Prepare Data for Exploration by Google via Coursera: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

The online course on Prepare Data for Exploration by Coursera is the third part of the series programme under the Google Data Analytics certificate. The course will equip the students with the skills needed to apply to introductory-level data analyst jobs. The experts will guide the students throughout the Prepare Data for Exploration online course. Over 24 hours, students will gain a detailed understanding of the following topics - Considerations in Data collection, Data formats in practice, The structure of data, Introduction to Data Ethics, the importance of data ethics, Introduction to data privacy, steps for ethical data use and others. The students will gain practical data analytics skills and learn how to use tools like SQL and spreadsheet to extract, organize and protect data. Hence the online session will help the students emerge as successful data analysts.

Course and certificate fees

The fees for the course Prepare Data for Exploration is -

Head	Amount in INR
1 month	Rs. 1,175
3 month	Rs. 2,351
6 month	Rs. 3,527

certificate availability

Yes

certificate providing authority

Coursera

Who it is for

Data analyst

The Prepare Data for Exploration certification will benefit the following students-

Candidates who want to secure a career in the domain of data analysis.

Eligibility criteria

Education

To apply for the Prepare Data for Exploration online course, the students need to have high-school level math skills.

Certification Qualification Details

The students will be rewarded with Prepare Data for Exploration certification once they complete the course after paying the requested amount.

What you will learn

Sql knowledge

On completing the Prepare Data for Exploration certification syllabus, the students will learn the following-

The professional ways of collecting data.
The techniques to modify data and its practical use.
The ways of analysing the spreadsheets using SQL.
Candidates will learn the boolean logic.
The difference between unbiased and biased data.
The relationship between data privacy and data ethics.
The process of determining data.
Types of data versus data types.
The process of identifying good data sources.
The details of data formats in practice.

The syllabus

Module 1: Data types and structures

Videos

Introduction to data exploration
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

Readings

Course 3 overview: Set your expectations
Helpful resources and tips
Select the right data
Data formats in practice
The effects of different structures
Data modeling levels and techniques
Use Boolean logic
Step-by-Step: Meet wide and long data
Transforming data
Glossary terms from module 1

Quizzes

Test your knowledge on collecting data
Optional Self-Reflection: Unstructured data
Test your knowledge on data formats and structures
Hands-On Activity: Introduction to Kaggle
Module 1 challenge

Assignment

Test your knowledge on data types, fields, and values

Plugins

Refresher: Your Google Data Analytics Certificate roadmap
Differentiate data types

Discussion Prompt

Meet and greet

Plugins

Refresher: Your Google Data Analytics Certificate roadmap
Differentiate data types

Module 2: Data responsibility

Videos

Ensuring data integrity
Bias: From questions to conclusions
Biased and unbiased data
Understanding bias in data
Identifying good data sources
What is "bad" data?
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

Module 2: Bias, credibility, privacy, ethics, and access

Readings

Data anonymization
The open-data debate
Sites and resources for open data
Glossary: Terms and definitions

Quizzes

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
Module 2 challenge

Discussion Prompt

Account for bias

Discussion Prompt

Account for bias

Module 3: Databases Essentials

Videos

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
Setting up BigQuery, including sandbox and billing options
How to use BigQuery
BigQuery in action

Readings

Databases in data analytics
Inspecting a dataset: A guided, hands-on tour
Metadata is as important as the data itself
From external source to a spreadsheet
Exploring public datasets
Using BigQuery
In-depth guide: SQL best practices
Glossary: Terms and definitions

Module 4: Organizing and protecting your data

Videos

Feel confident in your data
Let's get organized
All about file naming
Security features in spreadsheets

Readings

File organization guidelines
Balance security and analytics
Glossary terms from module 4

Quizzes

Test your knowledge on bringing data to order
Self-Reflection: Protect your resources
Test your knowledge on securing data
Module 4 challenge

Plugin

Effective file-naming and organization methods

Plugin

Effective file-naming and organization methods

Module 5: Optional: Engaging in the data community

Videos

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

Readings

Getting started with LinkedIn
Building connections on LinkedIn
Developing a network

Quiz

Self-Reflection: Adding Kaggle to your online presence

Module 3: Databases Essentials

Quizzes

Test your knowledge on working with databases
Test your knowledge on metadata
Test your knowledge on accessing data sources
Hands-On Activity: Clean data in spreadsheets with sorting and filtering
Self-Reflection: Compare databases and spreadsheets
Test your knowledge on sorting and filtering
Hands-On Activity: Introduction to BigQuery
Hands-On Activity: Create a custom table in BigQuery
Hands-On Activity: Choose the right tool for the job
Hands-On Activity: More practice with SQL
Test your knowledge on using SQL with large datasets
Module 3 challenge

app item

Hands-On Guided Project: Select a new city using BigQuery

app item

Hands-On Guided Project: Select a new city using BigQuery

Module 5: Engaging in the data community

Video

Manage 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
Congratulations! Course wrap-up

Readings

Get started with LinkedIn
Build connections on LinkedIn
Develop a network
Course 3 glossary
Coming up next..

Quiz

Self-Reflection: Add Kaggle to your online presence

Admission details

Filling the form

Students who wish to apply for the Prepare Data for Exploration online course can do so by following the given steps-

Step 1: The interested students can visit the course webpage.

Step 2: The enrol button needs to be clicked by the students.

Step 3: In the further steps, the students can choose to audit the course for free or apply for the course up-gradation by paying the amount as requested.

Scholarship Details

Applicants facing the financial crisis can apply for scholarships or financial aid to pursue the Prepare Data for Exploration programme. Students selected for the scholarship will be notified further.

How it helps

The Prepare Data for Exploration course gives students and professionals an opportunity to learn from the industry experts and professors and enhance their skills in the domain of data analysis. The Prepare Data for Exploration certification benefits the students who want to pursue a career as a data analyst. The course has been jointly developed by Google and Coursera.

The sessions will be held on the digital platform and can be accessed by the students in multiple subtitles. The Prepare Data for Exploration certification course provides successful candidates with a certificate that they can share over both digital and printed platforms to secure better jobs and career opportunities. The students, upon completion of the course, will have their professional skills enhanced and strengthened. Furthermore, for making the programme more affordable, scholarships are also made available to the students. The level of the course is intermediate.

FAQs

How much time will it take to continue the course?

The Prepare Data for Exploration certification course can be completed in 24 hours.

Is the session free?

No, the entire session is not free. Only the enrollment for the course is free. However, to access the graded material and the certificate, the course fee needs to be paid.