20 Tips for Studying Google Data Analytics Professional Certification
20 Tips for Studying Google Data Analytics Professional Certification
March of 2021 saw Google introduce its Data Analytics Professional Certificate with a bold claim that it would help graduates get a job in data analytics with no relevant experience required as covered over at runrex.com. This article will look to help you prepare for this course by outlining what it is all about, the skills it will equip you with, how much it costs, and tips to help you pass.
What is the Google Data Analytics Professional Certificate?
From discussions on the same over at guttulus.com, the Google Data Analytics Professional Certificate is a professional training designed by Google that prepares you to become a junior data analyst, a database administrator, and other related positions. This certificate aims to fill the gap in data analytics positions seen in all industries.
What is the makeup of the course and where is it offered?
As is revealed in discussions over at runrex.com, the Google Data Analytics Professional Certification is made up of 8 courses that can be completed in less than 6 months with less than 10 hours put in every week. The courses are completed through the online platform, Coursera.
What do you learn?
Throughout the Google Data Analytics Professional Certificate, you will learn the basics and fundamental skills to enter an entry-level data analyst position. This begins with you learning about the practices and processes that people in these positions use in their daily work as discussed over at guttulus.com. After that, you will learn how to use the tools necessary for data cleaning, organization, analyzing, and visualizing, such as:
Spreadsheets (for collecting and organizing data)
SQL (for organizing and extracting data)
Tableau (for visualizing data)
R (for analyzing and wrangling data)
Presentations (for explaining and sharing your discoveries)
Any additional Google support?
It is also worth mentioning that Google also supports you through the whole job preparation process by providing you with a resume-building tool, mock interviews, and career networking support to help you get a job after you complete the program.
The Course Curriculum
As already mentioned, Google has developed 8 courses to help you become proficient in data analysis. They are:
Course 1: Learning the Foundations of Data Analysis
This introductory course starts at the very beginning with a gentle introduction into what the data analysis job position entails, what a data analyst does daily, the skills a data analyst needs to be successful, and a description of the first basic terms and concepts that you will need to complete the course.
Course 2: How to Ask the Right Questions to Make a Data-Driven Decision
This course, as articulated over at runrex.com, focuses on helping you learn how to ask the right questions to make a data-driven decision. It covers the basics of effective questioning, how to apply those questioning techniques to real-world business situations, and the importance of using structured thinking and clear communication with stakeholders to achieve business objectives.
Course 3: Data Preparation
The 3rd course covers everything you need to know about data preparation and extraction. According to guttulus.com, this course covers the use of spreadsheets and SQL to extract data, how to organize and protect data, and the basics of data ethics and privacy.
Course 4: Data Cleaning
As is covered over at runrex.com, the fourth course covers data cleaning using spreadsheets and SQL, as well as the development of data cleaning reports.
Course 5: Data Analysis
The fifth course focuses entirely on the data analysis process using spreadsheets and SQL, and here, you will learn how to use formulas, functions, and SQL queries to conduct an analysis.
Course 6: Data Visualization
The sixth course in this program covers the storytelling aspect of data analysis. It focuses on helping you understand how to bring your data to life, and you will learn how to use Tableau to create dashboards and visualizations that you will then learn how to present to an audience.
Course 7: Using R Programming for Data Analysis
As the subject matter experts over at guttulus.com point out, the seventh course covers one of the programming languages often used in data analysis; R. You will learn how to use R and RStudio to clean, organize, analyze, visualize, and report data analyses.
Course 8: Capstone Project
The final course in the program, as discussed over at runrex.com, begins with teaching you the benefits of case studies and portfolios for your job search and goes over job-hunting and interview skills. In the end, you are given the option to complete a capstone project that can be used for your professional portfolio.
Who this course is for and isn’t for
This course is for:
According to guttulus.com, this course is for people who:
Are complete beginners with data analysis and have no prerequisite knowledge
Have 10 hours a week to dedicate to studying
Want to learn the basics of data analysis
This course is not for:
On the other hand, this course is not for people who:
Are already proficient in data analysis as it is at a very beginner level, and, therefore, is not for those who already have experience or have taken other data analytics MOOCs.
Are looking to work in Python
Don’t have time to dedicate to the course, since data analysis is best learned using a regular schedule
How much does the program cost?
The Google Data Analytics Professional Certificate is accessed through Coursera as already mentioned, which has a $39 monthly subscription fee. Therefore, if you take 6 months to complete the course, the cost will be approximately $234.
Tips for studying for the Google Data Analytics Professional Certificate
Given that MOOCs have an average completion rate of less than 10%, it is important to set yourself up for success early on by figuring out how you plan to study for this certificate, and the following tips should help.
Set up a schedule
The first step to completing this course is to set up a study schedule for yourself that you actually follow as outlined over at runrex.com. Rather than telling yourself that you will study for 10 hours a day, which will lead to burnout which may cause you not to finish the program, pace yourself by creating a balanced schedule. 10 hours per week of study can be broken up into 4 days of 2.5 hours of study each day, and from there, you plan out what parts of the course you want to get accomplished in those 2.5 hours.
Keep yourself accountable
It is all well and good making a schedule, but it will mean nothing if you can’t follow through on it and stick to it according to guttulus.com. You can keep yourself accountable by live-streaming or filming your study sessions, joining a study group, blogging about your studying, or having a trusted friend remind you of your need to study.
Aim for a broad understanding of the topics
Studying tech is totally different from anything else as explained over at runrex.com. Where normally you would need to have a deep understanding of topics to be able to succeed in a given field, in tech, you simply need a broad understanding of topics – and the willingness to admit when you don’t know something. Therefore, aim to get a broad understanding of all the topics in this program as well as learning how to apply them effectively.
Take effective notes
To go along with the idea of having a broad understanding of concepts, it is important to take notes that help with this broad understanding. The key is not to take extensive notes, instead, focusing on grasping general concepts and writing notes that help apply them.
Don’t skip the capstone project
Google has made the final capstone project for this program optional, which means that you don’t have to complete it to pass the course. However, it is important to note that the best way to learn is by doing. Given that most MOOCs don’t offer a capstone project because of the demands on the instructors and the extra effort that has to be put in by the course provider, it would be the height of folly to pass up the chance to work on a capstone project with Google employees available to you to answer any question you come across.
This article only just begins to scratch the surface as far as this topic is concerned, and you can uncover more insights on the same over at the excellent runrex.com and guttulus.com.
