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
Skill Level Appropriate for all
- [Voiceover] Hi, I'm Jung Ryoo, and welcome to Data Science Career Path and Certifications. This course will help you take your first step towards preparing yourself to enter a successful career in data science. I'll start by going over the history of data science and major concepts behind it, such as big data, machine learning, data mining, and data analytics. Then show you various data science marketplaces, such fraud detection, social media analytics, disease control, dating services, simulations, climate research, and network security.
We'll also check out skills required for data science jobs, including data mining and analytics, machine learning, natural language processing, statistics, and visualization. In addition, I'll be covering certification opportunities available in data science. Certifications include MCSE Business Intelligence, Cloudera Certified Professional Data Scientist, EMC Data Science Associate, and Oracle Business Intelligence Certificate. Now let's get started with Data Science Career Path and Certifications.
1. Define Data Science
6. Future of Big Data
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