Foundations: Data, Data, Everywhere
Updated on
Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Beginner
- Deadline
- Flexible
- Duration
- 20 hours
- Certificate
- Paid Certificate Available
- Course author
- Google Career Certificates
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Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystem
Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking
Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics
Describe the role of a data analyst with specific reference to jobs/positions
Description
This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will 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, you will:
- Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job.
- Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox.
- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process.
- Evaluate the role of analytics in the data ecosystem.
- Conduct an analytical thinking self-assessment.
- Explore job opportunities available to you upon program completion, and learn about best practices in the job search.
