Process Data from Dirty to Clean 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 beginner-level Process Data from Dirty to Clean online course will help the students develop the skills required to be a data analyst. It is an online programme and thus does not limit the students with any time restriction. Students across the countries can apply for this course. The programme deals with the topics such as tools used in data analysis, cleaning and checking data using the spreadsheet and SQL.

The Process Data from Dirty to Clean certification course also helps the students gain information regarding data verification. The course is provided in association with Google. The programme is free for all the participants if they learn from it in the audit mode. Since it is a beginner level programme, it does not require any specific academic eligibility, except the basic understanding of mathematics.

The Process Data from Dirty to Clean certification programme can be completed in 25 hours. However, it can be pursued weekly according to the requirements of the student. At the end of the course, after the successful completion of all lessons and assignments, students get a chance to enjoy the benefits of professional certification.

Course and certificate fees

The fees for the course Process Data from Dirty to Clean 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 Process Data from Dirty to Clean training is apt for the following people-

Students who want to become a data analyst.
Students who want to pursue a higher degree in the relevant field.

Eligibility criteria

Education

Candidates are expected to have the high-school level mathematical understanding to pursue this course.

Certification Qualifying Details

Students are required to purchase the certification course by making the payment of the quoted amount.

What you will learn

Sql knowledge

Upon the completion of the Process Data from Dirty to Clean training, students will be able to comprehend the following points-

Students will be able to understand the tools and techniques used in the domain of data analysis.
Candidates will gain an understanding of checking and cleaning the data through spreadsheets and SQL.
Participants will get to know how to verify the results of the cleaning data in the Process Data from Dirty to Clean certification.
Students will learn about data integrity along with the different types of integrity in the course.
Candidates will learn about the basic SQL functions as well as queries.
Students will understand the importance of data cleaning reports in the Process Data from Dirty to Clean programme.
Participants will gain an understanding of how to report the verified data.

The syllabus

Module 1: The importance of integrity

Videos

Introduction to focus on integrity
Why data integrity is important
Balancing objectives with data integrity
Dealing with insufficient data
The importance of sample size
Using statistical power
Determine the best sample size
Evaluate data reliability

Readings

Course 4 overview: Set your expectations
Helpful resources and tips
More about data integrity and compliance
Well-aligned objectives and data
When you find an issue with your data
Calculate sample size
When data isn't readily available
Sample size calculator
All about margin of error
Glossary terms from module 1

Quizzes

Module 1 challenge
Test your knowledge on data integrity and analytics objectives
Self-Reflection: Pre-cleaning activities
Test your knowledge on insufficient data
Test your knowledge on margin of error

Assignment

Test your knowledge on testing your data

Plugin

Refresher: Your Google Data Analytics Certificate roadmap

Module 2: Clean data for more accurate insights

Videos

Clean it up!
Why data cleaning is critical
Angie: I love cleaning data
Recognize and remedy dirty data
Data-cleaning tools and techniques
Clean data from multiple sources
Data-cleaning features in spreadsheets
Optimize the data-cleaning process
Different data perspectives
Even more data-cleaning techniques

Readings

What is dirty data?
Common data-cleaning pitfalls
Step-by-Step guide: Data-cleaning features in spreadsheets
Step-by-Step: Optimize the data-cleaning process
Workflow automation
Step-by-Step: Different data perspectives
Step-by-Step: Even more data-cleaning techniques
Working with .csv files
Develop your approach to cleaning data
Glossary terms from module 2

Quizzes

Module 2 challenge
Hands-On Activity: Cleaning data with spreadsheets
Test your knowledge on the first steps toward clean data
Hands-On Activity: Clean data with spreadsheet functions
Test your knowledge on cleaning data in spreadsheets

Assignment

Test your knowledge on data cleaning

Plugin

Principles of data integrity

Module 3: Data Cleaning with SQL

Videos

Use SQL to clean data
Sally: For the love of SQL
Understand SQL capabilities
Spreadsheets versus SQL
Widely used SQL queries
Evan: Having fun with SQL
Clean string variables using SQL
Advanced data-cleaning functions, part 1
Advanced data-cleaning functions, part 2

Module 3: Cleaning data with SQL

Readings

How a junior data analyst uses SQL
SQL dialects and their uses
Review: Set up your BigQuery account
Review: Get started with BigQuery
Optional: Upload the customer dataset to BigQuery
Optional: Upload the store transactions dataset to BigQuery
Glossary terms from module 3

Quizzes

Module 3 challenge
Hands-On Activity: Processing time with SQL
Hands-On Activity: Clean data using SQL
Self-Reflection: Challenges with SQL

Assignment

Test your knowledge on SQL queries

Plugin

Data-cleaning with SQL functions

Module 4: Verify and report on cleaning results

Videos

Verify and report results
Confirm data-cleaning meets business expectations
Verification of data cleaning
Capture cleaning changes
Why documentation is important
Feedback and cleaning

Readings

Step-by-Step: Verification of data cleaning
Data-cleaning verification checklist
Embrace changelogs
Advanced functions for speedy data cleaning
Glossary terms from module 4

Module 4: Verify and report on cleaning results

Quizzes

Module 4 challenge
Test your knowledge on manual data cleaning
Self-Reflection: Creating a changelog
Test your knowledge on documenting the cleaning process

Module 5: Optional: Add data to your resume

Videos

About the data-analyst hiring process
The data analyst job-application
Build a resume
Make your resume unique
Joseph: Black and African American inclusion in the data industry
Translate past work experience
Kate: My career path as a data analyst
Where does your interest lie?

Readings

The importance of diversity on a data analytics team
CareerCon resources on YouTube
Add technical skills to your resume
Add professional skills to your resume

Module 5: Optional: Adding data to your resume

Quizzes

Hands-On Activity: Build a resume
Hands-On Activity: Adding skills to a resume
Hands-On Activity: Continue refining your resume

Module 6: Course Course wrap-up

Videos

Congratulations! Course wrap-up

Readings

Reflect and connect with peers
Course 4 glossary
Coming up next

Admission details

The admission process of the Process Data from Dirty to Clean programme comprises of the following steps:

Step 1- Participants must visit the official webpage of Coursera.

Step 2- Candidates need to create an account on Coursera by clicking on the Join for free tab at the top right corner of the page.

Step 3- After creating the account, students need to enrol into the course by clicking on the enrol option on the page.

Step 4- Students will be asked to provide their credentials to enrol for the course.

Step 5- Students need to click on the Go to course on the redirected page to access the lessons.

Scholarship Details

Candidates who cannot pursue the course due to financial restraints can apply for the scholarship. Candidates who successfully complete the application process will get a positive response within 15 days.

How it helps

Students who apply for the Process Data from Dirty to Clean course will learn the aspects of data analysis. The course covers several topics such as tools to be used in data analysis, data verification, data reporting, etc. This beginner-level course helps the candidate prepare themselves for the job role of the data analyst. Students can apply for an internship or an introductory level job opportunity in the domain of data analysis.

If the students have access to the course subscription, they will get a professional certificate for the programme. The professional certificate has great value in the job market. It helps the candidate increase the weightage of their job profile. The Process Data from Dirty to Clean certification benefits those who want to get practical exposure in the industry by joining an internship or job opportunity.

Students can also use the certification to apply for a higher level of training in data analysis. The professionals from the relevant field can apply for the Process Data from Dirty to Clean certification course to gain some basic skills and brush up their concepts. The students who need a job can share the certification on their LinkedIn profiles and reach the maximum number of recruiters at once.