Author
Released
1/26/2018Jungwoo 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
Duration
Views
- 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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Introduction
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Welcome1m 9s
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1. Define Data Science
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Introduction1m 24s
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A brief history2m 37s
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Fundamentals3m 15s
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Big data analytics1m 44s
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Enabling technologies2m 51s
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2. Marketplace
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Introduction to marketplace1m 26s
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Fraud detection2m 5s
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Social media analytics2m 9s
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Disease control1m 24s
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Dating services1m 50s
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Simulations1m 28s
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Climate research1m 24s
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Network security1m 16s
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3. Skills
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Required skills2m 42s
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Data mining and analytics1m 49s
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Machine learning1m 33s
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Statistics1m 10s
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Visualization1m 35s
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4. Roles
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Introduction to roles1m 49s
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Data scientist or engineer1m 48s
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Data visualization developer2m 26s
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Salaries1m 32s
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5. Certifications
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6. Future of Data Science
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Emerging technologies1m 44s
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Emerging careers1m 34s
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Ethics1m 51s
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Professional development1m 45s
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Conclusion
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Video: Welcome