You’re almost there! This is the seventh and final course of the Google Advanced Data Analytics Certificate. In this course, you have the opportunity to complete an optional capstone project that includes key concepts from each of the six preceding courses. During this capstone project, you'll use your new skills and knowledge to develop data-driven insights for a specific business problem.
Google Advanced Data Analytics Capstone
This course is part of Google Advanced Data Analytics Professional Certificate
Instructor: Google Career Certificates
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(969 reviews)
What you'll learn
Examine data to identify patterns and trends
Build models using machine learning techniques
Create data visualizations
Explore career resources
Skills you'll gain
Details to know
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8 quizzes, 1 assignment
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Build your Data Analysis expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from Google
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There are 3 modules in this course
To start, you’ll be provided with an overview of the optional capstone project and how it differs from the end-of-course projects. You’ll also receive helpful suggestions for successfully completing the capstone project. Finally, you'll learn how to incorporate your completed capstone project into your professional portfolio.
What's included
10 videos9 readings3 quizzes1 assignment2 ungraded labs
You’ll review data-focused career resources designed to help you effectively navigate the job market. You'll also get useful tips for polishing your resume and preparing for interviews.
What's included
10 videos7 readings4 quizzes
You’ll complete the final tasks necessary to earn your Google Advanced Data Analytics Certificate badge. Congratulations!
What's included
2 videos3 readings1 quiz1 plugin
Instructor
Offered by
Recommended if you're interested in Data Analysis
University of Illinois Urbana-Champaign
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Johns Hopkins University
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Reviewed on Nov 30, 2024
This course is outstanding and helpful, This is a friendly course, I learn allot about Data Science, Data Analyst after clearing this course.
Reviewed on Sep 10, 2023
excelent course for developing skills on EDA process and good start on creating machine learning models that fits the data.
Reviewed on Sep 13, 2023
I learned a great deal. This is a well-designed online course. I'd highly recommend it to others seeking an entry point into the data realm.
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Frequently asked questions
Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace.
Data science and advanced data analytics are part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists and advanced data analysts rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.
A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models.
Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.
Large volumes of data — and the technology needed to manage and analyze it — are becoming increasingly accessible. Because of this, there has been a surge in career opportunities for people who can tell stories using data, such as senior data analysts and data scientists. These professionals collect, analyze, and interpret large amounts of data within a variety of different organizations. Their responsibilities require advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning.