10 Certifications In Data Science That Will Pay Off

10 Certifications in Data Science That Will Pay Off

Data scientist is one of the most in-demand positions in information technology. Businesses are becoming increasingly reliant on data and are eager to hire data experts capable of making sense of the data they collect. If you want to break into this profitable sector or stand out from the competitors, certification can be vital. 

Certifications in data science are an excellent approach to acquire an edge because they enable you to develop abilities that are in high demand in your desired field. They also serve as a means of validating your abilities, ensuring that recruiters and hiring managers understand what they're receiving if they hire you.

Whether you want to get a certification from an approved university, gain experience as a recent graduate, hone vendor-specific abilities, or demonstrate your knowledge of data analytics, the following certificates will work for you.

Cloudera Certified Associate (CCA) Data Analyst

The Cloudera Certified Associate (CCA) Data Analyst certification validates your ability to extract and generate reports in Cloudera's CDH environment using Impala and Hive as a SQL developer. As a data scientist, SQL developer abilities will enable you to extract, model, manage, analyze, and deal with data directly from the source. You'll be presented with eight to twelve client problems using a unique data set and a CDH cluster during the 120-minute exam. You'll be evaluated on your ability to examine each topic and then determine the most effective method for "implementing a technical solution with a high degree of precision."

Certified Analytics Professional (CAP)

The Certified Analytics Professional (CAP) credential validates your ability to "transform complex data into valuable insights and actions," which is precisely what businesses seek in a data scientist: someone who understands data, can draw logical conclusions, and can communicate to key stakeholders why those data points are significant. Before you may sit for the CAP or associate level aCAP tests, you must apply and meet specific prerequisites. To sit for the CAP certification exam, you must have three years of related experience if you hold a master's degree in a related subject, five years if you hold a bachelor's degree in a related field, and seven years if you hold any other degree unrelated to analytics. To sit for the aCAP exam, you must have a master's degree in data or analytics and less than three years of related experience.

Cloudera Certified Professional (CCP) Data Engineer

Cloudera describes its Certified Professional (CCP) Data Engineer credential as one of the most stringent and "demanding performance-based credentials." According to Cloudera, candidates for the CCP Data Engineer certification should have extensive expertise in data engineering and a "high level of mastery" of common data science abilities. The test consists of five to ten performance-based hands-on tasks on a Cloudera Enterprise cluster that has been configured. The exam will last four hours and you must get a score of 70% or better to succeed.

Dell EMC Data Science Track (EMCDS)

The Dell EMC Data Scientist Track (EMCDS) consists of two certification programs: the Data Science Associate v2 (DCS-DS) and the Data Science Specialist (DCS-DS). At the associate degree level, you'll study the fundamentals of data science and big data analytics – courses are available in-person or online. After completing the associate's degree program, you can progress to the specialist's degree program, which covers topics such as natural language processing, advanced analytical methods, Hadoop, Pig, Hive, HBase, and visualization approaches.

Data Science Council of America (DASCA) Senior Data Scientist (SDS)

Senior Data Scientist (SDS) credential from the Data Science Council of America (DASCA) is intended for individuals with at least five years of expertise in research and analytics. Students should have a working grasp of databases, spreadsheets, statistical analysis, SPSS/SAS, R, quantitative methodologies, and the principles of object-oriented programming and relational databases. The program is divided into five tracks that will appeal to a variety of people – each track has its own set of requirements for degree level, work experience, and application prerequisites. Each route requires at least a bachelor's degree and more than five years of expertise in data science, while others demand a master's degree or previous certifications.

Data Science Council of America (DASCA) Principal Data Scientist (PDS) 

The Data Science Council of America (DASCA) offers the Principal Data Scientist (PDS) certification, which is divided into three tracks for data science professionals with ten years or more of experience working with large data. The test covers fundamental to advanced data science principles, including big data best practices, data-driven business strategies, cross-organizational assistance, machine learning, natural language processing, and scholastic modeling. The exam is intended for "seasoned and high-achievers in the field of data science thought and practice."

Google Professional Data Engineer Certification

The Google Professional Data Engineer certification is best suited for individuals who have a firm understanding of the Google Cloud Platform (GCP) and experience creating and managing GCP-based solutions. The exam will assess your ability to design, develop, secure, and operate machine learning models and data processing systems. At a minimum, three years of industry experience is recommended, including one year or more of creating and managing systems utilizing GCP.

Open Certified Data Scientist (Open CDS)

The Open Group's Professional Certification Program for Data Scientists (Open CDS) is an experience-based certification program that does not require traditional training or examinations. You'll begin as a Certified Data Scientist, progress to Master Certified Data Scientist, and finally, pass the third level to become a Distinguished Certified Data Scientist. Certification needs a three-step process that includes applying for the certification, submitting an application for experience, and attending a board review.

IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate is comprised of nine courses covering data science fundamentals, open source tools, data science methodology, Python, databases and SQL, data analysis, data visualization, and machine learning, as well as a final applied data science capstone. The course is delivered online via Coursera and requires an average of three months to complete, but students are free to take more or less time. The course contains hands-on projects that will assist you in developing a portfolio to demonstrate your data science abilities to prospective employers.

SAS Certified AI & Machine Learning Professional

SAS's AI and Machine Learning Professional certification validates your ability to leverage open source tools to extract insights from data utilizing AI and analytics skills. The certification is comprised of many tests that include machine learning, natural language processing, computer vision, and forecasting and optimization of models. To earn the AI & Machine Learning professional title, you must complete the SAS Certified Specialist tests in Machine Learning, Forecasting and Optimization, and Natural Language Processing and Computer Vision.