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9 Data Science Certificates Worth Investing in for 2023

16 minute read | November 19, 2023
Maria Muntean

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Maria Muntean


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Data science is an increasingly attractive field, with a 28% rise in demand for data scientists over the last five years. A testament to the field’s importance is the rise of data science certifications, which serve as recognized proof of a data scientist’s skills and knowledge. Data scientists are in high demand and a senior data scientist can expect to earn well over $200,000 per year, according to Glassdoor. As a distinguished certified data scientist, even more doors will open for you, especially if your data science skills experience is backed by one of the best data science certifications on the market.

Many of the top data science certifications are very accessible, whether you are at the start of your data science journey, or are backed by a Bachelor’s Degree or Master’s Degree in Computer Science or Applied Data Science. You can choose to specialize by becoming a Open Certified Data Scientist (CDS), Senior Data Scientist (SDS), Microsoft Certified Azure Data Scientist, American DASCA Senior Data Scientist, Certified Analytics Professional (CAP) or more. These data science certifications prove that you are adept at managing deep learning and machine learning workloads, that you can gain insights through data exploration, understand data mining across multiple data points and data pipelines , know SAS programming basics, the R programming language, and have the technical skills to tackle real world business problems.

However, as the number of available data science certifications grows, so does the importance of selecting a data science certification that enhances your current skill set and provides long-term value for your career.

This article will help you make a data-driven decision, outlining the best data science certifications worth investing in for 2023. Each data science certificate program offers a unique blend of knowledge and practical experience to improve your competency and marketability in the data science job market. Let’s get you one step closer to your career as a data scientist!

What Does a Data Scientist Do?

A data scientist is a data analysis professional who uses data to solve problems and make predictions. They use their applied data science skills, including statistics, data visualization, mathematics, programming, data manipulation, predictive modeling, natural language processing and machine learning, to extract insights from data that would otherwise be hidden. Most data scientists hold a bachelor’s degree or master’s degree in Computer Science, but it is possible to enter the field without completing a formal education, and a bachelor’s or master’s degree isn’t strictly required if you have experience. Many potential employers will take this into account when they hire data professionals.

A certified data scientist can perform a number of daily tasks:

  • A data scientist gathers data: This involves collecting data from a variety of sources, such as surveys, customer transactions, and social media, using a proven data science methodology.
  • A data scientist has to clean and prepare data: This involves removing errors and inconsistencies from the data. This is an important step, as it can affect the accuracy of the data analysis.
  • A data scientist has to analyze data: Data analytics involves using statistical techniques to identify patterns and relationships in the data. Exploratory data analysis can be done using a variety of methods, such as regression analysis, clustering, and machine learning. Data analytics is one of the most important data science skills you’ll need to learn before working in the field.
  • A data analyst has to present data. Data visualization is an important task that all data science professionals have to familiarize themselves with. They may also use predictive modeling to create forecasts.
  • Data scientists build models: This involves using the insights from the statistical analysis to build models that can be used to make predictions. They may use the R programming language.
  • A data scientist has to present and communicate results: This involves communicating the results of the data analysis to stakeholders in a clear and concise way. As a senior data scientist, you have to be prepared to present your data management processing analysis to important stakeholders.
  • A data scientist will deploy models: This involves deploying the data analytics models into production so that they can be used to make predictions on a regular basis (predictive modeling). You may work on a number of important data science projects as a data engineer.

Data scientists are in high demand in a variety of industries, including business, finance, healthcare, and government, or any field where big data is generated. The job outlook for data scientists is very positive, with the Bureau of Labor Statistics projecting that employment of data scientists will grow 22% from 2020 to 2030, much faster than the average for all occupations or the field of data analytics. You can learn the necessary data science skills and become a certified data scientist by completing a number of data science courses, online or in-person. Choose your data science specialization carefully – the possibilities are endless for data science professionals, and there are a number of data science certificate programs to choose from.

Are Data Science Certifications Worth It?

Whether or not a data science certificate is worth it depends on your career goals and current knowledge. The best data science certifications often act as catalysts for most people, propelling novices to a competent professional level. AI and the use of natural language processing is fairly new but in high demand; experience will trump even the best data science certifications. It can be beneficial to gain experience, validate existing knowledge, and stand out in the job market. However, even the best data science certification is not a magic bullet. Practical experience in the data science field and continual learning are also essential, so look for certificates encouraging that. Some companies may also insist on a formal education, like a bachelor’s degree or a master’s degree.

You have to consider the area you’d like to specialize in, e.g. becoming a Certified Analytics Professional (CAP) or Senior Data Scientist (SDS). You can pick up a few basic skills and gain a basic understanding through self-study, but the learning process will be much quicker and easier if you complete a course or bootcamp. You can attend free or affordable bootcamps online. Sites like Coursera offer courses by prestigious colleges like Harvard University – at a fraction of the price it would cost to attend Harvard University, of course.

Data Science Certificate vs. Data Science Certification vs. Data Science Course

Understanding the differences between a certificate, certification, and course is paramount, especially since there are so many data science certificates and programs to choose from. Do you want to become a Master Certified Data Scientist? A Certified Analytics Professional? Do you need a bachelor’s degree or master’s degree before attempting the certification? And which are the best data science certifications to choose if you want to work in statistical analysis or data engineering?

A course refers to a series of lessons or lectures on a particular subject, often forming part of a more extensive program of study.

A certificate, on the other hand, is awarded after completing such a course, indicating that a learner has acquired specific knowledge or skills.

Unlike a certificate, a certification or data science program typically involves passing a rigorous examination process. It’s an official document proving an individual’s competence in a specific data science area, enhancing credibility and job prospects.

Of course, many data science professionals choose not to pursue a formal program at all and prefer to gain practical experience instead.

Data Science Certifications Worth Pursuing

This section will explore the data science certifications that are worth your time and resources, and outline their unique benefits.

IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate is an ideal program if you are just starting in the data science field and you’re looking to kickstart your career. This certification demonstrates a candidate’s ability to solve real-world problems using data science methodologies and statistics.

It requires learners to master essential tools such as Jupyter Notebooks, SQL, Python, predictive modeling, natural language processing, and data visualization and analysis libraries. The program also involves constructing and evaluating machine learning models using Scikit-learn and SciPy, applying these techniques to real location datasets.

The certificate is earned after completing all courses within the IBM Data Science Professional Certificate program on Coursera.




The IBM Data Science Professional Certificate is a beginner-level program that doesn’t require any prior experience. The program comprises ten courses that can be completed in approximately five months, assuming a commitment of 10 hours per week.

To provide participants with practical expertise, this certificate course focuses on developing skills with the tools, programming languages, and libraries commonly used by professional data scientists. Key topics include data analysis, data visualization, machine learning, and big data.

Much of the program emphasizes applied learning, with hands-on labs conducted in the IBM Cloud using real-world data sets. This practical experience equips learners with job-ready skills and helps them build a portfolio of data science projects, demonstrating their proficiency to potential employers.

It’s important to note that this program suits anyone interested in data science or machine learning, regardless of their academic background. The only prerequisite is a passion for learning and a readiness to develop new skills.

Microsoft Certified: Azure Data Scientist Associate

The Microsoft Certified: Azure Data Scientist Associate certification is geared towards data scientists and professionals who work with data science and machine learning projects on the Azure platform.

The certificate validates your knowledge and experience using Azure Machine Learning and MLflow for data science tasks.


The Azure Data Scientist Associate certification exam costs around $165 USD. However, the exact price is based on the country or region in which the exam is proctored. Becoming Microsoft Certified can be a real career booster.


The Azure Data Scientist Associate certification requires you to pass a final test, Exam DP-100: Designing and Implementing a Data Science Solution on Azure. This exam measures your ability to design and prepare a machine-learning solution and train and deploy models.

Microsoft provides several learning paths to help you prepare for the exam. These include exploring the Azure Machine Learning workspace, working with data in Azure Machine Learning, or automating machine learning model selection with Azure Machine Learning. Each of these learning paths contains modules of varying lengths.

Moreover, Microsoft allows for the renewal of your Microsoft Certification for free. This can be achieved by learning the latest updates to the technology for your job role and passing an online assessment on Microsoft Learn.

Google Professional Data Engineer

The Professional Data Engineer exam assesses your abilities in designing data processing systems, operationalizing machine learning models, ensuring solution quality, and building and operationalizing data processing systems.

It’s designed for data scientists who focus on designing and monitoring data processing systems, emphasizing security and compliance.


The Google Professional Data Engineer certification exam registration fee is $200.


The Google Professional Data Engineer certification exam is a 2-hour test with 50-60 multiple-choice questions. The exam can be taken online or onsite.

There are no prerequisites to take this certification exam. However, Google recommends candidates have at least three years of industry experience, including one year of experience with Google Cloud. Google provides several resources to help candidates prepare for the exam, including online training or in-person classes.

SAS Certified Data Scientist

The SAS Certified Data Scientist certification is an advanced certification for individuals who want to evince their ability to use open-source tools and SAS Data Management to manipulate big data. This certification is ideal for those aspiring to gain big data insights and make business recommendations using complex machine learning models. Becoming a SAS certified data scientist can give a real edge in your career.


The cost of the SAS Certified Data Scientist certification exams varies depending on the specific exam.

The Associate Exams are priced at $120 each. If you’re taking the Predictive Modeler exam, the cost is $250. All other exams cost $180 each.


The SAS Certified Data Scientist certification involves the completion of three different credentials, meaning candidates must pass three exams: the Data Curation Professional exam, the Advanced Analytics Professional exam, and the AI & Machine Learning Professional exam.

As a part of the certification journey, candidates are encouraged to take advantage of SAS Academics, which offers in-depth training and certifications. Academic discounts are also available for students and educators.

Databricks Certified Associate Developer for Apache Spark

The Databricks Certified Associate Developer for Apache Spark certification evaluates a candidate’s understanding and application of the Spark DataFrame API for basic data manipulation tasks within a Spark session. This certification is primarily geared towards individuals involved in data engineering or analysis and seeking to improve their skills in Apache Spark, a popular open-source distributed computing system for big data processing and analytics.

Candidates earning this certification are expected to demonstrate competence in using Python or Scala.


The cost of attempting the Databricks Certified Associate Developer for Apache Spark certification exam is $200. This price is applicable per attempt, meaning that if a candidate has to retake the exam, each attempt costs an additional $200.


Candidates are given 120 minutes to complete the certification exam with 60 multiple-choice questions. The questions are distributed across three high-level topics.

While not mandatory, it’s recommended that candidates complete the Apache Spark Programming with Databricks course, available with either instructor-led or self-paced options through the Databricks Academy.

Amazon Web Services (AWS) Certified Machine Learning

The AWS Certified Machine Learning credential is a certification program from Amazon Web Services intended for individuals in development or data science. It is intended for professionals with over a year of experience developing, architecting, or running machine learning workloads in the AWS Cloud.


The AWS Certified Machine Learning – Specialty exam (MLS-C01) costs $300.


Candidates are given 180 minutes to complete the exam. The exam consists of 65 multiple-choice or multiple-response questions. The exam is delivered via a Pearson VUE testing center or can be taken as an online proctored exam.

AWS provides various resources to help candidates prepare, including but not limited to exam guides and sample questions. It’s recommended that candidates leverage these resources to build the necessary knowledge and skills to excel in the exam.

Data Science Council of America (DASCA) Senior Data Scientist

The Data Science Council of America (DASCA) offers a Senior Data Scientist (SDS) Certificate recognized globally as a high-quality, vendor-neutral, cross-platform qualification. The SDS is designed for experienced big data analysts and technology professionals who aspire to display their advanced data leadership potential and stay at the forefront of data science.

This certification is best suited for technology professionals with at least four years of exposure to research and analytics who are interested in advancing to data scientist roles within large organizations. It aims to accelerate their journey toward becoming data leaders, data architects, and intelligence experts.


The total cost for the SDS certification program is $775. This is an all-inclusive, one-time fee covering the certification exam, preparation resources, a digital badge, and the shipping of materials. The price also includes the digital access and hosting cost of 3rd-party optional study resources. DASCA also offers special fee considerations for military and war veterans.


Applicants for the SDS program should have a sound understanding of the latest technology and data science trends and their intersections with other streams of computer science, business, and industry. Depending on the candidate’s educational qualifications, the minimum experience required varies from 3 to 5 years in data sciences, computing, business analytics, or other field.

Candidates are granted a 6-month timeframe to prepare for the SDS exam with a recommended self-study schedule of 8-10 hours per week. The exam is held online and can be taken at any time and location, with digital proctoring for integrity.

Data Science Council of America (DASCA) Principal Data Scientist

Compared to the Senior Data Scientist certification above, the Principal Data Scientist certificate is designed for seasoned professionals in the data science and analytics fields who have significant experience in data analytics and intelligence.

Ideal candidates have demonstrated their ability to transform data and business intelligence infrastructures within organizations and have a track record of managing and architecting enterprise-wide business intelligence systems. These individuals are seen as thought leaders, idea generators, and technology pioneers in the data science community.


The cost of acquiring the PDS™ certification depends on the applicant’s track. Here are the current pricing options as of 2023:

  • For invite-only applicants (Track 1), the fee is $850.
  • Via Corporate Nomination (Track 2), the fee is $1250.
  • The fee for those upgrading from SDS™ (Track 3) is $750.
  • For Open Applications (Track 4), the fee is $1450.


The PDS™ program provides a thorough structure, offering flexibility in its completion timeline. Candidates are given a full year from the date of registration confirmation to pass the exam and complete the assessment requirements. For preparation, candidates generally should study for 8-10 hours per week.

The program involves a multi-stage process that includes completion of registration formalities, preparation for the exam using the provided learning resources, and completing four assessment milestones.

Holders must update their professional achievements on their myDASCA dashboard once every five years.

Open Certified Data Scientist (Open CDS)

The Open CDS certification is designed to be a vendor-neutral, peer-reviewed certification, and is for individuals who integrate statistical and data analysis techniques to solve various business problems. Its requirements allow it to serve as an objective measure of a data scientist’s capabilities, making it highly valued by world-leading enterprises when assessing the skills of potential and current employees.


The pricing details for Open CDS are not publicly available on the certification’s website.


The Open CDS certification process is unique because it doesn’t involve attending specific training courses or passing written exams. Instead, applicants must demonstrate their skills and experience against a set of requirements. This demonstration is achieved by submitting written applications and undergoing peer interviews.

This experience-based approach emphasizes practical skills and on-the-job experience. It distinguishes the Open CDS from many other certifications, mainly focusing on theoretical knowledge or passing a particular exam. This certification process is developed from the IT sector’s requirements, ensuring it is closely aligned with the skills and knowledge data science professionals need in the real world.

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Where To Start When Considering Certifications

When considering certifications in data science, it’s essential to consider where you’re starting from and your ultimate career goals.

For instance, if you’re just beginning to explore the field or looking to solidify your foundational skills in data science, you might not need to jump into an official certification right away. In this case, enrolling in a comprehensive data science course, such as Springboard’s Data Science Bootcamp, can be a strategic and efficient way to start. Springboard offers students both a certificate upon completion and the foundational skills that are needed to launch a career in data science.

Springboard’s Data Science Bootcamp is designed to equip you with a solid understanding of the core concepts, techniques, and tools used in data science. You’ll learn through hands-on data science projects and get support from industry professionals and a community of peers. This holistic approach ensures that you don’t just learn the theory but also understand how to apply your knowledge in practical situations. Although this is not an official certification per se, it serves as a stepping stone for further specializations and certifications.

For those who aspire to progress into specific roles such as a data analyst, data engineer, Certified Analytics Professional, or even a data science manager, obtaining a data science certification can give you an edge. Many organizations in tech, healthcare, finance, and other industries value such credentials as they validate your proficiency in certain areas. More than that, some jobs might require data science certifications as a prerequisite. In such cases, having a certificate from an organization like the Data Science Council of America can be advantageous.

What To Look For in a Data Science Certification

There are several factors to consider when evaluating the best data science certifications. Let’s explore them below.

Course Reputation

A well-regarded course often has a track record of success, is endorsed by industry professionals, and is recognized by hiring managers. Look for data science courses with positive reviews, strong alumni networks, and a curriculum designed by industry experts.

Course Support

The quality of support provided throughout the course is another essential factor. This can include resources like textbooks, lectures, and access to software and tools. However, support should also encompass access to instructors or tutors, community forums, and mentorship opportunities.

The best courses offer individual mentorship and career coaching, giving you direct access to industry professionals who can guide you, answer your questions, and provide personalized feedback.

Future Job Needs

Before choosing a certification, consider whether it aligns with your career goals and the demands of the job market. Ensure the certification covers the required skills and tools in your desired industry.

Review job descriptions for roles you’re interested in, and see if the certification program covers those areas. Some roles may also require specific certifications.

Earning Power

Finally, consider the earning potential associated with the certification. While it’s not the only factor to consider, a certificate that increases earning power is often a good investment. This doesn’t just refer to higher salaries but also to the potential for career advancement.

Certifications that are recognized and respected in the industry can make you more hirable and open up opportunities for promotions and leadership roles. Research and compare the average salaries of professionals with and without a given certification to understand its potential return on investment.

FAQs About Data Science Certification

We’ve got the answers to your most frequently asked questions.

Are Data Science Certifications Expensive?

The cost of data science certifications can vary widely depending on the institution offering them, the breadth and depth of the curriculum, and the resources provided.
Some online courses may cost a few hundred dollars, while more comprehensive programs, particularly those affiliated with universities, might cost several thousand dollars.

It’s crucial to consider not just the cost but also the course’s value.

Will a Certification in Data Science Help You Get a Job?

A certification can significantly improve your employability, as it provides evidence of your skills and knowledge. Many hiring managers and recruiters look for certifications on resumes to filter candidates. It shows that you have undergone rigorous training and met the standards set by the certification body. The pool of Big Data is growing, and many companies want to hire data professionals with data wrangling and analytical skills to manage and use all that data. Data science certifications can prove that you have the necessary skills in advanced analytics to do the job.

How Many Data Science Certifications Do You Need?

The number of data science certifications you need will depend on your career goals and the specific requirements of the roles you’re interested in.

If you’re just starting in data science, a single comprehensive program that provides strong foundational knowledge can be sufficient. If you already have a master’s degree, you might not need a certification at all.

As you advance in your career, you may pursue additional certifications in more specialized areas to demonstrate your expertise and commitment to continuous learning.

What Is the Data Science Council of America? (DASCA)

The Data Science Council of America (DASCA) is a worldwide leader in data analytics accreditation and certification. It is an independent, vendor-neutral organization that offers a variety of certifications for data analysts, data engineers, data scientists, and other data science professionals.

About Maria Muntean

Maria-Cristina is a content marketer with 7 years of experience in SEO and content strategy for SaaS and technology brands. She holds an MA thesis on the effects of emotions in written and video content. She loves to spend time near the ocean and watch horror movies.