The old saying “knowledge is power” still holds true in today’s day and age, where data is knowledge or information, and thereby data is power. Data has proliferated every nook and corner of the globe and the very aspect of human existence by driving massive technological advancement through a data revolution.
It is not presumptuous to assert that data is the fuel that powers the world, and who better than data scientists to tame the data to derive meaningful insights that can revolutionize the world with brainstorming ideas and manifold applications?
What precisely is data science, then, and why is it still one of the top job profiles in the IT industry? The process of using cutting-edge scientific methods and procedures to clean, collect, and organize data to extract useful information, which can subsequently be utilized to support strategic planning and wise business decisions, is known as data science.
Thus, every organization is keen to hire skilled data scientists who can sort through massive quantities of data to produce quality data, which is what data science is all about in simple terms.
What are the benefits of having data science certifications?
Data science is a field that is constantly evolving, particularly in terms of tools and technology, and as such, it is a discipline that requires the continuous updating of existing knowledge as well as the installation of new skills.
While a relevant degree can help you build a solid foundation of knowledge, obtaining the appropriate data science certification can help you hone specialized skills that you might not learn on the job. Furthermore, it can serve to validate your expertise and knowledge of the field, which can help you stand out in a pool of like-minded professionals in front of recruiters.
Certification demonstrates to recruiters the amount of conviction and effort the individual has put in to meet the exam’s standards, which exemplifies a sense of authenticity and professional acumen. Furthermore, certifications are an excellent way to secure top positions, higher pay, and more career opportunities.
So, do you aspire to be a data scientist? Then, this article will walk you through some of the best data science certifications available today and will help you figure out which is the best institute for data science for you.
1. The Certified Analytics Professional (CAP) certification
The Certified Analytics Professional (CAP) certification is a vendor- and technology-neutral certification that is widely regarded as the gold standard in data science. For those considering a career in data science and analytics, the CAP certification attests to the professional’s expertise in seven domains of data analytics as well as your ability to derive meaningful insights from complex data. Having a CAP certification in your name not only helps you stand out amongst your peers but also proves to recruiters that you have top analytical talent and expertise. You must pass the Associate Certified Analytics (aCAP) Professional exam to obtain the CAP certification.
The eligibility requirements for the CAP certification exam state that you must have three years of work experience in a related field if you have a master’s degree in that field, five years of work experience in a related field if you have a bachelor’s degree in that field; and seven years of work experience in a related field if you have any other degree that is not related to analytics.
2. The Senior Data Scientist (SDS) certification by DASCA
The Data Science Council of America (DASCA) offers the prestigious SDS certifications to professionals with 4+ years of experience in research and analytics and a bachelor’s/degree master’s in data science or a related discipline. The certification expedites your path to becoming a data leader, data architect, or business intelligence expert. The certification prerequisites necessitate a thorough understanding of 4IR technology trends as well as an advanced understanding of the intersections of data science with other branches of computer science, engineering, business, and industry.
The rigorous nature of the SDS program requires candidates to demonstrate advanced knowledge of Statistical Analysis techniques and tools, analytics platforms such as SPSS/SAS, R, quantitative methods, RDBMS, object-oriented programming languages such as C++, Core JAVA, as well as working knowledge of the Linux and Unix environments and handling of databases and spreadsheets.
The exam covers everything from fundamental to advanced data science concepts such as Data Science Essentials, Data Science Applications in Business, The Functional Framework of Data Science, Building Pan-Organization Support, Big Data analytics essentials, advanced data science topics such as stochastic modeling, data structures, machine learning. The certification is validated in seven essential knowledge dimensions and 30 core professional knowledge subjects. The SDS certification is divided into five paths with varying levels of experience.
3. The Principle Data Scientist (PDS) certification by DASCA
The Principle Data Scientist certification, which is both a qualification-credential and a professional designation, is one of the top-ranked data science certifications for senior professionals offered by DASCA. This program has four paths, each of which requires at least ten years of professional data science experience. The certification focuses on advanced technology and analysis for complex subjects. Each path costs more than most tests, but this certification has no expiration date.
4. Open Certified Data Scientist (Open CDS)
Open CDS is a global certification based on independent experience that validates Data Scientists’ technical prowess, knowledge, and expertise. Having an Open CDS certification to your name demonstrates that you have the tenacity and skill set required to generate efficient data analyses for driving your organization’s business in a positive direction to success. Candidates for the open CDS certification must.
To qualify for the exam, candidates do not need to attend training sessions or take written tests. The certification is awarded through written applications and peer interviews in which candidates must demonstrate their knowledge and experience in accordance with a set of conformance requirements. You will achieve three certifications as you progress through the CDS certification process.
Level 1: Certified Data Scientist
Level 2: Master Certified Data Scientist
Level 3: Distinguished Certified Data Scientist
5. Microsoft Certified: Azure Data Scientist Associate
The Microsoft Azure Data Scientist Associate certification places a strong emphasis on your capacity to implement and run machine learning workloads on the Azure cloud platform using data science and machine learning. This certification is a subset of the Microsoft Azure family. It covers topics including machine learning (ML), artificial intelligence (AI) solutions, natural language processing (NLP), computer vision, and predictive analytics while being an entry-level certification. You must be adept in a variety of related responsibilities, including designing and managing virtual networks, deploying and managing resources, managing identities and governance, installing and managing storage, and more.
6. SAS Certified Data Scientist Certification
The SAS Certified Data Scientist credential combines various SAS data credentials. To complete the coursework and qualify for the SAS Data Science credential, pair the SAS Data Curation credential with either the Advanced Analytics Professional or the AI & Machine Learning Professional credential. The credentials cover topics such as data science principles, data management, data analysis and data manipulation, machine learning, programming skills, and predictive modeling.
It is designed to be a hands-on data scientist certification for those who use data visualization tools, as well as third-party analysis tools like Hive/HiveQL, Hadoop, and PIG/PIGLATIN and machine learning models, to extract insights from massive amounts of data and then apply that knowledge to real-world problems.