Top 5 Data Science Certifications Requested by Fortune 500 Companies in 2022 | by Albert Christophe | June 2022

We live in a world of big data, with the volume of global data expected to reach 180 zettabytes by 2025. However, this massive amount of data will require specialists in the field who can transform it into useful information using innovative technologies. Therefore, the work of data science professionals is essential in helping management teams develop goals and plans.

So, does that mean it’s easy to become a talented and fiery data science professional?

The answer to that is a clear no!

Data science is a lucrative field with huge demand for professionals and easy entry into the field – a common misconception beginners and even mid-level pros have these days. By discovering this unique field, you will realize that data science is a discipline that requires continuous learning of new skills and technologies to solve data problems.

  • According to reports from Payscale, an entry-level data scientist with a year or less of experience can expect to earn handsome salaries between $85,456 and $96,204, which is quite high compared to other professions.
  • According to Indeed, the number of data science job openings has increased by more than 33% and employers are prioritizing professionals with the latest data science skills.

Having a degree in the related field will undoubtedly equip you with basic skills, but earning data science certifications will allow you to hone niche skills that are hard to find in this industry. In addition, it is an opportunity to complete your expertise. That way recruiters at Fortune 500 companies will know what they’re getting if they hire you.

To help you better understand the importance of data science certifications; Let’s discuss some vital interview questions asked by employers.

  • What is the difference between long format data and wide format data?
  • Mention some sampling techniques. What is the main advantage of sampling?
  • What is your understanding of logistic regression?
  • What is a confusion matrix?
  • What are eigenvectors and eigenvalues?

It is impossible to answer all of these questions indisputably unless you have mastered them and officially hold a digital certification to prove these skills.

  • Benjamin Arnulf (leader in AI, data and analytics strategy with over 15 years of global experience in the US and Europe) – holds multiple data science certifications (Python for Data Science, Oracle Cloud Customer Connect, etc.)
  • Carla Gentry (Senior Data Scientist at Analytical solutions, values ​​certifications to acquire new skills and also holds one).

This represents a consistent condition that even the best data scientists consider a data science certification and you should not fall behind in doing so.

As the tweet mentions, several candidates opt for data science courses that fail to teach tangible and non-tangible data science skills. Most of the design programs help the learners to complete the course which just includes simple and basic learning topics.

  • A recent report by Forbes suggests that the job demand for data science professionals is expected to grow from 3,64,000 to 27,20,000; however, supply does not match industry demands.

The demand gap is for a reason. A popular quote explains the situation well.

“Anything worthwhile in life requires effort. It is a general rule that what takes the most effort provides the highest value, while what is effortless is effectively worthless.

The best organizations will only hire people who are talented enough to meet their job requirements, so even if you think you know data science well, a credible and globally accepted database a scientific certification is required to demonstrate that you are officially recognized to hold the latest skills in data science.

Let’s discuss some important and best data science certifications demanded by top companies in 2022.

1. IBM Certification in Data Science

2. Senior Data Scientist (DASCA)

3. Azure Data Science Associate (Microsoft)

4. Data Science Professional Certification (Harvard University)

5. SAS Certified Data Scientist

6. Applied Data Science with Python (University of Michigan)

7. Professional Data Engineer (Google)

8. Data Science Specialization (John Hopkins University)

9. Data Science Bootcamp (Springboard)

10. Nanodegree Data Scientist (Udacity)

You may have difficulty selecting the appropriate degree to earn. Additionally, you might be interested in specializations in which you would like to excel. Here is a curated list of the top 5 certifications selected based on their popularity and international demand.

This data science degree is designed to help novices grasp the fundamental ideas of data science, the duties and duties of a data scientist and how to use data science technologies like IBM cloud, RStudio fluently IDEs and Jupyter Notebooks. The program includes ten courses that teach learners the latest skills and approaches in data science. Python, databases and SQL, data visualization, data analysis and ML to name a few topics are covered in this program.

Advantages:

  • No specific prerequisites needed
  • Learn at your own pace

The inconvenients:

  • It takes longer to complete the program compared to others best data science certifications.

This is one of the best data scientist certifications you can get to enter the league of top data scientists, offered by the Data Science Council of America. This is the most powerful certification for qualified data science professionals who want to demonstrate their data leadership potential and cutting-edge data science knowledge. SDS™ is built on a vendor-neutral body of knowledge to underscore your commitment to the highest standards of competence and its high-impact learning path that results in an excellent qualification.

Preconditions:

Professionals with more than 4 years of professional experience and a bachelor’s / master’s degree in the field of data science and a related discipline can apply for this title. Additionally, the program requires you to be familiar with statistical analysis, database administration, spreadsheets, SPSS, R programming, and a range of quantitative approaches.

Advantages:

  • It is affordable and the whole process is online; saving time and money.
  • The certification program offers high-impact technology leadership jobs for data science professionals and is ranked among the top 5 data science certifications in the world by CIO magazine. SDS™ knowledge software, developed by the world’s leading industry professionals, provides a high-impact learning path that results in an excellent qualification.
  • SDS™ is aligned with the market needs of the world’s most important business regions, giving you a greater, more international advantage in the job market.
  • Certification is validated in five essential knowledge dimensions and 30 core professional knowledge topics

The inconvenients:

  • Prerequisites are slightly higher than other credentials.

Other certifications offered by DASCA:

This certification allows you to learn all there is to do about cloud technology while gaining hands-on learning experience with it. The exam assesses your abilities to build and deploy Azure applications.

Preconditions:

It’s ideal for anyone who wants to learn more about Azure or is already using it. Even though this is an entry-level degree, you will gain knowledge of the subject by studying the key principles; however, previous experience in the relevant sector is required. Additionally, it is perfect for data scientists as it is primarily focused on learning how to use and apply the Azures ML service and NLP, and is taught through hands-on experience.

Advantages:

  • Free to learn in the absence of the instructor
  • Advanced learning for entry-level professionals

The inconvenients:

  • The course loads with the presence of an instructor are high.

The HarvardX Data Science program equips you with the information and skills you need to tackle real-world data analysis challenges. The program teaches concepts such as probability, inference, regression and machine learning, as well as R programming, data management with dplyr, data visualization with ggplot2, file organization with Unix/ Linux, version control with git and GitHub, and preparing reproducible documents. with RStudio. You will simultaneously learn R, statistical ideas and data analysis procedures.

Preconditions:

There are no such prerequisites for obtaining this degree.

Advantages:

  • Suitable for professionals looking to gain hands-on experience with R programming

The inconvenients:

  • The program states that no prior qualifications are required, although a basic understanding of mathematics is a prerequisite.

This certification is an amalgamation of many SAS brand credentials. The credential includes a wide range of topics, such as data science principles, data analysis, and data manipulation, among others.

Prerequisites:

This is an interactive data scientist certification for those who use open source tools and machine learning models to extract insights from massive amounts of data and then use that knowledge to make better decisions. This certification requires learners to have at least 2-3 months of hands-on experience with SAS data management tools and applications, as well as third-party analytics tools such as Hive/HiveQL, Hadoop, and PIG/PIGLATIN.

Advantages:

  • SAS certified professionals are internationally recognized

The inconvenients:

  • Heavy on the pocket
  • Requires several prerequisites.

Other certifications offered by SAS:

Leaving aside the dispute over whether or not to get certifications or their importance, consider the knowledge you will receive during the learning process. There’s no waste if you have technical expertise that can help you build a better future.

About Jon Moses

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