Are you eager to step into the world of data analytics but feeling overwhelmed by the sheer number of courses available? You’re not alone.
That’s why I’ve taken the time to sift through Coursera‘s vast catalog and identify the top courses that will help you master data analytics in no time.
Let’s dive into the best Coursera data analytics courses and see which one is right for you.
What are the Best Coursera Data Analytics Courses?
We’ve compiled a list of the best and highest rated Coursera data analyst courses.
Introduction to Data Analytics: The Perfect Starting Point
Get a solid understanding of the data analytics landscape and the tools and technologies used by professionals.
Part of the IBM Data Science Professional Certificate, this course covers the basics of data analysis, data science, big data, and cloud computing. With a rating of 4.8 and a whopping 835,756 learners, this course is an excellent introduction to the world of data analytics.
The course covers essential concepts and techniques used by data analysts and data scientists, making it an excellent choice for beginners looking to break into the field. By the end of the course, you’ll have a solid understanding of the data analytics landscape and the tools and technologies used by professionals.
More details on Introduction to Data Analytics on Coursera.org.
Google Data Analytics Professional Certificate: Learn from the Masters
Master Google’s suite of analytics tools to tackle real-world data analysis challenges.
Google is synonymous with data, so it’s no surprise that their Google Data Analytics Professional Certificate course is top-notch. With a 4.8 rating and over 107k reviews, this standalone Google Professional Certificate course teaches you how to prepare, process, and analyze data to make informed business decisions.
You’ll learn about data cleaning, data manipulation, and data analysis, all while using Google’s suite of analytics tools like Google Sheets, BigQuery, and Data Studio. Upon completion, you’ll have the skills needed to tackle real-world data analysis challenges.
More details on Google Data Analytics on Coursera.org.
IBM Data Analyst: Master Python, SQL, and Excel
Develop a strong foundation in Python, SQL, and Excel for data analysis and visualization.
Part of the IBM Data Analyst Professional Certificate, this course has a 4.6 rating and 62.3k reviews. You’ll learn how to use Python, SQL, and Excel to perform data analysis and visualization, making this course ideal for anyone looking to develop a strong foundation in these essential tools.
Throughout the course, you’ll work with real-life datasets and gain hands-on experience in cleaning, analyzing, and visualizing data. By the end, you’ll be ready to tackle data analysis projects with confidence.
More details on IBM Data Analyst on Coursera.org.
Excel Skills for Business – Essentials: Hone Your Spreadsheet Skills
Harness the power of Excel for your data analysis needs and become a spreadsheet whiz.
Excel is a critical tool in any data analyst’s arsenal, and this course, part of the Excel Skills for Business Specialization, teaches you how to use Excel to manipulate, analyze, and present data. With a 4.9 rating and 51k reviews, this course offers a comprehensive introduction to Excel for business applications.
You’ll learn essential Excel functions, data analysis techniques, and visualization strategies, all while working with real-life examples. By the end of the course, you’ll be able to harness the power of Excel for your data analysis needs.
More details on Excel Skills for Business – Essentials on Coursera.org.
Data Analysis with Python: Harness the Power of Python Libraries
Build expertise in Python libraries like pandas, numpy, and matplotlib for data analysis.
Part of the IBM Data Science Professional Certificate, this course has a 4.7 rating and 49k reviews. It teaches you how to use Python libraries such as pandas, numpy, matplotlib, and seaborn to analyze data sets.
Throughout the course, you’ll learn how to import and clean data, perform statistical analysis, and create visualizations using Python. With hands-on examples and exercises, you’ll develop a strong foundation in data analysis with Python, a must-have skill for any aspiring data analyst.
More details on Data Analysis with Python on Coursera.org.
Data Visualization with Python: Bring Your Data to Life
Create visually appealing and informative data visualizations to support data-driven decision-making.
Another course in the IBM Data Science Professional Certificate, Data Visualization with Python, has a 4.7 rating and 42k reviews. It teaches you how to create different types of charts and graphs using Python libraries such as matplotlib, seaborn, folium, and word cloud.
In this course, you’ll learn about various visualization techniques, such as bar charts, line charts, scatter plots, heatmaps, and more. You’ll also explore interactive visualizations and geospatial data mapping. By the end of the course, you’ll be able to create visually appealing and informative data visualizations to support data-driven decision-making.
More details on Data Visualization with Python on Coursera.org.
SQL for Data Science with R: Unleash the Power of Relational Databases
Learn to use SQL and R together for powerful data analysis from relational databases.
With a rating of 4.8 and 36k reviews, this specialization teaches you how to use SQL and R to query, manipulate, analyze, and visualize data from relational databases. This set of courses is perfect for those looking to master two of the most popular tools used by data analysts and data scientists alike.
Throughout the specialization, you’ll learn how to write SQL queries to extract data from databases, use R for data manipulation and statistical analysis, and create compelling visualizations. By the end, you’ll have a comprehensive understanding of how SQL and R can be used together for powerful data analysis.
More details on SQL for Data Science with R Specialization on Coursera.org.
Data Analysis Tools Specialization: Master Statistical Techniques
Conduct rigorous data analysis using a range of statistical tools across various fields.
This specialization, with a rating of 4.5 and 400 reviews, teaches you how to use various statistical tools such as ANOVA, regression, chi-square tests, correlation coefficients, effect sizes, power analysis, etc., to analyze data sets in different fields such as psychology, education, health care, and more.
Throughout the specialization, you’ll gain a solid understanding of the statistical techniques used in various research settings and learn how to apply them to real-world data sets. By the end of the specialization, you’ll be equipped with the skills needed to conduct rigorous data analysis using a range of statistical tools.
More details on Data Analysis Tools Specialization on Coursera.org.
Data Analysis and Presentation Skills – the PwC Approach: Sharpen Your Data Storytelling Skills
the PwC Approach Specialization: Master data storytelling skills and effectively communicate data-driven insights.
Offered by PwC, this specialization has a rating of 4.7 and 9k reviews. It teaches you how to use Excel and PowerPoint to collect, analyze, and present data in a professional way. This set of courses is perfect for those looking to hone their data storytelling skills and learn how to effectively communicate data-driven insights.
Throughout the specialization, you’ll learn how to leverage Excel’s advanced features for data analysis, create visually appealing charts and graphs, and build compelling PowerPoint presentations that tell a data-driven story. By the end, you’ll have the skills needed to present data in a way that engages and informs your audience.
More details on Data Analysis and Presentation Skills – the PwC Approach on Coursera.org
Coursera Data Analyst Offerings: Why Choose Coursera?
When considering the field of data analytics, Coursera has undoubtedly etched its reputation as a top online learning platform. Opting for Coursera data analyst courses provides learners with an opportunity to study from globally-renowned universities and institutions.
Their content is designed to impart practical and theoretical knowledge, ensuring a holistic learning experience. With the constantly increasing importance of data in today’s world, having a reliable platform to guide you through the journey is crucial.
Coursera PwC Collaborations: Quality Meets Real-World Experience
One of the standout collaborations on Coursera is with PwC, a global network of firms delivering assurance, advisory, and tax services.
The “Coursera PwC” courses are tailored to offer the best of both worlds: academic rigor and real-world insights. PwC’s industry experience, combined with Coursera’s platform, offers students the chance to learn analytics from some of the best in the business.
Coursera Analytics Reviews: Deciphering the Feedback
Browsing through “data analytics Coursera review” sections, potential learners can gauge the quality, relevance, and efficiency of the offered courses. Reviews often highlight the real-world applicability, course content depth, and instructor expertise.
Thus, prospective students can make informed decisions based on these insights. Remember, knowledge is only as good as its application, and Coursera analytics courses have consistently received acclaim for bridging the gap between learning and its practical use in the professional world.
Frequently Asked Questions (FAQ’s)
What are the best Coursera data analytics courses?
There are several excellent data analytics courses available on Coursera. Some of the best options include “Data Analytics Foundations for Accountancy I” by the University of Illinois, “Data Analysis and Presentation Skills: the PwC Approach” by PwC, and “Data Analytics for Business” by the University of Colorado Boulder.
What are the prerequisites for taking Coursera data analytics courses?
Prerequisites for Coursera data analytics courses can vary depending on the specific course. Some courses may require prior experience in statistics or programming, while others may not have any prerequisites at all. It is important to review the course descriptions and requirements before enrolling in any course.
Are Coursera data analytics courses accredited?
Coursera is not an accredited institution, but many of the courses offered on the platform are created and taught by professors from accredited universities. While the courses themselves may not be accredited, they can still provide valuable knowledge and skills that can be applied in a professional setting.
How long do Coursera data analytics courses take to complete?
The length of Coursera data analytics courses can vary depending on the course and the individual’s pace. Some courses can be completed in a few weeks, while others may take several months. Many courses offer flexible schedules and self-paced learning options, allowing individuals to work at their own speed.
Can Coursera data analytics courses be audited for free?
Coursera data analytics courses can often be audited for free, but this may not include access to all course materials or the ability to receive a certificate of completion. Paid enrollment options may provide additional benefits such as graded assignments, access to instructors, and a verified certificate upon completion.
How can Coursera data analytics courses be beneficial in a professional setting?
Coursera data analytics courses can be beneficial in a professional setting by providing individuals with valuable skills and knowledge that can be applied to a variety of industries and job roles. These courses can help individuals develop critical thinking, problem-solving, and data analysis skills that are highly sought after in many industries.
Are there any discounts available for Coursera data analytics courses?
Coursera offers financial aid options for individuals who cannot afford to pay for courses. In addition, many courses offer discounted rates for bulk purchases or for individuals who enroll in multiple courses at once. It is also worth checking for any promotional discounts or codes that may be available.
Justin is a full-time data leadership professional and a part-time blogger.
When he’s not writing articles for Data Driven Daily, Justin is a Head of Data Strategy at a large financial institution.
He has over 12 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.