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
- We have so much information out there on data science and analytics career paths, however, there is very little in terms of how you can get started with your first step. Hi, I'm Jungwoo Ryoo, and as a college professor, I've seen many students struggling and being overwhelmed when they're beginning to pursue their career. I feel that data science and analytics is giving you a similar challenge, especially when you are new to the field.
I'll start by going over the history of data science and major concepts behind it. Since there is a huge demand in the data science marketplace, we'll cover the skills you will need that your perspective employers are looking for. Then I'll address how you can add value to your team by executing your role extremely well and demonstrate your proficiency through certifications. Your future will be a promising one as long as you keep up with your profession and enjoy the challenges that await you.
Let's take our first step.
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