Learn how to stay relevant as a data scientist through professional development by analyzing various opportunities available to you, such as certifications, Professional Development Units (PDUs), and networking activities through conferences and workshops.
- There are scientists need to stay abreast of new developments in both their specialty and discipline, at large, as well as the overall IT world. The breadth of the knowledge requirements for them is quite wide because data science builds on many of its underlying IT technologies, such as data infrastructure, and management. For example, one of the emerging data science technologies is in-memory analytics. Which means, running entire data analytics operations in the main memory of a computer instead of reading some of the data back and forth, from a secondary memory device.
Such as an external storage device. As a data scientist, you need to know the implications of this relatively new technology in your job, on a daily basis, and make a decision on whether to adopt it now or later. As you may already be well aware there are a number of ways to keep current with the latest developments in your field of expertise. One of the ways to force yourself to do this is to get certified.
After getting your certification, such as certified analytics professional, or CAP, you need to get recertified by acquiring a certain number of professional development units or PDUs, every once in awhile. Networking with other data science professionals by participating in conferences and workshops is another great way of keeping up to date with your profession. After all, these activities are what makes your job more exciting and fun.
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and analytics, explores which markets are using big data the most, 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 four 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 analytics is important
- How data science is used in social media, climate research, and more
- Data science skills
- Data science certifications
- The future of big data