Learn about the key certifications sought after within the industry.
- As the field of data science and analytics matures,…we're seeing more certification opportunities…becoming available.…Just like any professionals out there,…data scientists can establish more credibility…in what they're capable of by earning…well-known certifications in their field.…There are myriads of certification opportunities…available, and the number is growing as we speak.…
The key here is not how many certifications you have…but how many relevant skills you can demonstrate…through the certifications you have.…Many of the certifications also require…significant industry experience, therefore,…it is important for you to pick and choose…the best ones that fit your own needs.…If you're a student who is about to graduate,…your best bet would be certifications…that do not require any experience in the industry.…
For example, the Certified Analytics…Professional certification allows an associate CAP option…so that students can pass the exam portion…of the certification requirements…without any industry experience…
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and its subfields, explores the marketplaces for these fields, and reveals the five main skills areas: data mining, machine learning, natural language processing (NLP), statistics, and visualization. This leads to a discussion of the five biggest career opportunities, the six leading industry-recognized certifications available, and the most exciting emerging technologies. Along the way, Jungwoo discusses the importance of ethics and professional development, and provides pointers to online resources for learning more.
- A history of data science
- Why data analytics is important
- How data science is used in fraud detection, disease control, network security, and other fields
- Data science skills
- Data science roles
- Data science certifications
- The future of data science
Skill Level Beginner
Insights on Data Science: Lillian Piersonwith Lillian Pierson, P.E.23m 51s Intermediate
1. Define Data Science
6. Future of Data Science
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