This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. 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.
Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.
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:
- Find out how analysts decide which data to collect for analysis.
- Learn about structured and unstructured data, data types, and data formats.
- Discover how to identify different types of bias in data to help ensure data credibility.
- Explore how analysts use spreadsheets and SQL with databases and data sets.
- Examine open data and the relationship between and importance of data ethics and data privacy.
- Gain an understanding of how to access databases and extract, filter, and sort the data they contain.
- Learn the best practices for organizing data and keeping it secure.
What You Will Learn
- Explain factors to consider when making decisions about data collection
- Discuss the difference between biased and unbiased data
- Describe databases with references to their functions and components
- Describe best practices for organizing data
Course 3 of 8 in the Google Data Analytics Professional Certificate.
Syllabus
WEEK 1
Data types and data structures
We all generate lots of data in our daily lives. In this part of the course, you’ll check out how we generate data and how analysts decide which data to collect for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for exploration.
WEEK 2
Understanding bias, credibility, privacy, ethics, and access
When data analysts work with data, they always check that the data is unbiased and credible. In this part of the course, you’ll learn how to identify different types of bias in data and how to ensure credibility in your data. You’ll also explore open data and the relationship between and importance of data ethics and data privacy.
WEEK 3
Databases: Where data lives
When you’re analyzing data, you’ll access much of the data from a database. It’s where data lives. In this part of the course, you’ll learn all about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also check out metadata to discover the different types and how analysts use them.
WEEK 4
Organizing and protecting your data
Good organization skills are a big part of most types of work, and data analytics is no different. In this part of the course, you’ll learn the best practices for organizing data and keeping it secure. You’ll also learn how analysts use file naming conventions to help them keep their work organized.
WEEK 5
Optional: Engaging in the data community
Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you’ll explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.
Course challenge
Prepare for the course challenge by reviewing terms and definitions in the glossary. Then, demonstrate your knowledge of data collection, ethics and privacy, and bias during the quiz. You will also have an opportunity to apply your skill with spreadsheet and SQL functions, as well as filtering and sorting. Finally, secure and organize data with data analytics best practices.
