Data Science at U of U
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1 Data Science at U of U Je M. Phillips Assistant Professor, School of Computing Center for Extreme Data Management, Analysis, and Visualization Director, Data Management and Analysis Track University of Utah enormous noisy squashing working mining draw conclusion
2 make hypothesis Classic Scientific Paradigm
3 Classic Scientific Paradigm make hypothesis gather
4 Classic Scientific Paradigm make hypothesis gather compute statistics
5 Classic Scientific Paradigm make hypothesis gather compute statistics draw conclusion
6 Classic Scientific Paradigm make hypothesis gather compute statistics draw conclusion
7 enormous noisy Modern Data Science
8 Modern Data Science enormous noisy squashing working
9 Modern Data Science enormous noisy squashing working mining
10 Modern Data Science enormous noisy squashing working mining draw conclusion
11 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error
12 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error Tools Hadoop! Data Munging Tool Boxes (R, SciKit) Illustrations and Plots
13 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error Tools Hadoop! Data Munging Tool Boxes (R, SciKit) Illustrations and Plots Fundamentals Databases (no SQL) Modern Machine Learning & Data Mining Visualization & Statistics
14 Data Science
15 Machine Learning Statistics Visualization Data Science Databases Data Mining
16 Machine Learning Statistics Data Scientist Visualization Data Science Databases Data Mining
17 Computing at U.Utah View Fundamentals
18 Computing at U.Utah View Fundamentals Databases
19 Computing at U.Utah View Fundamentals Databases Disk Disk Disk Disk Disk Disk CP U CP U CP U CP U CP U CP U
20 Computing at U.Utah View Fundamentals Databases Data Mining
21 Computing at U.Utah View Fundamentals Databases Data Mining Machine Learning
22 Computing at U.Utah View Fundamentals Databases Data Mining Machine Learning Visualization
23 Computing at U.Utah View Fundamentals Databases Data Mining Machine Learning Visualization Advanced Topics Distributed Systems Networking Randomized Massive Data & Streaming Bayesian Modeling Natural Language Processing Information Retrieval Structured Prediction Visual Analytics
24 Computing at U.Utah View Fundamentals Advanced Topics Applications & Research Databases Distributed Systems Scientific Computing Networking Data Mining Machine Learning Visualization Randomized Massive Data & Streaming Bayesian Modeling Natural Language Processing Information Retrieval Structured Prediction Visual Analytics Image Analysis Simulated Science Energy Engineering Social Science Advertising Science
25 Computing at U.Utah View Fundamentals Advanced Topics Applications & Research Databases Distributed Systems Scientific Computing Networking Data Mining Machine Learning Visualization Randomized Massive Data & Streaming Bayesian Modeling Natural Language Processing Information Retrieval Structured Prediction Visual Analytics Image Analysis Simulated Science Energy Engineering Social Science Advertising Science Graduate Certificate in Big Data
26 Computing at U.Utah View Fundamentals Advanced Topics Applications & Research Databases Distributed Systems Scientific Computing Networking Data Mining Machine Learning Visualization Randomized Massive Data & Streaming Bayesian Modeling Natural Language Processing Information Retrieval Structured Prediction Visual Analytics Image Analysis Simulated Science Energy Engineering Social Science Advertising Science Graduate Certificate in Big Data MS in Data Management & Analysis
27 Computing at U.Utah View Fundamentals Advanced Topics Applications & Research Databases Data Mining Machine Learning Visualization Graduate Certificate in Big Data Distributed Systems Networking Randomized Massive Data & Streaming Bayesian Modeling Natural Language Processing Information Retrieval Structured Prediction Visual Analytics MS in Data Management & Analysis Image Analysis Simulated Science Energy Engineering Scientific Computing Social Science Advertising Science + lots of research, thesis PhD in Data Management & Analysis
28 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error Big Data, Big Questions 1. If we get good enough at finding pattern, will we find patterns that are not there? (False Discovery)
29 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error Big Data, Big Questions 1. If we get good enough at finding pattern, will we find patterns that are not there? (False Discovery) 2. Can you analyze big without violating personal privacy?
30 Modern Data Science enormous noisy squashing working mining draw conclusion model uncertainty and bound error Big Data, Big Questions 1. If we get good enough at finding pattern, will we find patterns that are not there? (False Discovery) 2. Can you analyze big without violating personal privacy? 3. As we get more sources of, how will we know which to trust?
31 Teaching Data Science 3 Bold Proclomations 1. Data Science should be taught in Computer Science departments. (others can teach domain specific tools)
32 Teaching Data Science 3 Bold Proclomations 1. Data Science should be taught in Computer Science departments. (others can teach domain specific tools) 2. Every domain of Science & Engineering will center on Data Science in 5 years.
33 Teaching Data Science 3 Bold Proclomations 1. Data Science should be taught in Computer Science departments. (others can teach domain specific tools) 2. Every domain of Science & Engineering will center on Data Science in 5 years. 3. All of Data Science will be applying Machine Learning in 10 years.
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