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Our Guide to the Best Data Analytics Courses

If you want a place in tomorrow’s corporate workforce, there’s a high likelihood that you’ll need to possess data analytics skills. This doesn't necessarily mean that you’ll be working as a machine learning engineer or data scientist, but increasingly companies are leveraging data analytics to inform their decision making, and in large part they are expecting their employees to do the same. In fact, the consultancy McKinsey expects the vast majority of the corporate workforce to utilize data skills for at least some aspect of their job.

While McKinsey is calling for companies to build out their own in-house analytics academies, most employees of companies big and small will be left on their own to upskill and stay relevant. Luckily, there are an increasing number of easily accessible data analytics courses — certificate programs, certifications, and bootcamps — that can help individuals from various backgrounds and with different levels of data literacy take the next step in their data education.

In this guide, we’ll demystify the field of data analytics, explain some of the reasons for taking a data analytics course, then dive into the different kinds of data analytics courses, their use-cases, and pros and cons. At the end, we’ll talk about what you should look for in a data analytics course before presenting some of our favorites.

What is data analytics?

Data analytics is an interdisciplinary field combining computer science, statistical analysis, and data management to extract actionable insights from data. The broader field of data analytics can be split into four sub-fields: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

  • Descriptive analytics focuses on understanding what has happened in the past, such as how a company’s sales performed during the holiday period in relation to the year before.

  • Diagnostic analytics focuses on understanding why past events have occurred, such as why one product might have sold more than in previous years.

  • Predictive analytics focuses on determining the likelihood of future events, such as which products might perform well if a company were to enter a new market.

  • Prescriptive analytics focuses instead on analyzing data to determine best courses of action for the future, such as whether a company should enter a new market or not.

Data Analytics vs. Business Analytics

One frequent point of confusion for those just looking to get into data analytics or build data skills is in the distinction between data analytics and business analytics. Different companies and data professionals will have different views regarding what the exact relationship is between the two. In our opinion, the difference isn’t so much one of essence as one of emphasis: data analytics and business analytics share a set of skills, techniques, and tools, often used to analyze data to solve business problems, but business analytics generally focuses on bigger picture business problems like reducing costs, boosting revenues, entering new markets, or initiating mergers and acquisitions.

If you’re interested in learning more about business analytics, including educational and career opportunities, check out our full explainer on the difference between a data analyst and a business analyst and our guide to business analytics master’s programs.

Data Analytics vs. Data Science

Another point of confusion comes when distinguishing data analytics from data science. As with data analytics and business analytics, data analytics and data science have considerable overlap. However, there is an important difference between the two: data science is far more focused on developing new techniques and tools to analyze big data sets, often through artificial intelligence and machine learning.

If data science appeals to you and you want to learn more, we have a variety of resources that can provide more information on:

Why take a course in data analytics?

Typically, you take a course in data analytics for one of three reasons: career advancement, career transition, or career exploration.

Career advancement

Data analytics courses can provide crucial training and assessment in data analytics skills for students looking to upskill in order to advance their careers and either perform their existing job better or land a new position.

Data analytics courses will generally teach and assess one, several, or all of the following skills:


Programming is a crucial skill if you want to manipulate data and perform advanced analyses, or create efficient data pipelines. Data analytics courses frequently teach students Structured Query Language (commonly SQL), which is used for database management. They will sometimes also teach Python, a general-purpose programming language used for more advanced analytics, including machine learning, and R, a programming language with specific application for statistics and data visualization.

Statistical analysis

Statistical analysis is at the heart of data analytics, the catalyst behind turning data into actionable insights. Data analytics courses vary in breadth and depth of their statistical analysis instruction, from fundamental statistics concepts to techniques like regression, optimization, to advanced predictive modeling.

Data management

Programming and statistical analysis skills aren’t useful if you can’t efficiently and effectively manage data along the data pipeline, from raw data collection, to storage, to preparation, to analysis. Some courses will also teach skills like data mining for big data sets. 

Data visualization

The insights data analysis produces aren’t nearly as valuable if they can’t be effectively communicated. For business intelligence operations, it’s also common practice to create data dashboards that can help stakeholders assess key performance indicators (KPIs) at a glance.  For this reason, many data analytics courses offer training in data visualization techniques and tools like Tableau.

Advanced skills

In addition to these skills, many data analytics courses also offer training in machine learning, and even deep learning — areas more often in the purview of data scientists.

Career transition

Data analytics courses also provide value to those without existing analytics experience who are looking to break into the field, with many providing comprehensive training that can launch an individual into an entry-level position, regardless of background. Potential titles for those transitioning careers with a data analytics course include: data analyst, business analyst, business intelligence analyst, and, in some cases, data scientist, all of which offer salaries well in excess of the US median annual wage in the US of $45,760.

Data analyst

A data analyst typically collects, prepares, and analyzes data to produce new learnings to support the operations of their company, which they communicate to internal and external stakeholders through compelling data visualizations. According to, in the US the average data analyst salary is $81,719.

Business analyst

A business analyst’s responsibilities overlap considerably with a data analyst’s — in fact, the two titles are sometimes basically synonymous. If there is a distinction, however, it’s in a business analyst’s focus. They will also collect, prepare, and analyze data to extract insights, but more often this will be in support of larger business goals such as reducing costs, driving revenues, or entering a new market. According to, in the US the average business analyst salary is $79,770.

Business intelligence analyst

A business intelligence analyst’s responsibilities are similar to those of a business analyst, but they generally focus on producing informational support and dashboards monitoring KPIs and market and industry performance. According to, in the US the average business intelligence analyst salary is $85,278.

Data scientist

As we noted above, there is overlap in the skillsets of data scientists and data analysts, and in some cases a graduate of a data analytics course is able to land a data scientist position, especially if they have existing computer science and advanced mathematics experience. Data scientists leverage this experience to devise, develop, and launch new approaches to data analysis. According to, in the US the average data scientist salary is $139,631. While it is possible to become a data scientist with a data analytics education, if your goal is to become a data scientist, we’d recommend you look into data science courses.

Career exploration

While most data analytics courses emphasize skill development, they are also valuable if you’re just looking to learn more about the field and potential career opportunities. Free massive open online courses (MOOCs) are a great low-risk way to explore data analytics and get a better idea of what a data analytics professional’s day-to-day might be.

Why should you take a data analytics course instead of pursuing a data analytics master’s degree?

For college graduates looking to advance or transition their careers in or into data analytics, another option is to enter one of an increasing number of data analytics master’s programs. Data analytics master’s are generally two-year programs that award an advanced degree upon their completion. Many of these programs are open to those without extensive background in data analytics, and holding one of these degrees can provide the holder with expanded career opportunities, especially for senior positions. So why pursue a data analytics course instead?

Compared to data analytics master’s, data analytics courses are typically shorter in duration, less expensive, and less time-intensive. They are also sometimes targeted towards one skill or capability. That makes them a great option for someone who is time-crunched, wants to make a career transition quickly, and lacks the savings or desire to go into debt to fund an expensive college education.

If the idea of earning a graduate degree in data analytics appeals to you, however — and there are many reasons it should — check out our data analytics master’s guide for more.

What are the different kinds of data analytics courses?

Data analytics courses have such a wide variety of use-cases in part because there are so many different kinds of them. Here, we will focus on the most common three data analytics courses: data analytics certification programs, data analytics bootcamps, and data analytics certificate programs.

Data Analytics Certification Programs

What are they?

Data analytics certifications are credentials received in exchange for passing an exam that communicate to potential employers that an individual is competent in a particular skill or professional capability. Data analytics certification exams are often the culmination of a course of study that provides instruction in that skill, though exam-takers usually also have the option of taking the exam without taking a course or preparing through self-paced materials. Often, software providers like Cloudera will offer certification programs for their data analytics software to allow analysts the opportunity to demonstrate their ability, to gain new users, and to increase market-share in the analytics market.

Who’re they for?

Certification programs are for those who want to demonstrate and advertise a particular skill to potential employers. Generally, these individuals already have some, or even significant, background in analytics.

How much do they cost?

Most certification providers only require exam-takers to pay for the exam, which usually costs several hundred dollars.

Data Analytics Bootcamps

What are they?

Data analytics bootcamps are months-long, intensive courses of study — many, but not all, online — geared towards helping learners land an entry-level data analytics job. In addition to a comprehensive data analytics curriculum and an independent capstone project, these bootcamps provide career services to help students craft their resumes, practice their interview skills, and ultimately receive a job offer. Some even offer a job guarantee or income share agreement that allows students to get a refund if they don’t find employment within a certain time-frame or only pay tuition once they’ve found a job. However, with these offers, it’s always important to read the small print to avoid disappointment.

Who’re they for?

Data analytics bootcamps are for those who want to transition into data analytics without paying for a costly and time-intensive degree program. While some bootcamps will stipulate that students enter with existing experience in programming or statistical analysis, many allow complete beginners to enroll.

How much do they cost?

The average bootcamp cost $11,727 in 2020. Students are often given the option of installment plans, financing, or income-share plans where they pay back a fraction of their income once they get a job. Some bootcamps also offer money-back job-guarantees. As we mentioned above, for all of these offers it’s important to always read the small print.

Data Analytics Certificate Programs

What are they?

Data analytics certificate programs are a broad category of courses that offer training in a particular data analytics skill, a set of skills, or even a comprehensive skillset. Upon completion of the course, students receive a certificate that they can display on their resumes and LinkedIn. Many certificate programs offer instruction in the same areas as bootcamps, with some even offering comprehensive data analytics curricula, but there are generally more opportunities for self-paced and asynchronous learning, often at a lower cost.

Who’re they for?

Data analytics certificate programs are great options for aspiring analytics professionals who want more flexibility in curriculum and modality than is possible in bootcamps or master’s programs. They are also great for those who wish to avoid the substantial expense of bootcamp or degree tuition. Finally, given the many free options, data analytics certificate programs are great for those who want to explore a data analytics career before committing significant time and money to the pursuit.

How much do they cost?

Data analytics certificate programs range in cost from free to several thousands of dollars, depending on the educational provider’s reputation, the modality, and the extent of the curriculum.

Our Picks for the Best Data Analytics Courses

What’s our approach?

Online, you can find countless sites purporting to rank the best data analytics courses. As we’ve shown above, however, there are not only many different reasons to take a data analytics course, but different kinds of courses that might suit learners to greater and lesser degrees. In our minds, a simple ranking that separates the “best” from the “rest” simply doesn’t do justice to this variation.

Accordingly, for our picks we’ve foregone ranking and focused instead on pointing our readers to great examples of the three kinds of courses — certifications, bootcamps, and certificates — that we’ve explored above. In doing so, we’ve focused on highlighting courses that can provide value for money — through reputation, length, modality, curriculum, career services, and credentials — to a variety of learners. Our hopes are that interested individuals will be able to find something that works for them.

Data Analytics Certifications

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Microsoft Certified: Power BI Data Analyst Associate

Microsoft’s Data Analyst Associate certification program is more narrow in scope than the other certifications we are highlighting, focusing on Microsoft’s Power BI software, but it covers many of the same skills — data preparation, data modeling, data visualization — as the other certifications on the list at a fraction of the cost. Students are able to access the curriculum for free and need to pay just $165 to take the certification exam. In general, this course would be best for someone who already has experience as a data analyst and is looking to explore new software.

Length: Self-paced

Modality: Self-paced, online

Prerequisites: None

Syllabus Highlights: “Getting started with Microsoft data analytics,” “Model data in Power BI,” “Visualize data in Power BI”

Reported Outcomes: None reported

Cost: $165 for certification exam

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Amazon’s AWS Certified Data Analytics

Amazon’s AWS Data Analytics certification offers those with experience and expertise in using Amazon Web Services for data analytics the opportunity to earn a credential attesting to this face. To earn the certification, students must pass an exam of multiple choice and multiple response questions. To prepare, Amazon provides a variety of free materials, including an exam guide, sample questions, a practice question set, and digital training with an AWS skill builder.

Length: Self-paced training, 180 minute exam

Modality: Online

Prerequisites: 5 years of analytics experience; 2 years of hands-on experience with AWS for analytics

Syllabus Highlights: N/A

Reported Outcomes: None

Cost: $300 for exam

Cloudera CDP

Cloudera’s CDP Data Analyst Certification

Cloudera’s CDP Data Analyst Certification offers exam-takers the opportunity to demonstrate their expertise in using Cloudera products such as Cloudera Data Visualization and Cloudera Machine Learning as well as SQL and Apache. Before taking the online, proctored exam, students have the opportunity to prepare through Cloudera Educational Services’ comprehensive suite of courses.

Length: Self-paced training, 120 minute exam

Modality: Online, proctored

Prerequisites: Knowledge of Salesforce, business intelligence tools, spreadsheets, and Python or R

Syllabus Highlights:  N/A

Reported Outcomes: None

Cost: $300 for exam

CAP INFORMS certificate

INFORMS’ Certified Analytics Professional Certification

While the previous certifications attest to ability in a certain software or suite of software, the Certified Analytics Professional certification (CAP) is an independent certification of one’s ability as a data analyst. For the exam, takers are required to hold a college degree and have a certain amount of experience in analytics. An Associate Certified Analytics Professional (aCAP) certification is available for those without a degree and the requisite experience. In the exam, analysts are tested in 7 areas: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. To prepare for the exam, students have the opportunity to use free resources, take a sample test, or take a CAP online prep course or bootcamp. Certifications are valid for three years.

Length: Self-paced training, 100 question exam

Modality: On site at a testing center or proctored online

Prerequisites: For CAP, college degree and 3-5 years of analytics experience; for aCAP, none

Syllabus Highlights: N/A

Reported Outcomes: None

Cost: $495 INFORMS member, $695 non-member

Data Analytics Bootcamps

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Columbia Engineering Data Analytics Bootcamp

Columbia Engineering’s Data Analytics Bootcamp offers courses in Excel, Python, databases, and machine learning, as well as a final project that students are able to collaborate on with their peers. Throughout the bootcamp, students have access to academic and career support, including a Career Engagement Network that helps students prepare their resumes and portfolios and practice interviewing.

Length: 24 weeks, part-time (9 hours of live classes per week, 20+ hours of homework per week)

Modality: Live, online

Prerequisites: None

Syllabus Highlights: “Excel crash course,” “Python data analytics,” “Machine learning and other advanced topics”

Reported Outcomes: None reported, though positive testimonials

Cost: $14,745

Georgetown University seal

Georgetown University’s Data Analytics Bootcamp

Georgetown’s Data Analytics Bootcamp offers students the opportunity to learn data analysis and data visualization and apply these skills in collaborative projects. Georgetown also offers a course in critical thinking and 1:1 career services to help students find job placement after the course.

Length: 12 weeks, Friday evenings and Saturdays

Modality: Live, online

Prerequisites: None

Syllabus Highlights: “Foundations of Data Analytics & Python Basics,” “Statistics,” “Data Analytics in Python & SQL,” “Data Visualization”

Reported Outcomes: None

Cost: $6,995


Berkeley Online Data Analytics Boot Camp

Cal Berkeley’s Data Analytics Boot Camp offers students the opportunity to practice skills like Excel, Python, API Interactions, and Machine Learning on projects focused around fields like finance, human resources, healthcare, and government. For those interested, Berkeley also offers a coding bootcamp.

Length: 24 weeks, with 9 hours of in-class time and 20+ hours of hands-on projects and practice work

Modality: Live, online

Prerequisites: None

Syllabus Highlights: “Excel Crash Course,” “Python Data Analytics,” “Web Visualization”

Reported Outcomes: None reported

Cost: $9,995

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CareerFoundry’s Data Analytics Program

CareerFoundry’s Data Analytics Program isn’t a bootcamp by name, but we’re including it in the list because it offers opportunities to work 1:1 with an expert mentor, meaning that students will have direct visibility on what it’s like to work as a data analyst. CareerFoundry also offers an impressive 180-day guarantee: either you get a job offer as a data analyst within 180 days after finishing the course or you get your money back.

Length: 5 months at 30-40 hours/week or up to 8 months at 15-20 hours/week

Modality: Self-paced, online with live 1:1 mentor sessions

Prerequisites: None

Syllabus Highlights: “Cleaning Your Data,” “Conducting a Descriptive Analysis,” “Storytelling with Data”

Reported Outcomes: CareerFoundry graduates have gone on to jobs at Amazon, Facebook, and Google

Cost: $6,210

Data Analytics Certificate Programs

google logo of the G

Google Data Analytics Certificate

Google’s Data Analytics Certificate aims to teach students job-ready skills to help them land an entry-level job with one of the 150 employers in an employer consortium that includes SiriusXM, Snapchat, Target, and Verizon. Students learn core data analytics skills over 7 courses focusing on topics like data cleansing, data analysis, data visualization, and R programming, before applying these skills through a hands-on capstone project.

Length: 6 months, under 10 hours of study per week

Modality: Self-paced, online

Prerequisites: None

Syllabus Highlights: “Ask Questions to Make Data-Driven Decisions,” “Analyze Data to Answer Questions,” “Share Data Through the Art of Visualization,” “Data Analysis with R Programming”

Reported Outcomes: 75% of graduates report career improvement

Cost: $39/month of attendance on Coursera

Cornell-University seal

Cornell’s Data Analytics Certificate Program

Cornell’s Data Analytics Certificate Program aims to give students who have a basic understanding of statistics a usable foundation in business analytics. Through three courses focused on data visualization, data-driven decision making, and predictive analytics, students learn to build dashboards that monitor key performance indicators (KPIs), develop incisive business questions, and create regression models that can predict the future.

Length: 9 weeks (3 3-week courses), 3-5 hours per week

Modality: Self-paced, online

Prerequisites: Statistics

Syllabus Highlights: “Understanding and Visualizing Data,” “Implementing Scientific Decision Making,” “Using Predictive Data Analysis”

Reported Outcomes: None reported

Cost: $2,625

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datacamp’s Data Analyst in SQL Career Track

datacamp’s data analyst course of study is a novel alternative to a bootcamp or university certificate program for a fraction of the cost. Students can take all or just several of 11 courses led by datacamp faculty and industry professionals and complete a final project. For just $25/month, students are also able to supplement this data analyst course with courses in Python, Tableau, and R.

Length: 39 hours of instruction

Modality: Self-paced, online

Prerequisites: None

Syllabus Highlights: “Introduction to Statistics,” “Intermediate SQL,” “Exploratory Data Analysis in SQL”

Reported Outcomes: None reported

Cost: $25/month, which includes access to other courses as well

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IBM’s Data Analyst Professional Certificate

IBM’s Data Analyst Professional Certificate, offered on Coursera with a 4.6/5 rating, offers another low-cost way for aspiring data analysts to build the skills necessary to land an entry-level position that is faster than Google’s certificate program. Students cover basic spreadsheet skills, database querying skills using SQL, and analysis skills using Python software libraries lily Python. Students also take two courses in data visualization before a culminating capstone project that students can use as the first entry in their data analytics portfolio.

Length: 4 months, under 10 hours/week

Modality: Self-paced, online

Prerequisites: None

Syllabus Highlights: “Excel Basics for Data Analysis,” “Databases and SQL for Data Science with Python,” “Data Visualization with Python” 

Reported Outcomes: 42% of certificate grads started a new career

Cost: $39/month of attendance on Coursera

What’s next?

In this guide, we’ve covered the basics of data analytics, gone over some of the reasons to take a data analytics course and the skills and professional opportunities they provide, looked at the different kinds of data analytics courses, and presented some of our favorite ones.

What’s next? If you see a course that interests you, we’d recommend clicking through to its website to learn more. If you’d like to learn more about data analytics and what a data analytics career can look like, we’d recommend checking out the following guides and articles: