No matter whether you are planning to build a career in data science or not, you may have heard of this common saying that “Data Scientist the sexiest job of the 21st century.” I am not eager to explain why, but one thing is for sure that when someone is getting hired as a data scientist, recruiters examine every single detail of their skillset before they hire him. And the next important thing what all certifications for data scientists he has bagged already. Now, why am I focused on data science today?
Not to mention, data science is the hottest job in IT this time because data scientists are important to almost every company. Also, data science is a broad field. Certifications for data scientists provide one with proof of the qualities and knowledge he possesses. Simultaneously, certifications for data scientists help one hone niche skills required for a particular industry. Furthermore, if you have gained excellence in the field and gained top certifications, trust me, no one can stop you in the market to get hired as a data scientist.
This blog will provide you a complete list of top data science certifications that will help you to lift your career.
Related post – Data science vs. Big data vs. Data analysts
Skills that data scientists need
Before deep dive into the part of the certifications, let me give you an overview of the required skills as a data scientist. Data science is a multidisciplinary stream that involves many things; some of them are like
- Visualization
- Data mining
- Machine learning
- Statistics
- Pattern recognition
Source: Quora
Knowledge wise, as defined by Hugh Conway in 2010 through a Venn diagram, data science is a combination of mathematics, statistics, subject expertise, and hacking skill.
Venn Diagram
Source: Drew Conway
A data scientist must be proficient enough in –analytics, programming, and domain knowledge. Furthermore, the following skills will help one carve out a niche as a data scientist:
– Strong programming knowledge of Python, SAS, R, Scala
– Practical experience in SQL database coding
– Familiarity with unstructured data and, at the same time, the ability to work with it irrespective of the sources of data.
– Concepts of multiple analytical functions
– Knowledge of machine learning
Top 8 Certifications for Data scientists
1. IBM Data Science Professional Certification
Duration — Approx 12 months (flexible)
Level — Beginner
Platform — edx/coursera
Mode- self paced
You get: Certificates and digital badge
What you will learn
- Apply various Data Science and Machine Learning skills, techniques, and tools to complete a project and publish a report.
- Practice with various tools used by Data Scientists and become experienced in using some of them like Jupyter notebooks.
- Master the key steps involved in tackling a data science problem and learn to follow a methodology to think and work like a Data Scientist.
- Write SQL to query databases and explore relational database concepts.
- Understand Python and practice Python programming using Jupyter.
- Import and clean data sets, analyze data, build and evaluate data models and pipelines using Python.
- Utilize several data visualization tools, techniques, and libraries in Python to present data visually.
- Understand and apply variously supervised and unsupervised Machine Learning models and algorithms to address real-world challenges using Python.
[Ref: https://www.edx.org/professional-certificate/ibm-data-science ]
Courses
- What is Data Science?
- Open Source tools for Data Science
- Data Science Methodology
- Python for Data Science and AI
- Databases and SQL for Data Science
- Data Analysis with Python
- Data Visualization with Python
- Machine Learning with Python
- Applied Data Science Capstone
The certification requires no pre-requisites. However, for a better grasp of learning, doing a crash course on Python beforehand would be helpful.
Job outlook:
- Over 2.5 million jobs in data science and related professions (Burning Glass)
- Python most popular language for data science (KDnuggets)
Access the certification: Link1 – coursera, Link2- edx
2. HarvardX’s Data Science Professional Certificate
Duration — 1 year 5 months (flexible)
Level — Beginner
Platform — edX
Mode – Self paced
This program was supported in part by NIH grant R25GM114818. As per HarvardX policy, individuals who enroll in these courses on edX must abide by the edX honor code’s terms. HarvardX will take appropriate corrective action in response to violations of the edX honor code, including dismissal from the HarvardX course, revoking any certificates received for the HarvardX course or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Those programs’ academic policies will also govern enrollment enrollees taking HarvardX courses as part of another program.
What you will learn
- Build a foundation in R and learn how to wrangle, analyze, and visualize data.
- Learn basic data visualization principles and how to apply them using ggplot2.
- Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007-2008.
- Learn inference and modeling, two of the most widely used statistical tools in data analysis
- Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.
- You will learn to process and convert raw data into formats needed for analysis in the wrangling part.
- Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.
- Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
- Show what you’ve learned from the Professional Certificate Program in Data Science
The best part about this certification is the course touching base on essential tools for practicing data scientists such as Unix/Linux, Git and GitHub, and RStudio.
Another crest for this certification is its realism — the courses introduce the learners to motivating real-world case studies in the likes of —
- Trends in World Health and Economics
- US Crime Rates
- The Financial Crisis of 2007–2008
- Election Forecasting
- Building a Baseball Team (inspired by Moneyball)
- Movie Recommendation Systems.
Job outlook:
- R is a required skill in 64% of data science job postings and was Glassdoor’s Best Job in America in 2016 and 2017. (source: Glassdoor)
- Companies are leveraging the power of data analysis to drive innovation. Google data analysts use R to track trends in ad pricing and illuminate patterns in search data. Pfizer created customized packages for R so scientists can manipulate their own data.
Access the certification: Link
3. Amazon AWS Certified Machine learning – Specialty
Exam format – Multiple choice
Delivery mode –Testing centre or Online proctored
Time – 180 minutes
Cost – 300 USD
Data scientists’ learning paths as guided by the AWS defines the role of data scientists who role and build the models using machine learning, create and work on algorithms, and train predictive models to achieve business goals.
Now if we look into AWS certifications stack then two relevant certifications fall under this category:
- AWS Certified Machine learning – Specialty
- AWS Certified Data analytics – specialty (Formerly known as – AWS Certified Big Data – Specialty)
The AWS Certified Machine Learning – Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate’s ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems.
What are validated by this certification?
- Select and justify the appropriate ML approach for a given business problem
- Identify appropriate AWS services to implement ML solutions
- Design and implement scalable, cost-optimized, reliable, and secure ML solution
Pre-requisites
- 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud
- The ability to express the intuition behind basic ML algorithms
- Experience performing basic hyperparameter optimization
- Experience with ML and deep learning frameworks
- The ability to follow model-training best practices
- The ability to follow deployment and operational best practices
Access the Certification: Link
4. AWS Certified Data analytics – specialty
Exam format – Multiple choice
Delivery mode –Testing centre or Online proctored
Time – 180 minutes
Cost – 300 USD
Earn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data.
What does it validate?
- Define AWS data analytics services and understand how they integrate
- Explain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualization
Pre-requisites
- At least 5 years of experience with data analytics technologies
- At least 2 years of hands-on experience working with AWS
Experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions
Access the Certification: Link
5. Microsoft Certified Azure Data Scientist Associate
Duration — 180 minutes exam
Level — Advanced
Platform — Microsoft
Price — $165
Total Questions — 51
Type — Single and multi-choice questions (~50% questions from ML studio, 40% from ML service & 10% generic data science questions.)
The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service. This exam measures your ability to accomplish the following technical tasks: set up an Azure Machine Learning workspace, run experiments and train models, optimize and manage models, and deploy and consume models.
Skills Measured
- Set up an Azure Machine Learning workspace (30–35%)
- Run experiments and train models in Azure (25–30%)
- Optimize and manage Azure built models (20–25%)
- Deploy and consume the production-ready models (20–25%)
You are offered three learning paths guided by Microsoft for the certification-
- Create Machine learning models
- Create a no-code predictive model using Azure Machine learning
- Build AI solutions with Azure machine learning
Learning path as specified by Azure is as follows:
Access the certification: Link
6. Dell EMC Data Scientist, Advanced Analytics
This certification is divided into two levels.
- Associate level
- Specialist level
Associate level– This learning path is aligned to and supports Associate – Data Science Certification. The course(s) in this learning path provides practical foundation level training that enables immediate and effective participation in big data and other analytics projects. This exam focuses on the practice of data analytics, the role of the Data Scientist, the main phases of the Data Analytics Lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques. Successful candidates will achieve the Dell EMC Proven Professional – Data Science Associate credential.
For exam topics and recommended training, please refer to this document as provided by Dell EMC. The Data Science and Big Data Analytics course prepare you for Data Scientist Associate v2 (DCA-DS) Certification.
Specialist level – This certification is designed to build on the skills developed in the Associate level course in Data Science (Data Science & Big Data Analytics) and help aspiring Data Scientists continue to evolve and expand their skill sets. The main growth areas include advanced analytical methods, Hadoop (and Pig, Hive, HBase), Social Network Analysis, Natural Language Processing, and Visualization methods. The development of these skills and the use of these methods provide the data scientist the ability to identify and communicate conclusions and recommendations in order to solve business challenges across many domains.
Pre-requisite – Associate level certification
For topic details and recommendations please refer to this document as provided by Dell EMC.
Job outlook
- 73% of transformation ready individuals said that training and certification make them more effective.
- 23% received a salary increase after certifying.
- 86% of IT hiring managers place a medium or high value on IT certification when selecting a candidate.
- 94% recommend Dell Technologies training and certification.
7. Dell EMC Data Scientist – Data Engineering
Like Data Scientist, Advanced Analytics, this certification is also divided into associate and specialist levels. You can find the details of the topics here for associate level and specialist level in this link.
8. SAS® Certified Data Scientist
Duration — Few months to several years
Cost — $250
Level — Advanced
Platform — SAS Academy for Data Science
Designed for individuals who can manipulate and gain insights from big data with a variety of SAS and open source tools, make business recommendations with complex machine learning models, and then deploy models at scale using the flexible, robust SAS environment.
What are the focused areas of the SAS data scientist exam?
- Data curation
- Advanced analytics
- AI and Machine learning
Candidates who earn this credential will be required to have earned either the SAS Certified Data Curation Professional or the SAS Certified Big Data Professional and either the SAS Certified Advanced Analytics Professional or the SAS Certified Professional AI and Machine Learning credentials.
Job prospect:
Three professional level credentials are acquired as part of the certification. Hence, you are not only launching your career but also transforming your future.
Access the certifications: Link
Summary
It is high time for data science roles. Data science is mushrooming right now, and there are no signs of subsiding anytime soon. So, if you love data, then better make the most out of it now. Also, data science is waiting for you! Most of the article parts are taken from the exact sites to deliver the latest and authentic information. I hope you will enjoy it!