Prepare Data for Exploration
4.8 /5- Offered byCoursera
Prepare Data for Exploration at Coursera Overview
Duration | 22 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Prepare Data for Exploration at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 8 in the Google Data Analytics
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level No experience with spreadsheets or data analytics is required. All you need is high-school level math skills and a curiosity about how things work.
- Approx. 22 hours to complete
- English Subtitles: English
Prepare Data for Exploration at Coursera Course details
- 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.
- 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.
Prepare Data for Exploration at Coursera Curriculum
Data types and data structures
Welcome to the course
Hallie: Fascinating data insights
Data collection in our world
Determining what data to collect
Discover data formats
Understanding structured data
Know the type of data you're working with
Data table components
Meet wide and long data
Course syllabus
Deciding if you should take the speed track
Optional: Your diagnostic quiz score and what it means
Selecting the right data
Data formats in practice
Data modeling levels and techniques
The structure of data
Understanding Boolean logic
Transforming data
Glossary: Terms and definitions
Optional: Familiar with data analytics? Take our diagnostic quiz
Test your knowledge on collecting data
Self-Reflection: Unstructured data
Test your knowledge on data formats and structures
Hands-On Activity: Applying a formula
Hands-on Activity: Introduction to Kaggle
Test your knowledge on exploring data types, fields, and values
*Weekly challenge 1*
Understanding bias, credibility, privacy, ethics, and access
Ensuring data integrity
Bias: From questions to conclusions
Biased and unbiased data
Understanding bias in data
Identifying good data sources
What is "bad" data?
Optional Refresher: Get ready for Qwiklabs
Introduction to data ethics
Optional Refresher: Alex: The importance of data ethics
Introduction to data privacy
Andrew: The ethical use of data
Features of open data
Andrew: Steps for ethical data use
Data anonymization
The open-data debate
Sites and resources for open data
Glossary: Terms and definitions
Test your knowledge on unbiased and objective data
Test your knowledge on data credibility
Test your knowledge on data ethics and privacy
Hands-On Activity: Kaggle datasets
Test your knowledge on open data
*Weekly challenge 2*
Databases: Where data lives
All about databases
Database features
Exploring metadata
Using metadata as an analyst
Metadata management
Megan: Fun with metadata
Working with more data sources
Importing data from spreadsheets and databases
Sorting and filtering
BigQuery in action
Databases in data analytics
From external source to a spreadsheet
Finding public datasets
Using BigQuery
In-depth guide: SQL best practices
Glossary: Terms and definitions
Test your knowledge on working with databases
Test your knowledge on metadata
Test your knowledge on accessing data sources
Self-Reflection: Databases and spreadsheets
Test your knowledge on sorting and filtering
Hands-On Activity: Applying SQL
Test your knowledge on using SQL with large datasets
*Weekly challenge 3*
Organizing and protecting your data
Feel confident in your data
Let's get organized
All about file naming
Security features in spreadsheets
Organization guidelines
Learning Log: Review file structure and naming conventions
Balancing security and analytics
Glossary: Terms and definitions
Test your knowledge on how to organize data
Self-Reflection: Protecting your resources
Test your knowledge on securing your data
*Weekly challenge 4*
Optional: Engaging in the data community
Managing your presence as a data analyst
Why an online presence is important
Tips for enhancing your online presence
Networking know-how
Benefits of mentorship
Rachel: Mentors are key
Getting started with LinkedIn
Building connections on LinkedIn
Developing a network
Self-Reflection: Adding Kaggle to your online presence
Congrats! Course wrap-up
Glossary: Terms and definitions
Coming up next...
*Course challenge*
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