The data science industry has drastically transformed in the last decade. For those who graduated with a degree in mathematics, data science was a golden ticket. However, times have changed. Switching to a data science career with just a degree in mathematics won’t suffice. Modern businesses require modern techniques and technologies to get the work done.
We live in a world driven by big data. However, this large amount of data requires experts who can convert it into actionable insights. Thus, the role of a “data scientist” is fundamental for all business aspects. Professionals skilled in mathematics, statistics, programming and data visualization tools are key to a data science career. Adding a professional certification and a portfolio of projects to your resume won’t hurt either.
Recruiters pay attention to candidates who can demonstrate their skills and know how to do so. The ideal pathway is to earn a certification along with a portfolio of projects.
With multiple online certifications available, selecting the ideal certification program can be challenging. This article lists ten reputable data science certifications.
Top 10 Data Science Certifications for 2025
1. Data Scientist Nanodegree Program
The data scientist nanodegree program by Udacity is ideal for professionals seeking hands-on experience in running data pipelines, building recommendation systems and designing experiments. The nanodegree program is an advanced course and requires three months to complete.
Skills You’ll Learn:
- Introduction to Data Science – Predictive Analytics, AI Algorithms, Statistical Modelling, Github Portfolios, Exploratory Data Analysis, CRISP-DM
- Software and Data Engineering – Magic Methods, Pip, Flask, Unit Testing, Code Reviews, Bootstrap, Scikit Learning, Machine Learning Pipeline Creation, Entity Recognition, Sentiment Analysis, Feature Extraction, Data Pre-processing, Tokenization
- Experimental Design and Recommendations – Matrix Factorization, Latent Variables, Experiment Design, Experiment Control, Recommendation Engine Fluency
Prerequisites:
- Basic SQL
- Data Wrangling
- Pandas
- Git
- JSON
- NumPy
- Data Visualization
- Basic Python
- Linear Algebra
- Relational Database Basics
- Python Data Analysis Libraries
- Python for Data Science
- Basic Statistical Modeling
What You’ll Get:
- Work on real-world projects
- Program certificates
- Unlimited access to their top-rated courses
- Personalized project reviews
2. IBM Data Science Professional Certificate
If you’re a beginner seeking a career in data science, then this professional certification course offered by Coursera is ideal for you. It is a 12-course series program and is beginner-friendly. The course is self-paced, however, it may take around three months to complete the program.
Skills You’ll Learn:
- Master up-to-date practical skills and data science knowledge
- Get hands-on experience with the tools, languages and libraries used by industry professionals, such as Python and SQL
- Import and clean data sets
- Analyze and visualize data
- Build machine learning models and data pipelines
- Apply data science skills to real-world projects
Prerequisites:
- Open to everyone with credible work and academic background
- No prior computer programming experience
- Statistics, calculus and linear algebra knowledge are helpful but not an absolute requirement
What You’ll Get:
- Demonstrate technical skills
- Obtain professional-level certification
- Earn an employer-recognized certificate from IBM
3. Professional Certificate in Data Science: Harvard University
The HarvardX data science program prepares you to jumpstart a career in data science along with real-world projects. The difficulty level is intermediate, hence, ideal for beginners. Hosted on edX, the professional certification course prepares you to tackle data analysis challenges. This program includes topics like data wrangling, R programming, data visualization and more.
Skills You’ll Learn:
- Implementing machine learning algorithms
- R programming skills
- Gain practical experience in data visualization tools using ggplot2
- Obtain practical skills in tools like Git and Github, Unix, Linux and RStudio
Prerequisites:
No prerequisites for the first course. However, later courses may require knowledge available in the series. You may check the courses mentioned in the program to get specific details.
What You’ll Get:
- Premier certificate
4. Microsoft Certified: Azure Data Scientist Associate
The Microsoft Certified Azure Data Scientist Associate program by Microsoft is an intermediate course applicable for subject matter experts in the field of data science and machine learning. These candidates must have experience in implementing and running machine learning workloads on Azure.
Skills You’ll Learn:
- Data exploration
- How to train machine learning models
- Implementing data pipelines
- How to design and create a suitable work environment for data science workloads
- How to manage, deploy and monitor scalable machine learning solutions
Prerequisites:
- Knowledge and experience in data science using MLflow and Azure machine learning
What You’ll Get:
- The professional credentials do not have an expiration date
5. SAS Certified Data Scientist
The SAS-certified data scientist program from SAS offers four professional-level credentials.
- Data Curation Professional
- Advanced Programming Professional
- Advanced Analytics Professional
- AI and Machine Learning Professional
Earning a single credential may help land a career in data science, but earning all four credentials can transform your career in the field.
Skills You’ll Learn:
- Obtain a solid understanding of data management
- Hadoop and big data concepts
- Advanced programming techniques
- How to process data using SQL
- How to use the SAS macro facility
- Advanced analytics technologies – machine learning and predictive modeling
- Analytical approach toward solving business problems
- Understanding the analytical life cycle
Prerequisites:
- At least six months of programming experience in SAS or another programming language
What You’ll Get:
- The professional credentials do not have an expiration date
6. Open Certified Data Scientist (Open CDS)
The Open Group Open Certified Data Scientist (Open CDS) certification offers a comprehensive certification program for aspiring data scientists. The open CDS offers three-level certifications:
- Certified Data Scientist
- Master Certified Data Scientist
- Distinguished Certified Data Scientist
This certification program doesn’t require undergoing online training or exams. Professionals applying for the certification must complete the experience application form and attend a board review to get through the program.
Prerequisites:
- Candidates with capstone-type projects
What You’ll Get:
- Industry-recognized certification
7. IBM’s Introduction to Data Science Specialization
IBM’s data science specialization course is a beginner-level program and requires one month to complete. It is self-paced, flexible and ideal for candidates seeking to launch a data science career.
This certification program is a four-course series that provides key foundational skills required by data scientists.
- What is Data Science
- Tools for Data Science
- Data Science Methodology
- Databases and SQL
Skills You’ll Learn:
- Write SQL statements
- Data science and machine learning applications and use cases
- Hands-on skills – JupyterLab, GitHub, Watson and R Studio
- Hands-on labs and assignments
Prerequisites:
- No prior experience is required
What You’ll Get:
- Shareable certificate
8. Certified Analytics Professional (CAP)
CAP is a vendor and technology-neutral certification by INFORMS ideal for experienced professionals in the following areas.
- Two years of analytics experience with an MA or MS degree or higher
- Four years of analytics experience with a BA or BS degree
- Eight years of analytics experience with any level of education
Skills You’ll Learn:
- Skills to evaluate data science tasks
- Formulate methodical approach
- Communicate actionable analysis
Prerequisites:
Details are mentioned in the above description.
What You’ll Get:
- Professional certification is valid for three years from the time it is issued.
9. University of Colorado Boulder’s Data Science Graduate Certificate
The data science graduate certificate from Boulder offers 12 credits from the time the candidate enrolls for the program. This certification program takes approximately 6 to 9 months to complete. However, candidates enrolled in this program must also complete the following specializations.
- Data mining foundations and practice specialization (3 credits)
- Statistical inference specialization (3 credits)
From the following, users must select at least two specializations.
- Introduction to statistical learning for data science specialization (3 credits)
- Statistical modeling (3 credits)
- Machine learning specialization (3 credits)
Skills You’ll Learn:
- Probability theory
- AI and machine learning
- Big data analytics
- Statistical modeling
- Python and R programming
- Calculus and linear algebra
- Unstructured data
- Data visualization
Prerequisites:
- No prior requisites, however, knowing math and R and Python programming.
What You’ll Get:
The certificate is stackable, and interested candidates can apply these credits toward pursuing a Master’s in data science.
10. Online Certificate in Data Science: Georgetown University
Georgetown’s online data science certificate program provides technical and analytical skills for data analysis. This program offers hands-on practical skills and allows candidates to work on real-world projects.
This certification program is self-paced and will require four months to complete.
Skills You’ll Learn:
- Conduct statistical hypothesis testing
- Apply data science pipelines to workflows
- Data ingestion and data wrangling
- Apply query-related and NoSQL databases
- Improve models
Prerequisites:
- Entry and mid-level professionals
- Bachelor’s degree
- Completion of two college-level math courses
- Python Programming
What You’ll Get:
- Professional certification
Top 4 Factors To Consider in a Data Science Certification
With multiple certification courses and programs available online, selecting the right certification that fits your career goals is challenging. However, below are a few key points to consider when making a decision.
1. Reputation
Make sure to check for online reviews and whether industry professionals have endorsed the course. Connect with leaders, network and strong alums on professional networks such as LinkedIn.
2. Course Support
Check whether the certification program has relevant resources and references to solve program queries, accessible lectures, videos and textbooks.
3. Future Job Needs
Conduct in-depth research and check whether the skills align with the market demands. Ensure to browse relevant and credible sources.
4. Salary
Adding a certificate doesn’t guarantee whopping salaries; however, it adds credibility to the candidate’s profiles. To strengthen portfolios, adding projects has a higher potential to earn higher salaries.
Notably, the organization’s size and industry type play a significant role in terms of the pay scale.
In Conclusion
Earning a data science certification helps demonstrate skills to employers. Jobs in the data science field are undoubtedly in high demand and are expected to remain so for the foreseeable future.
How eager are you to accelerate your career in the data science field?
Related: A Ranking of Top Data Scientists, Past and Present
Related: How To Become a Business Intelligence Analyst
