5 Free Courses To Break Into Data Analytics - KDnuggets

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5 Free Courses to Break Into Data Analytics

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If you’d like to switch to a data career, learning data analytics is super helpful. That’s why we put together this list of free data analytics courses to help you jumpstart your journey!

Even if you're an absolute beginner excited to explore the field of data, you’ll find these courses helpful. Because they are tailored towards aspiring data professionals and do not require prior programming experience.

Let’s get started.

Link: Google Data Analytics Professional Certificate

The Google Data Analytics Professional Certificate is one of the most popular specializations on Coursera—with close to 2 million learners from across the world. This certification program aims to get you up to speed on the fundamentals of data analytics. So as to help you land your entry-level analytics role in less than 6 months. It also does not require any prior experience.

The specialization has 8 courses to help you learn the fundamentals of data analysis using SQL, spreadsheets, Tableau, and R programming. The Google Data Analytics certificate program has the following courses:

Foundations: Data, Data, Everywhere
Ask Questions to Make Data-Driven Decisions
Prepare Data for Exploration
Process Data from Dirty to Clean
Analyze Data to Answer Questions
Share Data Through the Art of Visualization
Data Analysis with R Programming
Google Data Analytics Capstone: Complete a Case Study

Note: If you’re interested in getting the certificate for the Google Data Analytics specialization, you need to have a Coursera Plus subscription. If you’re unable to pay for your certificate, you can consider applying for financial aid. However, you can audit the course and access the course materials for free.

Link: Data Analysis with Python for Excel Users

The Google Data Analytics Professional Certificate should’ve given you a good grasp of the data analytics landscape and some of the essential tools like spreadsheets, SQL, R, and Tableau.

Now that you’re comfortable working with spreadsheets, you can learn Python for data analytics. Not only is Python much simpler to learn than R but also has a wider range of applications.

The Data Analytics with Python for Excel Users course by freeCodeCamp is a free course to learn the basics of data analysis with Python. It starts out by teaching you how to set up your Python development environment and use Jupyter notebooks.

The course has the following three modules:

Module 1: Hello world (covering the basics of Python)
Module 2: Introduction to Pandas
Module 3: Introduction to Pivot Tables in Pandas

This course should help you gain the foundations for analyzing data with Python. Which you can then build on as needed.

Link: Data Analysis with Python Certification

Now that you have the fundamentals of data analysis with Python down it's time to build on that by learning further. Data Analysis with Python, a free certification by freeCodeCamp will teach you everything on Python data analysis libraries while also working on simple projects.

You’ll learn to work with Python libraries NumPy, pandas, matplotlib, and Seaborn:

Basics of Jupyter notebooks
NumPy
Pandas
Data cleaning
Data visualization
Reading data from various sources
Parsing HTML

The projects you’ll build in this certification are:

Mean-Variance-Standard Deviation Calculator
Demographic Data Analyzer
Medical Data Visualizer
Page View Time Series Visualizer
Sea Level Predictor

This certification is completely free. After working through the course, you need to finish all the projects to claim your certificate.

Link: Google Advanced Data Analytics Professional Certificate

The Google Advanced Data Analytics Professional Certificate will help you dive deeper into data analysis with Python. While also learning statistics concepts and building machine learning models. This specialization also gives you the opportunity to work on a capstone project to apply what you’ve learned.

The courses in this specialization are as follows:

Foundations of Data Science
Get Started with Python
Go Beyond the Numbers: Translate Data into Insights
The Power of Statistics
Regression Analysis: Simplify Complex Data Relationships
The Nuts and Bolts of Machine Learning
Google Advanced Data Analytics Capstone

Note: As with the Google Data Analytics Professional Certificate, you can audit the Google Advanced Data Analytics specialization for free.

Link: IBM Data Analyst Professional Certificate

The IBM Data Analyst Professional Certificate is yet another comprehensive data analytics specialization offered by IBM on Coursera. Which will help you learn all the basics and essential tools to jumpstart your data analytics career.

This certification is also tailored for beginners, so you don't need any prior experience with programming and data analytics. Over a series of courses and capstone projects, the specialization will help you gain proficiency in the following:

Python and SQL basics
Excel and Tableau
Working with APIs and web services
Python data science libraries

The recommended time frame is around 4 months at about 10 hours of learning per week. The following are the courses in this data analyst professional certificate:

Introduction to Data Analytics
Excel Basics for Data Analysis
Data Visualization and Dashboards with Excel and Cognos
Python for Data Science, AI, and Development
Python Project for Data Science
Databases and SQL for Data Science with Python
Data Visualization with Python
IBM Data Analyst Capstone Project

Note: As with the other Coursera specializations, you can audit this for free.

I hope you found this list of data analytics courses helpful. If you’re looking to pivot to data analytics soon, I wish you the best in your learning journey.

If you’re looking for tips to navigate the data job market, read 7 Reasons Why You’re Struggling to Land a Data Science Job.

Bala Priya C is a developer and technical writer from India. She likes working at the intersection of math, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and coffee! Currently, she's working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more.