Data Science and Certification

8 Best Data Science Certifications Program

Posted in Data Science, Certification
8 Best Data Science Certifications Program

As data science becomes more and more important for humankind, the growing demand for proficient data scientists in various walks of the industry is simply natural.

Data science is one of the hottest career avenues as of now, no doubt about it. As the world moves towards consuming more and more data and even at a faster rate, the emphasis on data science is only meant to grow over time.

Data science is a complex field involving a galore of concepts, data science tools, techniques, approaches, methodologies, and much, much more. Although you can instantly jump into the data science scene, it is thoughtful to know data science in detail beforehand.

8 Best Data Science Certification Programs

Being a certified data science gives a professional a distinctive edge among the competition. Also, it is an opportunity to learn data science if you’re still a student or a graduate, and then confidently advance into the vast realms of data science.

To help you with your cause, here is our pick of the 8 best data science certification programs worth considering to go for:

1. SAS Certification

SAS Academy for Data Science

Duration – Few months to several years
Level – Expert
Platform – SAS Academy for Data Science

Whether you’re looking for getting a better job, bagging a promotion, or enhancing your existing skillset, the SAS Data Science Certification is an excellent option to go for.

The prestigious certification requires a candidate to go through a rigorous certification process that includes:

18 courses divided into 5 modules:

Module 1: Big Data Preparation, Statistics and Visual Exploration
  • Course 1: Big Data Challenges and Analysis-Driven Data
  • Course 2: Exploring Data With SAS Visual Analytics
  • Course 3: Statistics 1: Introduction to ANOVA, Regression and Logistic Regression
  • Course 4: Preparing Data for Analysis and Reporting
  • Course 5: Crafting Compelling (and correct) Data Stories
Module 2: Big Data Programming and Loading
  • Course 1: Introduction to SAS and Hadoop: Essentials
  • Course 2: DS2 Programming Essentials With Hadoop
  • Course 3: Hadoop Data Management With Hive, Pig, and SAS
  • Course 4: Getting Started With SAS In-Memory Statistics
Module 3: Predictive Modeling
  • Course 1: Applied Analytics Using SAS Enterprise Miner
Module 4: Advanced Predictive Modeling
  • Course 1: Neural Network Modeling
  • Course 2: Predictive Modeling Using Logistic Regression
  • Course 3: Data Mining Techniques: Predictive Analytics on Big Data
  • Course 4: Using SAS to Put Open Source Models Into Production
Module 5: Text Analytics, Time Series, Experimentation and Optimization
  • Course 1: Text Analytics Using SAS Text Miner
  • Course 2: Time Series Modeling Essentials
  • Course 3: Experimentation in Data Science
  • Course 4: Optimization Concepts for Data Science
  • Multiple case studies
  • 5 examinations, with a requirement to pass each of them
    • SAS Big Data Preparation, Statistics and Visual Exploration certification exam
    • SAS Big Data Programming and Loading certification exam
    • The predictive Modeling certification exam
    • Advanced Predictive Modeling certification exam
    • Text Analytics, Time Series, Experimentation and Optimization certification exam

Thankfully, the data science certification program offers two learning formats for grasping all the essential topics that form the basis of the SAS Data Science Certification exams:

  1. Instructor-Led Training - Dual attempts for all certification examinations, internship, and placement program, etc. [NOT OFFERED IN US AND CERTAIN OTHER REGIONS]
  2. Self-Paced e-Learning - Courses available 24x7, complete at your own pace over 12 months, etc.

The SAS Certified Data Science Certification program requires a candidate to have:

  • At least 6 months of programming experience in SAS or some other programming language.
  • At least 6 months of experience using mathematics and statistics in a business environment.

In case of candidates doesn’t have these, they need to go for the following SAS-offered courses:

  • Statistics 1: Introduction to ANOVA, Regression or Logistic Regression, and
  • SAS Programming for R Users

OR

  • SAS Programming for Data Science Fast Track

Earning the prestigious SAS Data Science Certification is not a simple task as it includes all the essential topics about data science. So, start preparing today to achieve the best results possible. There’s a long way ahead, so better keep going starting now.

Important topics:

  • Accessing, manipulating, and transforming data
  • Basics of analytics and statistics
  • Critical SAS programming skills
  • Enhancing data quality for analytics and reporting
  • Essential communication skills
  • Experimentation in business
  • Exploring and visualizing data
  • Hadoop, Hive, Pig, and SAS
  • Machine learning
  • Optimization techniques
  • Pattern detection
  • Predictive modeling techniques and their application to distributed and in-memory big data sets
  • Time series forecasting

Exam Details

1.  Name – SAS Big Data Preparation, Statistics, and Visual Exploration Exam
Code – A00-220
Duration – 110 minutes
Language(s) – English
Passing Percentage – 67%
Prerequisites – Hands-on experience with various SAS data preparation tools, including:

  • SAS DataFlux Data Management Studio
  • SAS/STAT
  • SAS Visual Analytics

Price – $180
Questions Type – Multiple choice, short answer, and interactive questions
Total Questions – 55 to 60

2. Name – SAS Big Data Programming and Loading Exam
Code – A00-221
Duration – 105 minutes
Language(s) – English
Passing Percentage – 68%
Prerequisites – Hands-on experience with various SAS and open-source data preparation tools, including:

  • Hadoop, Hive, and Pig
  • SAS Base and DS2 programming
  • SAS In-Memory Statistics

Price – $180
Questions Type – Multiple-choice, short-answer, and interactive questions
Total Questions – 60 to 65

3. Name – Predictive Modeler (Using SAS Enterprise Miner)
Code – A00-255
Duration – 165 minutes
Language(s) – English
Passing Score – 725 (out of 1,000)
Prerequisites:

  • A comprehensive understanding and mastery over the predictive modeling functionalities of the SAS Enterprise Miner
  • Ability to:
    • Assess and implement models
    • Build predictive models
    • Perform pattern analysis
    • Prepare data

Price – $250
Questions Type – Multiple-choice and short-answer
Total Questions – 55 to 60

4. Name – SAS Certified Specialist: Advanced Predictive Modeling (based on SAS 9.4)
Code – A00-225
Duration – 110 minutes
Language(s) – English
Passing Percentage – 67%
Prerequisites:

  • Hands-on experience with several SAS data preparation tools, including:
    • SAS Enterprise Miner
    • SAS LASR Analytic Server
    • SAS/STAT
    • SAS Visual Analytics
  • Working experience in:
    • Applying machine learning and predictive modeling techniques to big, distributed and in-memory data sets
    • Deploying open-source modes in SAS

Price – $180
Questions Type – Multiple-choice, short-answer, and interactive questions
Total Questions – 50 to 55

5.  Name – SAS Specialist: Text Analytics, Time Series, Experimentation and Optimization (based on SAS 9.4)
Code – A00-226
Duration – 110 minutes
Language(s) – English
Passing Percentage – 68%
Prerequisites:

  • Hands-on experience with various SAS data preparation tools, including
    • SAS/ETS
    • SAS/OR
    • SAS Text Analytics
  • Working experience in:
  • o Experiment design for business
  • o Optimization techniques
  • o Text analytics
  • o Time series forecasting

Price – $180
Questions Type – Multiple-choice, short-answer, and interactive questions
Total Questions – 50 to 55

You can signup here.

2. SAS Certified Big Data Professional

Data Curation Professional

Duration – Few weeks to several months
Level – Intermediate
Platform – SAS Academy for Data Science

The SAS Big Data Certification assesses a candidate for the ability to use the technology and tools for handling big data. Both instructor-led training (not offered in the US and some other countries) and self-paced e-Learning modes of learning are available for assisting candidates in preparation for this certification exam.

Candidates interested in enrolling for the SAS Big Data Certification program must have at least 6 months of programming experience in SAS or some other programming language. The SAS Certified Big Data Professional is an extensive certification program that involves several real-world case studies and a total of 9 courses, divided into 2 modules.

The certification exam includes Module 1: Big Data Preparation, Statistics, and Visual Exploration, and Module 2: Big Data Programming and Loading modules of the SAS Certified Data Science certification.

Important topics:

  • Accessing, manipulating, and transforming data
  • Basics of analytics and statistics
  • Critical SAS programming skills
  • Essential communication skills
  • Exploring and visualizing data
  • Hadoop, Hive, Pig, and SAS
  • Improving data quality for analytics and reporting

Exam Details:

  1. SAS Big Data Preparation, Statistics and Visual Exploration certification exam
  2. SAS Big Data Programming and Loading certification exam (See Exam details section of the SAS Data Science Certification for details)

You can signup here.

3. SAS Certified Advanced Analytics Professional

Advanced Analytics Professional

Duration – Few weeks to several months
Level – Intermediate
Platform – SAS Academy for Data Science

The SAS Advanced Analytics Certification not only assesses a candidate’s ability to use advanced analytics techniques for solving critical business problems but also offers the opportunity to learn the latest offerings in the same.

The Advanced Analytics Certification includes the last 3 modules of the SAS Certification, i.e.:

  1. Module 1: Predictive Modeling
  2. Module 2: Advanced Predictive Modeling
  3. Module 3: Text Analytics, Time Series, Experimentation and Optimization

Leave for Module 1, which has only 1 course; the remaining 2 modules have 4 courses each, totaling to 9 courses. You can see the names of the courses in the SAS mentioned above Certification.

The SAS Certified Advanced Analytics Professional program has the same experience requirements as that of the SAS Certified Data Science program:

  • At least 6 months of programming experience in SAS or some other programming language
  • At least 6 months of experience using mathematics and statistics in a business environment

In case of candidates doesn’t have these, they need to go for the following SAS-offered courses:

  • Statistics 1: Introduction to ANOVA, Regression or Logistic Regression, and
  • SAS Programming for R Users

OR

  • SAS Programming for Data Science Fast Track

Important topics

  • Experimentation in business
  • Machine learning and predictive modeling techniques, and their application in distributed and in-memory big data sets
  • Optimization techniques
  • Pattern detection
  • Time series forecasting

Exam Details

  1. Predictive Modeling certification exam (See Exam details section of the SAS Data Science Certification for details)
  2. Advanced Predictive Modeling certification exam (See Exam details section of the SAS Data Science Certification for details)
  3. Text Analytics, Time Series, Experimentation and Optimization certification exam (See Exam details section of the SAS Data Science Certification for details)

You can signup here.

4. Senior Data Scientist

Senior Data Scientist

Duration – Flexible
Level – Expert
Platform – DASCA (Data Science Council of America)

DASCA, short for Data Science Council of America, is the foremost provider of globally recognized data science certifications. It's SDS (Senior Data Scientist), and PDS (Principal Data Scientist) credentials are two of the top global data scientist certifications.

The vendor-neutral data science certification institution offers detailed, in-depth certification programs to candidates coming from the varying background, including business management, finance, stats, and technology.

The Senior Data Scientist (SDS) credential is meant for data analysts and scientists with over 5 years of industry experience. The top-rated third-party, vendor-neutral certification helps these professionals explore higher work domains in data science and analytics.

Knowledge domains tested for the SDS credential:

  • Data Science for Business Stakeholders (15%)
  • Data Science (18%)
  • Business Potential of Big Data (17%)
  • Building Cross-Organization Support (15%)
  • Data Science Fundamentals For Data Scientists (15%)
  • Data Science Essentials For Data Scientists (10%)
  • Advance Data Science For Data Scientists (10%)

Candidates interested in pursuing the SDS certification can choose one among the 5 candidacy tracks:

  1. SDS Track 1 - For those holding a relevant bachelor’s degree. Requirements:
  2. Educational
  3. A completed bachelor’s degree in Applied Sciences, Computer Science, Economics, Engineering, Finance, Management, Mathematics, Statistics, or related disciplines.
  4. Professional
  5. 5 or more years of working experience in Business Analytics, Business Intelligence, Computing, or Data Science
  6. SDS Track 2 - For those holding a relevant master’s degree. Requirements:
  7. Educational
  8. A completed master’s degree in Applied Sciences, Computer Science, Economics, Engineering, Finance, Management, Mathematics, Statistics, or related disciplines.
  9. Professional
  10. 4 or more years of working experience in Business Analytics, Business Intelligence, Computing, or Data Science
  11. SDS Track 3 - For candidates with a bachelor’s degree (QualiFLY). Requirements:
  12. Educational
  13. Same as that of SDS Track 1
  14. Professional
  15. Same as that of SDS Track 2
  16. SDS Track 4 - For candidates with a master’s degree (QualiFLY). Requirements:
  17. Educational
  18. Same as that of SDS Track 2
  19. Professional
  20. 3 or more years of working experience in Business Analytics, Business Intelligence, Computing, or Data Science
  21. SDS Track 5 - For candidates holding an SBDA (Senior Big Data Analyst) or SBDE (Senior Big Data Engineer) credential (QualiFLY)
  22. Educational
  23. A valid SBDA or SBDE credential
  24. Professional
  25. 4 or more years of industry experience after acquiring SBDA or SBDE certification

Note: The SDS certification is valid for 5 years.

Exam Details

Name – Senior Data Scientist Exam
Code – N/A
Duration – 100 minutes
Language(s) – English
Passing Percentage – 65% (Using an algorithm that accounts for a degree of difficulty, relative scoring, and scaling.)
Price – $650
Questions Type – Multi-choice, multi-answer
Total Questions – 85

You can signup here.

5. Principal Data Scientist

Senior Data Scientist

Duration – Flexible
Level – Expert
Platform – DASCA (Data Science Council of America)

Another best certification offered by the Data Science Council of America is the Principal Data Scientist certification. The PDS credential is meant for data scientists helping companies reaching new heights in their business endeavors.

The Principal Data Scientist certification puts a data scientist in front of the global league of data scientists. The 3rd-party, vendor-neutral credential is an invaluable addition to a candidate’s resume, flaunting professional class, and leadership in Big Data Architects and Data Scientists roles.

Successfully earning the PDS credential requires passing two assessment levels; PDS Level I and PDS Level II. While Level I is an online, computer-based test, Level II comprises written work and submissions.

PDS Level I Exam Knowledge Domains:

  • Data Science for Business Stakeholders (10%)
  • Data Science (10%)
  • Business Potential of Big Data (15%)
  • Building Cross-Organizational Support (10%)
  • Data Science Fundamentals For Data Scientists (15%)
  • Data Science Essentials for Data Scientists (25%)
  • Advanced-Data Science For Data Scientists (15%)

PDS is probably the most prestigious data scientist certification that one can have. It is, however, available only to the most accomplished data scientists. The Principal Data Scientist certification is awarded only after following a stringent assessment of application, evaluation, and vetting.

There are 4 candidacy tracks available for pursuing the Principal Data Scientist certification:

  1. PDS Track 1 - The QualiFLY Route ($850) - For alumni or graduates of DASCA-recognized institutions or DASCA-partner universities. Requirements:
  2. Educational
  3. Master’s Degree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, or related disciplines.
  4. Professional
  5. 10 years of experience in the technology domain.
  6. 3 years or more experience in Big Data Architecting, Business Analytics Application Development, Business Intelligence Solution Design, Data Analytics, Data Engineering, Data Products Development, Data Science Applications in AI, or IoT.
  7. PDS Track 2 - Corporate Nomination ($850) - For data science professionals and data scientists holding a master’s degree and working in DASCA-partner organizations/Corporate Partners. Requirements:
  8. Educational
  9. Same as that of PDS Track 1
  10. Professional
  11. Same as that of PDS Track 1
  12. PDS Track 3 - for the SDS Certified ($300) - For individuals holding the DASCA Senior Data Scientist (SDS) certification. These candidates need not go through the PDS Level I exam. Instead, they directly move to submissions-based assessment Level II. Requirements:
  13. Education
  14. Same as that of PDS Track 1
  15. Holding an active SDS credential
  16. Professional
  17. Same as that of PDS Track 1 with the exception of having at least 5 years of experience in Big Data Architecting, Business Analytics Application Development, Business Intelligence Solution Design, Data Analytics, Data Engineering, Data Products Development, Data Science Applications in AI or IoT.
  18. PDS Track 4 - Open Applications ($950) - For dedicated data scientists with 12 or more years of experience in the technology domain. Requirements:
  19. Education
  20. Same as that of PDS Track 1
  21. Professional
  22. 12 years or more experience in the technology domain.
  23. 5 years or more experience in Big Data Architecture, Business Analytics Application Development, Business Intelligence Solution Design, Data Analytics, Data Engineering, Data Products Development, Data Science Applications in AI, or IoT.

The PDS certification is valid for a lifetime.

Exam Details:

Name – Principal Data Scientist Exam
Code – N/A
Duration – 100 minutes
Language(s) – English
Passing Percentage – 65% (Using an algorithm that accounts for a degree of difficulty, relative scoring, and scaling.)
Price – $820
Questions Type – Multi-choice, multi-answer
Total Questions – 100

You can signup here.

6. Microsoft Certified: Azure Data Scientist Associate

Microsoft Certified: Azure Data Scientist Associate

Duration – Flexible
Level – Entry-level
Platform – Microsoft Learn

Interested in learning how to implement and run machine learning workloads on Azure and doing the same? It requires a good knowledge of data science and machine learning. The Microsoft Certified: Azure Data Scientist Associate is the certification for you.

The best thing about this Microsoft certification is that you can prepare for the course free with learning options from Microsoft. You can, however, have the best learning experience from Microsoft with the instructor-led, paid preparation way.

The associate certification from Microsoft requires a candidate to have a sound understanding of:

  • Fundamentals of machine learning and data science
  • Exploring AI solution development with data science services in Azure
  • Building AI solutions with Azure Machine Learning service
  • Get started with Machine Learning with an Azure Data Science Virtual Machine
  • Performing data engineering with Azure Databricks
  • Extracting knowledge and insights from the data using Azure Databricks
  • Introduction to machine learning with Python and Azure Notebooks

The Microsoft Certified: Azure Data Scientist Associate certification requires giving and passing the Microsoft Exam DP-100: Designing and Implementing a Data Science Solution on Azure. Here are the topics covered by this exam:

  • Set up an Azure Machine Learning workspace (30-35%)
    • Create an Azure Machine Learning workspace
    • Manage data objects in an Azure Machine Learning workspace
    • Manage experiment compute contexts
  • Run experiments and train models (25-30%)
    • Create models by using Azure Machine Learning Designer
    • Run training scripts in an Azure Machine Learning workspace
    • Generate metrics from an experiment run
    • Automate the model training process
  • Optimize and manage models (20-25%)
    • Use Automated ML to create optimal models
    • Use Hyperdrive to tune hyperparameters
    • Use model explainers to interpret models
    • Manage models
  • Deploy and consume models (20-25%)
    • Create production compute targets
    • Deploy a model as a service
    • Create a pipeline for batch inferencing
    • Publish a Designer pipeline as a web service

Exam Details

Name – Designing and Implementing a Data Science Solution on Azure
Code – Exam DP-100
Duration – 150 to 180 minutes
Language(s) – Chinese (Simplified), English, Japanese, and Korean
Passing Percentage – 70%
Prerequisites – None
Price – $165
Questions Type – Interactive, multiple-choice, task-based, case study exam format, short answer question
Total Questions – 40 to 60

You can signup here.

7. IBM Data Science Professional Certificate

IBM Data Science Professional Certificate

Duration – 3 months (flexible)
Level – Beginner
Platform – Coursera

Another opportune data certification is the IBM Data Science Professional Certificate. The beginner-level data science certification program is ideal for candidates looking to kickstart their professional data science career.

The professional data scientist certification from IBM involves a total of 9 courses:

  1. What is Data Science?
  2. Open Source tools for Data Science
  3. Data Science Methodology
  4. Python for Data Science and AI
  5. Databases and SQL for Data Science
  6. Data Analysis with Python
  7. Data Visualization with Python
  8. Machine Learning with Python
  9. Applied Data Science Capstone

There are no applying prerequisites for the IBM Data Science Professional Certificate. Anyone with a genuine interest in data science can opt for the program.

Other than English, the data science certification program is also available in Arabic, German, Korean, Turkish, and Vietnamese languages. Instructors for the data science certification program are:

  • Joseph Santarcangelo - Ph.D., Data Scientist at IBM/IBM Developer Skills Network
  • Alex Akeson - Ph.D., Data Scientist/IBM Developer Skills Network
  • Rav Ahuja - AI and Data Science Program Director/IBM
  • Saeed Aghabozorgi - Ph.D., Sr. Data Scientist/IBM Developer Skills Network
  • Polong Lin - IBM Developer Skills Network

You can signup here.

8. HarvardX’s Data Science Professional Certificate

Professional Certificate in Data Science

Duration – 1 year and 5 months (flexible)
Level – Beginner
Platform – edX

Designed to empower faculty for improving teaching and learning via on-campus and online modes, HarvardX offers a range of online courses. Learn data science essentials, such as R and machine learning, from real-world case studies with HarvardX’s Data Science Professional Certificate.

The data science certification from HarvardX equips candidates with the knowledge and skills required for tackling real-world data analysis problems. The professional data science certification has 9 courses in total:

  1. Data Science: R Basics
  2. Data Science: Visualization
  3. Data Science: Probability
  4. Data Science: Inference and Modeling
  5. Data Science: Productivity Tools
  6. Data Science: Wrangling
  7. Data Science: Linear Regression
  8. Data Science: Machine Learning
  9. Data Science: Capstone

Each course of the certification course features a range of questions and answers, and case studies, including:

  • Building a Baseball Team (inspired by Moneyball)
  • Movie Recommendation Systems
  • Trends in World Health and Economics
  • The Financial Crisis of 2007-2008

Important Topics

  • Basic R programming
  • Fundamentals of data science
  • Understanding and applying Inference, modeling, and probability
  • Data visualization with ggplot2
  • Data wrangling with dplyr
  • Unix/Linux
  • Linear regression
  • Git and GitHub
  • RStudio
  • Machine learning algorithms

You can signup here.

P.S. - Need best data science courses and other learning material to champion the certification exam(s)? Check out these top data science tutorials and courses recommended and curated by the hackr.io community.

Summary

As they say, no time like now! Data science is mushrooming right now, with no signs of subsiding anytime soon. So, better make the most out of it now. If you’re someone who likes to play with numbers and doesn’t get enough of doing calculations, equations, and that kind of stuff over and over again...data science is waiting for you!

Here’s time to wrap up the article. Signing out, hoping that you’ll have gained a little something out of sparing your time and effort in going through the write-up. No? Not at all? Let us know in the comments to make it better.

Oh, and don’t forget to check out our pick of the best data science books for beginners and experts, if you’re that serious about data science. Keep going!

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Simran Kaur Arora

Simran Kaur Arora

Simran, born in Delhi, did her schooling and graduation from India in Computer Science. Curious and passionate about technology urged her to study for an MS in the same from the renowned Silicon Valley, California, USA. Graduated in 2017, she flew back to India and now works for hackr.io as a freelance technical writer. View all posts by the Author

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venkatesh
venkatesh

Great job, i love this topic & especially the way you have explained it is really awsome. Thnaks for sharing this info..