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Top 5 Data Science Certifications In-demand By Fortune 500 Firms in 2022

We live in a big data world, with the volume of global data expected to reach 180 zettabytes by 2025. However, this massive amount of data will necessitate domain specialists who can transform it into useful insights using innovative technologies. As a result, the work of data science professionals is critical in assisting leadership teams in developing goals and plans.

So, does that mean becoming a talented and ablaze data science professional is easy?

The answer to this is a clear No!

Why Data Science Professionals Are In Demand?

Data science is a lucrative field with huge demand for professionals and an easy to enter the field — a common misconception that beginners and even mid-level professionals have these days. As you discover the unique domain, you will realize that data science is a discipline that requires continuous learning of new skills and technologies to solve data-related problems.

  • According to Payscale reports, an entry-level data scientist with a year or lesser experience can expect to earn handsome salaries somewhere between USD 85,456 to USD 96,204, which is pretty high compared to other professions.
  • According to Indeed, the number of data science job postings has increased by over 33 percent and employers prioritize professionals having the latest-data science skills.

Holding a degree in the related field will no doubt equip you with basic skills but earning data science certifications will allow you to hone niche skills that are difficult to find in this industry. Furthermore, it is a chance to supplement your expertise. This way, recruiters of Fortune 500 firms will know what they are getting if they hire you.

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

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

All of these cannot be answered indisputably unless you have aced them and officially hold a digital certification to prove these skills.

Consider examples of experts working in Fortune 500 firms at top levels

  • Benjamin Arnulf ( AI, data, and analytics strategy leader with 15+ years of global experience in the USA and Europe) — holds multiple data science certifications (Python for data science, Oracle Cloud Customer Connect, and so on)
  • Carla Gentry (Senior Data Scientist at Analytical solutions, values certifications to learn new skills and holds one too).

This represents a coherent condition that even top-tier data specialists consider a data science certification and you should not fall behind in doing so.

As the tweet mentions, several applicants opt for data science courses that fail to teach tangible and non-tangible data science skills. Most of the design programs in a way that helps learners to complete the course that merely includes learning topics that are easy and basic.

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

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

“Everything worthwhile in life necessitates effort. It is a general rule that what needs the most effort provides the highest value, whereas what is effortless is effectively worthless”.

Top organizations will only recruit individuals who are talented enough to match their work requirements, so even if you believe you are knowledgeable about data science, a credible and globally accepted data science certification is required to demonstrate that you are formally recognized to hold the latest data science skills.

Let us discuss some important and best data science certifications in demand by top companies in 2022.

1. IBM Data Science Certification

2. Senior Data Scientist (DASCA)

3. Azure Data Science Associate (Microsoft)

4. Professional Certification in Data Science (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. Data Scientist Nanodegree ( Udacity)

You may have difficulties in selecting the appropriate credential to obtain. Furthermore, you may be interested in having specializations that you would like to excel in. Here is a curated list of the top 5 certifications that are selected based on their popularity and international demand.

1. IBM Data Science Certification

This data science credential is designed to assist novices to grasp the core ideas of data science, the duties and devoirs of a data scientist, and how to make use of data science technologies like IBM cloud, RStudio IDE, and Jupyter Notebooks fluently. The program comprises ten courses that teach learners the most recent data science skills and approaches. Python, databases and SQL, data visualization, data analysis, and ML to name a few topics are covered under this program.

Pros:

  • No specific prerequisites needed
  • Learn at your speed

Cons:

  • It takes a longer time to complete the program compared to other best data science certifications.

👉 Certification Details:

2. Senior Data Scientist (SDS™) by DASCA

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

Pre-requisites:

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

Pros:

  • It is affordable and the entire process is online; saves time and cost.
  • The certification program offers high-impact tech-leadership jobs for data science professionals and is ranked among the top 5 data science certifications in the world by CIO magazine. The SDS™ knowledgeware, 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 most important global business regions, giving you a bigger, more international edge in the job market.
  • The certification is validated in five essential knowledge dimensions and 30 core professional knowledge subjects

Cons:

  • Prerequisites are slightly more compared to other credentials.

👉 Certification Details:

Other certifications offered by DASCA:

3. Azure Data Science Associate (Microsoft)

This certification enables you to learn all there is to do about cloud technology while also gaining practical learning experience with it. The exam assesses your abilities to create and deploy Azure applications.

Pre-requisites:

It is ideal for anyone interested in learning further about Azure or who is already using it. Even though it is an entry-level credential, you will gain knowledge of the subject by studying the key principles; nonetheless, prior experience in the relevant sector is required. Moreover, it is perfect for data scientists because it is primarily focused on learning how to use and apply Azures ML service, and NLP, and is taught through hands-on experience.

Pros:

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

Cons:

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

👉 Certification Details:

4. Professional Certification in Data Science (Harvard University)

The HarvardX Data Science program provides you with the information and skills you need to face real-world data analysis difficulties. The program teaches concepts such as probability, inference, regression, and machine learning, as well as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and repeatable document preparation with RStudio. You will concurrently learn R, statistical ideas, and data analysis procedures.

Pre-requisites:

There are no such pre-requisites to obtain this credential.

Pros:

  • Apt for professionals wanting to gain hands-on experience in R programming

Cons:

  • The program says that there are no prior qualifications needed, albeit a basic comprehension of mathematics is a re-requisite.

👉 Certification Details:

5. SAS Certified Data Scientist

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

Pre-requisites:

It is intended to be 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 analysis tools such as Hive/HiveQL, Hadoop, and PIG/PIGLATIN.

Pros:

  • SAS-certified professionals are internationally recognized

Cons:

  • Heavy on the pocket
  • Requires multiple pre-requisites.

👉 Certification Details:

Other certifications offered by SAS:

In a nutshell…

Leaving aside the dispute over whether or not to obtain certifications or how important are they, examine the knowledge you will receive during the learning process. There is no such thing as a waste if you have technical expertise that can help you construct a better future.

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