Top Data Science Certifications You Should Know in 2025

Top Data Science Certifications You Should Know in 2025

Categories: Analytics & Data Management|Published On: May 14, 2025|9.1 min read|
About the Author

Brian Ng

A network engineering and cybersecurity expert with over 25 years of experience, Brian is highly skilled in Cisco, AWS, and Azure technologies.
Top Data Science Certifications You Should Know in 2024

Which Data Science Certification is the best?

Which data science certifications will optimize your career potential in 2025? This analysis presents the most advantageous and industry-acknowledged certifications available today. Shortlist the top data science certifications and discern how each can directly impact your professional trajectory without wasting time on sales fluff. Keep reading to uncover which certifications align with your career objectives.

Key Takeaways

  • Data science certifications are vital for IT professionals to validate their skills, set themselves apart in a competitive job market, and meet the rising demand in the field, as the employment of data scientists is projected to grow by 35% from 2022 to 2032.

  • There are several top data science certifications in 2024, including the Data Engineering on Google Cloud, Practical Data Science with Amazon SageMaker, Amazon SageMaker Studio for Data Scientists, Designing and Implementing a Data Science Solution on Azure, and Data Engineering on Microsoft Azure, each catering to different skill levels and career paths.

  • Choosing the right data science certification depends on individual career goals, the alignment with current skills, practical applicability, learning flexibility, and financial investment, with the ultimate aim of enhancing professional development, employability, and return on investment.

Why Data Science Certifications Matter

Data science certifications not only validate your knowledge and skills but also offer a significant advantage in a competitive job market. According to the US Bureau of Labor Statistics, approximately 17,700 job openings for data scientists are expected annually over the next decade. Moreover, the employment of data scientists is projected to grow by 35% from 2022 to 2032, which is much faster than the average for all occupations. Therefore, obtaining certifications in data science is a strategic approach to prepare for this increasing demand.

Such certifications convey a signal of proficiency that is valued by organizations. They act as a testament to your commitment to professional development, and often serve as a requirement for certain job roles. This makes them a necessary step for many IT professionals in Malaysia, striving to stay competitive in the job market.

Moreover, data science certifications bear credibility as they signify a track record of success. They are often endorsed by the industry and recognized by hiring managers, which can translate into increased earning potential. Thus, these certifications not only validate your skills but can also open doors to better job opportunities and career advancement.

Ultimately, for IT professionals, data science certifications are valuable tools to set themselves apart in an increasingly competitive job market. They offer a platform to showcase your mastery over key data science concepts, thereby enhancing your employability and career prospects.

Top Data Science Certification Courses for 2025

As we navigate through 2025, certain data science certifications courses have emerged as highly sought after by data science professionals. Among these are:

  • GCPDE: Data Engineering on Google Cloud
  • AWS-PDSASM: Practical Data Science with Amazon SageMaker
  • AWS-SSDS: Amazon SageMaker Studio for Data Scientists (BONUS)
  • DP-100T01: Designing and Implementing a Data Science Solution on Azure
  • CT-DX: CompTIA DataX

Each certification provides a unique combination of knowledge acquisition, skill development, and industry recognition.

GCPDE:
Data Engineering on Google Cloud

The GCPDE: Data Engineering on Google Cloud certification course is a top-tier certification course designed to equip participants with the skills necessary to become data-driven using the Google Cloud Platform. This course is ideal for anyone interested in data engineering, as it requires no specific academic prerequisites, making it accessible to a broad audience.

Upon completion of the program, you become eligible to take the Google Cloud Professional Data Engineer certification exam.

A comprehensive course:

The curriculum is comprehensive, covering key topics such as designing and building data processing systems, creating end-to-end data pipelines, and analyzing data using advanced Google Cloud technologies.

Gain Practical Experience:

Participants will gain practical experience with tools like Cloud Dataproc for running Hadoop and Spark jobs, Cloud Dataflow for processing batch and streaming data, and Cloud BigQuery for large-scale data analysis. The program also includes training on implementing machine learning models using TensorFlow and Cloud ML.

This hands-on program emphasizes real-world applications and provides students with the opportunity to work on live projects and labs. By focusing on both the theoretical and practical aspects of data engineering, the course ensures that participants are well-prepared for careers as data engineers.

AWS-PDSASM:
Practical Data Science with Amazon SageMaker

The AWS-PDSASM: Practical Data Science with Amazon SageMaker course is designed for data scientists, developers, and machine learning practitioners who wish to effectively utilize Amazon SageMaker to accelerate the development and deployment of high-quality machine learning models. This course empowers participants to leverage Amazon SageMaker’s comprehensive suite of purpose-built tools for each stage of the machine learning development process.

Upon completion of the program, students become eligible to pursue the AWS Certified Machine Learning – Specialty certification exam.

The agenda:

This intensive one-day course offers a blend of theory and practical application, focusing on a real-world machine learning use case. Participants will learn how to analyze and visualize datasets, prepare data, engage in feature engineering, and navigate through the stages of model building, training, tuning, and deployment using Amazon SageMaker. The course is structured to provide a thorough understanding of the data science workflow, from initial data analysis to deploying models at scale.

Hands-on experience:

In addition to learning the technical skills, attendees will gain hands-on experience with Amazon SageMaker through various demonstrations and exercises, including setting up Jupyter notebooks, training models using algorithms like XGBoost, and automating model tuning. The training also covers deployment strategies such as A/B testing and auto-scaling, ensuring models are production-ready.

AWS-SSDS:
Amazon SageMaker Studio for Data Scientists

The AWS-SSDS: Amazon SageMaker Studio for Data Scientists course is an advanced training program designed to enhance the productivity of experienced data scientists by fully leveraging Amazon SageMaker Studio. This course focuses on streamlining the entire machine learning workflow, from data preparation to model deployment, utilizing SageMaker Studio’s comprehensive suite of tools.

This course does not offer a certification, but it will significantly boost your data science skills.

What you will learn:

Over a span of three days, participants will delve into the functionalities of SageMaker Studio, learning to accelerate model building, tuning, and deployment. The course emphasizes practical skills in deploying robust monitoring solutions to maintain model performance and teaches best practices for collaboration and resource management within the SageMaker Studio environment.

Target audience:

This course is tailored for experienced data scientists who are already proficient in machine learning and deep learning fundamentals, including those familiar with ML frameworks and Python programming. Participants will gain hands-on experience through labs that involve setting up data processing workflows, tuning models, and implementing full-scale deployment and monitoring strategies.

DP-100T01:
Designing and Implementing a Data Science Solution on Azure

The DP-100T01: Designing and Implementing a Data Science Solution on Azure course is specifically tailored for professionals aiming to master the intricacies of data science and machine learning in the cloud with Azure. Aspiring to equip data scientists with the ability to leverage AI and machine learning effectively, this course emphasizes enhancing organizational capabilities in visualizing and delivering innovation, improving customer experiences, increasing revenue, and maintaining a competitive edge.

Upon completion of the course, you become eligible for the Microsoft Certified: Azure Data Scientist Associate certification exam.

Tools & skills:

Participants will engage deeply with Azure’s tools, mastering data ingestion and preparation, model training, deployment, and monitoring. The course is designed for data scientists who already have foundational knowledge in Python and familiarity with machine learning frameworks such as Scikit-Learn, PyTorch, and TensorFlow.

Target Audience:

This course is ideal for data scientists who are ready to elevate their expertise in cloud-based machine learning solutions, focusing on practical applications and robust learning outcomes that align with industry standards and requirements.

CT-DX:
CompTIA DataX

The CompTIA DataX (DY0-001) is the premier skills development program for highly experienced professionals seeking to validate competency in the rapidly evolving field of data science.

Professionals in the data field looking to upskill and close existing knowledge gaps will benefit from CompTIA DataX. This new certification falls under CompTIA Xpert — a new series of certifications and trainings offered through CompTIA that are geared towards professionals who are looking to gain expert knowledge in business-critical technologies.

DataX equips highly experienced professionals with essential skills that meet the demands of the rapidly evolving field of data science. Learners will have access to a comprehensive curriculum that covers concepts ranging from the foundations of machine learning to more specialized data science applications.

Tools & practices:

The CompTIA DataX exam was developed to meet an industry need ––bridge gaps in training and knowledge for data science professionals. The exam objectives include real-world scenarios where learners apply their knowledge, ensuring they are prepared for various challenges they may face in their careers as data scientists.

Based on extensive input from experienced data scientists, DataX validates successful candidates can properly utilize and analyze vast amounts of data, extract meaning and generate actionable insights. S

Prepare yourself:

CompTIA DataX validates expert-level data science skills regardless of vendor tools. DataX focuses on core competencies like data mining, visualization, and reporting, ensuring candidates can adapt to various platforms.

Its vendor-neutral approach, ISO/ANSI National Accreditation Board (ANAB) accreditation, and alignment with government standards (e.g., DoD 8570) enhance its credibility and global recognition.

Choosing the Right Data Science Certification

Choosing the right data science certification varies with each individual’s circumstances and needs. Prospective learners should consider how well the program aligns with their career stage, specific goals, and current skill set. Understanding the requirements and flexibility of a data science certification program, including prerequisites and delivery methods, is crucial to ensure it accommodates an individual’s schedule and learning pace.

You should also evaluate if the certification provides practical learning opportunities and teaches widely-used tools in the data science community such as Jupyter and more. These practical skills can then be directly applied in your professional role, increasing your value as a team member.

Finally, when considering a data science certification, it’s important to balance its cost against your personal financial situation. Making an informed decision should be informed by course reputation and feedback from past participants. Ultimately, the right certification should enhance your skills, boost your career, and provide a return on your investment.

Trainocate Malaysia’s Certification Programs

Trainocate Malaysia is a leading player in the IT Training Provider Industry in Malaysia, with over 25 years of experience. We offers a comprehensive suite of data science certifications, encompassing areas such as big data, data engineering, and data science to meet diverse professional needs.

Conveniently located in the burgeoning KL Eco City, neighboring Mid Valley City, Trainocate Malaysia provides easy access to participants. As a HRD Corp Registered Training Provider and Authorized Training Partner with top technology companies like AWS, Google Cloud, and Microsoft, we are prime choice for professionals seeking to boost their careers with data science certifications.

Summary

In conclusion, data science certifications are a powerful tool for IT professionals in Malaysia seeking to enhance their careers. Whether you’re a beginner or an experienced professional, there’s a certification for you. From the comprehensive Practical Data Science with Amazon SageMaker Certificate to the specialized Data Engineering on Microsoft Azure Certificate, the opportunities for learning and career advancement are abundant. So go ahead, explore these certifications, and get ready to take your career to new heights.

Frequently Asked Questions

What are the benefits of data science certifications?

Data science certifications validate your knowledge, increase your employability, and are highly valued by organizations, helping you stand out in a competitive job market. They may also be required for certain jobs.

Which data science certifications are recommended for 2024?

Consider pursuing the Data Engineering on Google Cloud, Practical Data Science with Amazon SageMaker, Amazon SageMaker Studio for Data Scientists, Designing and Implementing a Data Science Solution on Azure, and Data Engineering on Microsoft Azure.

How should I choose the right data science certification?

To choose the right data science certification, consider your career stage, goals, and current skills, as well as the program requirements, flexibility, and hands-on learning opportunities. Choose a certification that aligns with your specific needs and offers hands-on experience.

Where can I get a data science certification in Malaysia?

You can get a data science certification in Malaysia through Trainocate Malaysia, which offers a range of comprehensive certifications in partnership with top technology companies like AWS, Google Cloud, and Microsoft.

About the Author

Brian Ng

A network engineering and cybersecurity expert with over 25 years of experience, Brian is highly skilled in Cisco, AWS, and Azure technologies.