Big data is becoming increasingly prevalent among companies of all sizes. There is a huge need for data scientists who use tools to create the processes and algorithms that make it possible for data analysts to make sense of all that data. 

To become a data scientist, or to get any job in data science, it is a good idea to get a data science certification. A certification (or certificate) will provide you with the necessary knowledge and skills to succeed as a data scientist. 

Data scientists are among the top three jobs in America, according to Glassdoor [1]. The World Economic Forum’s 2025 Future of Jobs Report lists data analysts and scientists among the top 11 for increasing demand across industries [2].

Read on to learn whether a data science certification is worth it, how to choose one, and a few programs to choose from.

professional certificate

IBM Data Science

Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.

4.6

(78,595 ratings)

709,523 already enrolled

Beginner level

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Average time: 4 month(s)

Learn at your own pace

Skills you'll build:

Generative AI, Data Science, Model Selection, Data Analysis, Python Programming, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), SQL, Jupyter notebooks, Machine Learning, Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Methodology, Data Mining, Github, Jupyter Notebook, K-Means Clustering, Data Science Methodology, Rstudio, Big Data, Deep Learning, Quering Databases, Data Generation, Career Development, Interviewing Skills, Job Preparation, Resume Building

What is a data science certification?

Certifications and certificates are not the same, though they sound similar. Certificates, such as IBM’s Data Science Professional Certificate, serve as learning material and proof that an individual has completed a training or educational course. Certifications, such as those obtained through DASCA, are globally recognized credential programs that involve taking and passing a standardized exam. 

Further, data science differs from data analytics in that data analysts make sense of existing data, while data scientists develop new processes and systems to capture and organize the data for analysts. Data science certificates provide learners with distinct skills such as Python and SQL, data analysis, data visualization, and the ability to build machine learning models.

specialization

Business Analytics

Data-driven decision making potential unlocked. Learners will be able to obtain, manage, analyze and visualize data to gain a competitive advantage in the world of strategic business decision making.

4.7

(215 ratings)

19,570 already enrolled

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Average time: 2 month(s)

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Skills you'll build:

Data Analysis, Analytics, Machine Learning, Rstudio, power bi, robotic process automation, Accounting Analytics, Natural Language Processing, Business Analytics, R Programming, regression, Marketing, Marketing Analytics, Health Care, prediction, classification, clustering, Analytic Mindset, Data Cleansing and Exploration, Alteryx, R and RStudio, PowerBI

What credentials do you need to be a data scientist?

You might be wondering whether certification is necessary to get a job in data science. The truth is that if you’re looking for a credential to add to your resume, then a Professional Certificate is not necessarily going to land you that coveted job. But what you do need are the skills often gained by completing a certification program.

Data scientists need to know statistical analysis and computing, machine learning, data analysis, data visualization, mathematics, and programming. On top of that, they are more likely to be hired if they are familiar with the tools and libraries a data scientist uses on a daily basis. 

Certificates can help you learn these skills in a comprehensive, logical fashion. 

In job interviews, you’ll be asked questions that test your skills and how well you are able to communicate how you would solve problems or build predictive analytics models. 

According to Zippia, 51 percent of data scientists hold a bachelor’s degree, and 34 percent hold a master’s degree [3]. Increasingly, especially in the technology industry, it is possible to jump into a data scientist role with enough hands-on experience and skills, even if you don’t have a formal degree.

What is the best certification for data science: How to decide 

Once you’ve determined that pursuing a data science certification is right for you, here’s how to find the right one.

You’ll want to consider things like:

• Skills learned: What skills will I learn? Does this program consist of more hands-on applied learning, or is it more theoretical? Are these skills aligned to a specific career pathway, industry, or tool?

• Cost: How much does it cost? Is it worth it for me at this point in my career? 

• Qualifications or requirements: What do I need to enroll in this program? Do I need a bachelor’s degree?

• Time: How long is the program? Is it flexible? Is it online or in person?

• Reviews: What do people rate the program? What is the overall score? Do reviewers think the certification is worthwhile?

These questions should help guide your search for the data science certification that aligns with your career goals.

4 top data science certificate programs from Coursera

These are a few of the top-rated data science certificate programs that Coursera offers. 

1. IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate is a flexible online course that prepares those with no prior experience for entry-level data scientist positions. Through 10 courses that take approximately 11 months to complete, learners develop an understanding of data science methodology as well as skills through hands-on projects like predicting housing prices, random album generator, and best classifier model. According to survey results, 28 percent of learners started a new career after completing this specialization.

Requirements: There is no prior experience, knowledge, or training required.

Cost: The course costs $59 per month by subscription on Coursera.

The IBM Data Science Professional Certificate gave me a lot of confidence. I never saw myself as a computer person, but the program has you do all these complicated-seeming things like working in the Cloud and connecting to APIs, and it was so cool to me to see how easy Watson Studio actually was to use and how much you could do on it.

— Sam B.

professional certificate

IBM Data Science

Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.

4.6

(78,595 ratings)

709,523 already enrolled

Beginner level

Learn More

Average time: 4 month(s)

Learn at your own pace

Skills you'll build:

Generative AI, Data Science, Model Selection, Data Analysis, Python Programming, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), SQL, Jupyter notebooks, Machine Learning, Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Methodology, Data Mining, Github, Jupyter Notebook, K-Means Clustering, Data Science Methodology, Rstudio, Big Data, Deep Learning, Quering Databases, Data Generation, Career Development, Interviewing Skills, Job Preparation, Resume Building

2. From Data to Insights with Google Cloud Specialization

Google Cloud’s specialization, From Data to Insights with Google Cloud, is a flexible, accelerated online course that teaches learners how to derive insights through data analysis and visualization, specifically with Google Cloud. The program consists of four courses that cover data loading, querying, schema modeling, optimizing performance, and query pricing. It can be completed in five months or less.

Requirements: There is no prior experience, knowledge, or training required.

Cost: The course costs $59 per month by subscription on Coursera.

specialization

From Data to Insights with Google Cloud

Learn Data Analysis that Scales. Learn how to query and process petabytes of data in seconds

4.7

(4,048 ratings)

48,449 already enrolled

Beginner level

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Average time: 1 month(s)

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Skills you'll build:

Bigquery, Machine Learning, SQL, Data Visualization, Google Cloud Platform, Cloud Computing

3. Google Data Analytics Professional Certificate

Google’s Data Analytics Professional Certificate is a flexible online course that prepares learners for entry-level data analytics positions. These roles are needed in industries as wide ranging as technology, retail, banking, agriculture, and government. Through eight courses that take approximately six months to complete, students gain an understanding of the practices and processes a junior or associate data analyst needs to know.

Requirements: There is no prior experience, knowledge, or training required.

Cost: The course costs $59 per month by subscription on Coursera.

professional certificate

Google Data Analytics

Get on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.

4.8

(153,263 ratings)

2,650,136 already enrolled

Beginner level

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Average time: 6 month(s)

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Skills you'll build:

Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, Data Calculations, R Markdown, R Programming, Rstudio, Tableau Software, Presentation, Data Integrity, Sample Size Determination, Decision-Making, Problem Solving, Questioning

4. IBM Introduction to Data Science Specialization

IBM’s Introduction to Data Science Specialization is a shorter, beginner-friendly version of the Data Science Professional Certificate. It omits the courses that dive into data analysis, data visualization, and machine learning with Python but covers the tools, methodology, and SQL knowledge. If you’re looking specifically for the basics, this can be a good option.

Requirements: There is no prior experience, knowledge, or training required.

Cost: The course costs $59 per month by subscription on Coursera.

specialization

Introduction to Data Science

Launch your career in data science. Gain foundational data science skills to prepare for a career or further advanced learning in data science.

4.7

(13,055 ratings)

94,694 already enrolled

Beginner level

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Average time: 1 month(s)

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Skills you'll build:

Data Science, Python Programming, Cloud Databases, SQL, Relational Database Management System (RDBMS), Big Data, Machine Learning, Deep Learning, Data Mining, Data Analysis, CRISP-DM, Methodology, Jupyter notebooks, Github, Rstudio

Are data science certifications worth it?

Data science certifications can be a good investment for your data science career, a growing field projected to have a job outlook of 36 percent growth over the next decade. For context, the average growth across all jobs in the United States is 4 percent, demonstrating the potential for career opportunities in data science [4]. With a subscription cost of $49 a month, the data science certification programs you can find on Coursera are often a more affordable option than traditional degree programs to help you learn a targeted set of skills. 

Prepare for the best data science certifications on Coursera 

Start learning data science today with a free trial. IBM’s Data Science Professional Certificate strongly emphasizes applied learning—so you’ll be able to add Jupyter, GitHub, R Studio, and Watson Studio into your data scientist toolkit. 

professional certificate

IBM Data Science

Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.

4.6

(78,595 ratings)

709,523 already enrolled

Beginner level

Learn More

Average time: 4 month(s)

Learn at your own pace

Skills you'll build:

Generative AI, Data Science, Model Selection, Data Analysis, Python Programming, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), SQL, Jupyter notebooks, Machine Learning, Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Methodology, Data Mining, Github, Jupyter Notebook, K-Means Clustering, Data Science Methodology, Rstudio, Big Data, Deep Learning, Quering Databases, Data Generation, Career Development, Interviewing Skills, Job Preparation, Resume Building