Learn how data science can drive and enhance simulations by defining different types of simulations and evaluating the value of data-driven simulations, especially in terms of their enhanced accuracy and predictive power. Explore how the field of climatol
- [Voiceover] Simulations imitates the operative of…a real world system.…The true power of simulation comes from…its predictive nature.…A computer simulation can completely rely…on a mathematical model,…can be interpreted into an algorithm,…and then finally implemented into a piece of code.…A physics engine used for gaming,…is an excellent example of this.…This purely model-driven simulation is not always accurate…and can misrepresent what can happen in the real world.…
Which is why data science can play…an important role in simulations.…By feeding real life data into a simulation model,…scientists can improve…the accuracy of a simulation drastically.…In addition to the improved accuracy,…the simulation model aided by this infusion of…a large amount of real-life data…can also significantly enhance its predictive power.…For example, the field of Climatology…is one of the beneficiaries of the recent progresses…of big data analytics.…
Now, meteorologists can predict…future weather patterns with much more accuracy.…In fact, it is becoming quite feasible…
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
Learning Data Science: Understanding the Basicswith Doug Rose1h 16m Appropriate for all
1. Define Data Science
6. Future of Data Science
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