Become a DATA ANALYST with NO degree? The Google Data Analytics Professional Certificate.

Hey, Aspiring learners out there! Ever wanted to start a career in the field of Data? Let's check out the new professional certificate provided by google.

Table of Contents:

• Introduction

• About the course

• Tools & Skills involved in the course

• Benefits

• Conclusion

INTRODUCTION

Google recently announced a course for Data analytics in the month of March. This course aimed for the students or associates to get introduced to the field of Data analytics.

What is Data Analytics?

As the process of analyzing raw data to find trends and answer questions. Data Scientists and Analysts use data analytics techniques in their research, and businesses also use them to inform their decisions.

Data analysis can help companies better understand their customers, evaluate their ad campaigns, personalize content, create content strategies and develop products.

ABOUT THE COURSE

Google Data Analytics course is available on Coursera and you can enroll at a cost of $39 per month for all eight classes. As such, the faster you complete the class, the better it is.

There are 8 Courses in this Professional Certificate:

1. Foundations: Data, Data, Everywhere :

This course describes the basic foundation of data and tells us the lifecycle and its functionality. And also it will cover day to day responsibility of a data analyst. At the end of this course, we can discover a wide variety of terms and concepts relevant to the role of a junior data analyst.

2. Asking Questions to Make Data-Driven Decisions:

This course describes effective questioning techniques that can help guide analysis. And also understanding of data-driven decision-making and how data analysts present findings.

3. Preparing Data for Exploration

This course helps to identify different types of bias in data to help ensure data credibility. And to find the relationship between and importance of data ethics and data privacy. It also covers best practices for organizing data and keeping it secure.

4. Process Data from Dirty to Clean

This course is one of the best because it covers different methods to process a huge number of clustered data to the precise data, where it involves various methods of data cleaning and methods, logic to apply them. It covers tools like both SQL and Excel sheets.

5. Analyze Data to Answer Questions

This course describes what is involved in the data analysis process with reference to goals and key tasks, and the importance of organizing data before analysis with references to sorts and filters.

6. Share Data Through the Art of Visualization

This course explains the key concepts involved in design thinking as they relate to data visualization. And the use of data visualizations to talk about data and the results of data analysis, also the key concepts involved in data visualization.

7. Data Analysis with R Programming

This course describes the RStudio programming environment including its components and benefits, and programming languages and appropriate use including examples. It also differentiates between the R Console and R programming environments.

8. Capstone: Complete a Case Study

A case study deals with the basic understanding of previous courses, where we have to apply those concepts in such a way that at the end of the study we should be able to make data-driven decisions. Since it's an optional one but it is highly recommended to take participation to have some hands-on training and gain some confidence towards data analytics.

TOOLS & SKILLS

These are the tools that are covered in the course:

1. Tableau Software

Tableau is the fastest-growing data visualization and data analytics tool that aims to help people see and understand data.

In other words, it simply converts raw data into a very easily understandable format. Data analysis is great, as it is a powerful visualization tool in the business intelligence industry.

2. R Programming

R is a programming language and software environment for statistical analysis, graphics representation, and reporting.

Uses:

• Data Analytics.

• Statistical inferences.

• Machine learning and deep learning.

3. Google Big Query

BigQuery is a fully managed, serverless data warehouse that enables scalable analysis over petabytes of data. BigQuery was designed for analyzing data on the order of billions of rows, using a SQL-like syntax.

BENEFITS

Google has designed this course to prepare you for a job in your field of choice, you'll get access to a resume building tool, mock interviews, and career networking support designed to help you with your job search. You'll also be able to connect with over 130 US employers in the hiring consortium who are accepting candidates who have completed a Google Career Certificate.

CONCLUSION

I recently completed this course and had a very good experience so if you guys have some doubts do let me know in the comments or reach me at LinkedIn, Twitter.

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Hope this blog helps you to get started in the field of Data Analytics. Do share your views. 😄