Google Data Analytics Certificate is a badge of honor. It's also a real badge. In this part of the course, you'll learn how to claim your certificate badge and display it in your LinkedIn profile. You'll also be introduced to job search benefits that you can claim as a certificate holder, including access to the Big Interview platform and Byteboard interviews.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a framework for students to build a digital portfolio, which is standard in industry for data analysts
Develops strong analytical skills, which are core competencies for data analysts
Students gain hands-on experience using industry-standard tools and resources, which is valuable for future job applications
Taught by current Google data analysts, which provides students with access to insights from industry professionals
Covers resume-building techniques, which are useful for students transitioning into data analyst roles
Provides opportunities to practice case studies, which are commonly used in data analyst job interviews

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Reviews summary

Google data analytics capstone: complete a case study

**Learners say** this certificate program provides a strong foundation in data analytics skills and prepares them for entry-level analyst roles. The case study is highlighted as a valuable hands-on experience, but some learners note that it could be improved with better guidance and project support.
learners say this certificate program provides a strong foundation in data analytics skills and prepares them for entry-level analyst roles
"Learners say this certificate program provides a strong foundation in data analytics skills and prepares them for entry-level analyst roles."
The hands-on case study allows you to apply your data analytics skills to real-world data. It is a valuable experience that can help you prepare for entry-level analyst roles.
"The case study is highlighted as a valuable hands-on experience, but some learners note that it could be improved with better guidance and project support."
The case study could benefit from better guidance and project support.
"The case study is highlighted as a valuable hands-on experience, but some learners note that it could be improved with better guidance and project support."

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 Google Data Analytics Capstone: Complete a Case Study with these activities:
Review basic statistics
Improves preparation for learning data analysis by reviewing fundamental statistical concepts.
Browse courses on Statistics
Show steps
  • Review probability distributions and measures of central tendency.
  • Study hypothesis testing and confidence intervals.
  • Practice solving statistical problems.
Take a data analysis online tutorial
Provides a structured approach to learning data analysis concepts and techniques.
Show steps
  • Find an online tutorial that covers the basics of data analysis.
  • Follow the tutorial and complete all the exercises.
  • Review the material and test your understanding.
Organize your course materials
Improves navigation and accessibility of course content, reducing time spent searching for information.
Show steps
  • Create a system for organizing your notes, assignments, and other materials.
  • Review your materials regularly and update your organization system as needed.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Write a blog post about data analysis
Enhances understanding by requiring clear and concise explanation of data analysis concepts.
Show steps
  • Choose a data analysis topic to write about.
  • Research the topic and gather information.
  • Write a clear and concise blog post explaining the topic.
  • Share your blog post with others.
Join a data analysis study group
Provides opportunities for collaboration, discussion, and sharing of knowledge.
Show steps
  • Find a study group or create your own.
  • Meet regularly to discuss course material and work on projects.
  • Help each other with understanding concepts and solving problems.
Practice data analysis problems
Improves analytical skills and reinforces understanding of data analysis concepts.
Browse courses on Data Analysis
Show steps
  • Find practice problems online or in textbooks.
  • Solve the problems and check your answers.
  • Review your mistakes and identify areas for improvement.
Create a data analysis project
Provides hands-on experience applying data analysis techniques and solidifies understanding.
Browse courses on Data Analysis
Show steps
  • Choose a dataset and define your research question.
  • Clean and prepare the data.
  • Analyze the data and draw conclusions.
  • Create data visualizations to present your findings.

Career center

Learners who complete Google Data Analytics Capstone: Complete a Case Study will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use data to solve complex problems and develop innovative solutions. This course can help aspiring Data Scientists develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data mining, machine learning, and statistical modeling, which are all essential skills for Data Scientists. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Business Analyst
Business Analysts work with businesses to improve their performance by analyzing data and identifying areas for improvement. This course can help aspiring Business Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data analysis, process improvement, and project management, which are all essential skills for Business Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Statistician
Statisticians collect, analyze, and interpret data to provide insights and help organizations make informed decisions. This course can help aspiring Statisticians develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data analysis, statistical modeling, and probability, which are all essential skills for Statisticians. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Data Analyst
Data Analysts examine and interpret data to provide insights and help organizations make informed decisions. This course can help aspiring Data Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data preparation, data analysis, and data visualization, which are all essential skills for Data Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and trends. This course can help aspiring Market Researchers develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data analysis, survey design, and market segmentation, which are all essential skills for Market Researchers. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course can help aspiring Actuaries develop the skills and knowledge necessary to succeed in this role. The course covers topics such as probability, statistics, and finance, which are all essential skills for Actuaries. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Consultant
Consultants provide advice and guidance to businesses on a variety of topics, including data analysis, business strategy, and operations management. This course can help aspiring Consultants develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data analysis, business strategy, and project management, which are all essential skills for Consultants. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to improve the efficiency of business operations. This course can help aspiring Operations Research Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as linear programming, optimization, and simulation, which are all essential skills for Operations Research Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to develop trading strategies and models. This course can help aspiring Quantitative Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as financial modeling, data analysis, and risk management, which are all essential skills for Quantitative Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Financial Analyst
Financial Analysts use financial data to make investment recommendations and provide insights to businesses. This course can help aspiring Financial Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as financial modeling, valuation, and investment analysis, which are all essential skills for Financial Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Risk Analyst
Risk Analysts identify and assess risks to businesses and develop strategies to mitigate those risks. This course can help aspiring Risk Analysts develop the skills and knowledge necessary to succeed in this role. The course covers topics such as risk assessment, risk management, and financial analysis, which are all essential skills for Risk Analysts. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Product Manager
Product Managers are responsible for the development and marketing of products. This course can help aspiring Product Managers develop the skills and knowledge necessary to succeed in this role. The course covers topics such as product development, marketing, and data analysis, which are all essential skills for Product Managers. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Data Engineer
Data Engineers design and build the infrastructure and systems that are used to store and analyze data. This course can help aspiring Data Engineers develop the skills and knowledge necessary to succeed in this role. The course covers topics such as data warehousing, data mining, and big data, which are all essential skills for Data Engineers. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Database Administrator
Database Administrators are responsible for the maintenance and security of databases. This course may be useful for aspiring Database Administrators who are interested in working with data-intensive applications. The course covers topics such as data management, database security, and performance tuning, which can all be valuable skills for Database Administrators. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course may be useful for aspiring Software Engineers who are interested in developing data-driven applications. The course covers topics such as data analysis, software development, and project management, which can all be valuable skills for Software Engineers. Additionally, the course provides learners with the opportunity to complete a case study, which can help them demonstrate their analytical abilities to potential employers.

Reading list

We've selected 14 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 Google Data Analytics Capstone: Complete a Case Study.
Provides a comprehensive overview of Google Analytics, one of the most popular web analytics tools used by businesses today. It covers the basics of Google Analytics, such as how to set up an account, track website traffic, and analyze data. It also covers more advanced topics, such as how to use Google Analytics to track conversions, measure the effectiveness of marketing campaigns, and identify opportunities for improvement.
Provides a comprehensive overview of data science, covering the basics of data science, such as data collection, data cleaning, and data analysis. It also covers more advanced topics, such as data mining, machine learning, and artificial intelligence.
Provides a comprehensive overview of big data analytics, covering the challenges and opportunities of big data. It also covers the different technologies and techniques that are used to analyze big data.
Provides a gentle introduction to machine learning, covering the basics of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive overview of deep learning, covering the basics of deep learning, such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of SQL, a powerful programming language used to query and analyze data. It covers the basics of SQL, such as data types, operators, and functions. It also covers more advanced topics, such as joins, subqueries, and views.
Provides a comprehensive overview of Python, a popular programming language used for data analysis. It covers the basics of Python, such as data types, operators, and functions. It also covers more advanced topics, such as data structures, algorithms, and libraries.
Provides a comprehensive overview of data visualization, covering the basics of data visualization, such as charts, graphs, and maps. It also covers more advanced topics, such as interactive data visualization, dashboards, and storytelling with data.
Provides a practical guide to data storytelling, covering the entire process from data collection to data visualization. It includes case studies and examples from a variety of industries, making it a valuable resource for anyone who wants to learn more about data storytelling.
Provides a philosophical exploration of the ethical issues surrounding data, covering topics such as privacy, surveillance, and discrimination. It valuable resource for anyone who wants to think more deeply about the ethical implications of data.
Provides a concise overview of big data, covering the challenges and opportunities of big data. It also covers the different technologies and techniques that are used to analyze big data.
Provides a gentle introduction to data science, covering the basics of data science, such as data collection, data cleaning, and data analysis. It also covers more advanced topics, such as data mining, machine learning, and artificial intelligence.
Provides a comprehensive overview of statistical learning, covering the basics of statistical learning, such as linear regression, logistic regression, and tree-based methods. It also covers more advanced topics, such as regularization, model selection, and ensemble methods.

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