As the demand for data science professionals is increasing, there is a challenge faced by recruiters around the world. This challenge is of hiring potential candidates who have all the required skills. There is more satisfaction required at the end of recruiters and hiring managers as they know the challenge to identify the knowledge and skills of a person in a few hours of the interview. For this reason, a person who is having a professional certification gets more weightage at the time of consideration.
What is a Professional Certification?
A professional certification is a distinction or a designation that is earned by a person as an assurance of a certain qualification or proven skill. The certification is an attestation of a person’s knowledge or proficiency in a certain subject or profession. A certification may be issued by an educational institution or by any professional body or society. The certification helps a person in showcasing their skills to the recruitment panel.
The Difference Between a Training and a Professional Certification
There is a big difference between training and certification. The training program aims to train a person on a specific skill or subject. The training usually takes time from a couple of months to more than a year. The trainee person needs to pay a decent amount of fees towards getting training. At the end of the training, the institution provides a training completion certificate to the candidate. Some training programs end with a test and provide a certificate to only those candidates who have passed the test.
On the other hand, a professional certification program is provided by professional bodies and these are not supported by any training. The candidates need not invest any time in getting trained first to earn the certificate. They also need not invest any amount of money in availing training. A professional certification is meant for professionals working in that particular area. The candidates can prepare on their own for a professional certification exam.
Certifications in Data Science
Here we list down the top premier global professional certifications and designations in data science.
This distinction is provided by the Association of Data Scientists (ADaSci). This designation is awarded to those candidates who pass the CDS exam and hold a minimum of two years of work experience as a data scientist. However, the candidates who do not have experience can also take the exam and carry the results. But their charter, in this case, is put on hold until they attain the two years of experience. There is no training or course required to earn this award. The cost of taking this exam is 250 US Dollar. This charter has lifetime validity and hence it does not expire.
The Chartered Financial Data Scientist program is organized by the Society of Investment Professionals in Germany. They first provide a training course conducted by the Swiss Training Centre for Investment Professionals. After completing this training, the candidates are allowed to earn this designation. It costs around 8,690 Euro.
This professional certification is offered by INFORMS. It is supported by the Canadian Operational Research Society and 3 more professional societies. There are various levels of certification. Each level has different eligibility requirements, from graduate to postgraduate etc. To earn this certification, the cost starts from 495 US Dollar. To take this exam, the candidate needs to be available in-person in the designated test centres. It is valid for three years only.
This certification program is organized by Cloudera. It is more specific towards SQL and databases and more suitable for Data Analysts. It costs around 295 US Dollar and there is no any specific eligibility requirement for this certification. This certification is valid only for two years.
This certification program is organized by Dell EMC. To earn this distinction, it is mandatory to attend a training program, either in-class or online. It costs around 230 US Dollar. To take this exam, the candidate needs to be available in-person in the designated test centres.
It is organized by the Open Group. The members of the Open Group include HCL, Huawei, IBM, Oracle etc. There are 3 levels of this certification. Require to have a different level of experience for each level of certification. The cost for this certification starts from 295 US Dollar. To take this exam, the candidate needs to be available in-person at the specified place.
This certification program is provided by the Data Science Council of America (DASCA). It requires 6+ years of experience of Big Data Analytics / Big Data Engineering. It costs around 650 US Dollar. This certification has 5 years of validity.
This certification program is provided by the Data Science Council of America (DASCA). It requires 10+ years of experience of Big Data Analytics / Big Data Engineering. There are various tracks of this exam. It costs between 850-950 US Dollar depending on the track.
It is organized by SAS. To get this certification, you need to pass two more exams first SAS Big Data Professional and SAS Advanced Analytics Professional. Along with this, you need to take 18 courses as well. It costs around 4,400 US Dollar.
Financial Data Professional program is organized by Financial Data Professional Institute (FDPI). It is more suitable for financial professionals who apply AI and data science in finance. It opens the exam window with a fixed registration period. The cost of the FDP exam is 1350 US Dollar. To take this exam, the candidate needs to be available in-person in the designated test centres.
So, here we have listed the top certification exams in data science across the world. To choose from the list, a candidate should analyze the requirements in the coming future, the suitability of certification, contents covered in the exam so that it can meet the job requirements, exam cost, exam dates and time flexibility etc. The candidate should take one such certification which meets all their expectations instead of taking multiple certification exams.
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Vaibhav Kumar has experience in the field of Data Science and Machine Learning, including research and development. He holds a PhD degree in which he has worked in the area of Deep Learning for Stock Market Prediction. He has published/presented more than 15 research papers in international journals and conferences. He has an interest in writing articles related to data science, machine learning and artificial intelligence.