Data Science and Analytics Curriculum development at Rensselaer (and the Tetherless World Constellation) - PowerPoint PPT Presentation

Loading...

PPT – Data Science and Analytics Curriculum development at Rensselaer (and the Tetherless World Constellation) PowerPoint presentation | free to download - id: 69bed3-NmFkM



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Data Science and Analytics Curriculum development at Rensselaer (and the Tetherless World Constellation)

Description:

Title: PowerPoint Presentation Author: Peter Darnell Last modified by: Peter Fox Created Date: 12/6/2010 3:12:21 PM Document presentation format: On-screen Show (4:3) – PowerPoint PPT presentation

Number of Views:49
Avg rating:3.0/5.0

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Data Science and Analytics Curriculum development at Rensselaer (and the Tetherless World Constellation)


1
Data Science and Analytics Curriculum development
at Rensselaer (and the Tetherless World
Constellation)
  • NRC BigData Education Workshop
  • April 11-12, 2014, Washington DC

Peter Fox (RPI and WHOI/AOPE) pfox_at_cs.rpi.edu,
_at_taswegian Tetherless World Constellation,
http//tw.rpi.edu twcrpi Earth and Environmental
Science, Computer Science, Cognitive Science, and
IT and Web Science
2
Data is a 1st class citizen
http//thomsonreuters.com/content/press_room/scien
ce/686112
3
tw.rpi.edu
  • Future Web
  • Web Science
  • Policy
  • Social

Hendler
Research Themes
  • Xinformatics
  • Data Science
  • Semantic eScience
  • Data Frameworks

Fox
McGuinness
  • Semantic Foundations
  • Knowledge Provenance
  • Ontology Engineering Environments
  • Inference, Trust

Multiple depts/schools/programs 35 (Post-doc,
Staff, Grad, Ugrad)
4
  • Govt. Data
  • Open
  • Linked
  • Apps

Hendler/ Erickson
Application Themes
  • Env. Informatics
  • Ecosystems
  • Sea Ice
  • Ocean imagery
  • Carbon

Fox
McGuinness
Platforms Bio-nano tech center Exp. Media and
Perf. Arts Ctr. Center for Comput.
Innovation Institute for Data Exploration and
Applications http//idea.rpi.edu
  • Health Care/ Life Sciences
  • Population Science
  • Translational Med
  • Health Records

5
http//tw.rpi.edu/web/Courses
GIS4Science Data Analytics
Context
Experience
Data
Information
Knowledge
Presentation Organization
Integration Conversation
Creation Gathering
5
Web Science
6
I teach and am involved
  • Data Science, Xinformatics, GIS for the
    Sciences, Semantic eScience, Data Analytics,
    Sematic Technologies
  • School of Science
  • ITWS and EES curriculum committees, SoS CC
  • EES international student advisor
  • Institute Faculty Fellow
  • Institute-wide
  • New Digital Humanities program
  • Institute for Data Exploration and Applications

7
Data Science/ Xinformatics
  • Science has fully entered a new mode of
    operation. Data science is advancing inductive
    conduct of science driven by the greater volumes,
    complexity and heterogeneity of data being made
    available over the Internet. Data science
    combines of aspects of data management, library
    science, computer science, and physical science
    using supporting cyberinfrastructure and
    information technology. As such it is changing
    the way all of these disciplines do both their
    individual and collaborative work. Data science
    is helping scientists face new global problems of
    a magnitude, complexity and interdisciplinary
    nature whose progress is presently limited by
    lack of available tools and a fully trained and
    agile workforce. At present, there is a lack
    formal training in the key cognitive and skill
    areas that would enable graduates to become key
    participants in e-science collaborations. The
    need is to teach key methodologies in application
    areas based on real research experience and build
    a skill-set. At the heart of this new way of
    doing science, especially experimental and
    observational science but also increasingly
    computational science, is the generation of data.
  • In the last 2-3 years, Informatics has attained
    greater visibility across a broad range of
    disciplines, especially in light of great
    successes in bio- and biomedical-informatics and
    significant challenges in the explosion of data
    and information resources. Xinformatics is
    intended to provide both the common informatics
    knowledge as well as how it is implemented in
    specific disciplines, e.g. Xastro, geo, chem,
    etc. Informatics' theoretical basis arises from
    information science, cognitive science, social
    science, library science as well as computer
    science. As such, it aggregates these studies and
    adds both the practice of information processing,
    and the engineering of information systems. This
    course will introduce informatics, each of its
    components and ground the material that students
    will learn in discipline areas by coursework and
    project assignments.

8
Modern informatics enables a new scale-free
framework approach
9
Mediation generations
Borgmann et al., Cyber Learning Report, NSF 2008
10
Data Analytics Challenge
11
IT and Web Science
  • First IT academic program in U.S.
  • First web science degree program in U.S.
  • BS in ITWS (20 concentrations) and MS in IT (10
    concentrations)
  • PhD in Multi-Disciplinary Sciences
  • http//itws.rpi.edu

12
      Technical Track Courses     Concentrations
Computer Engineering Track ECSE-2610 Computer Components and Operations ENGR-2350 Embedded Control ECSE-2660 Computer Architecture, Networking and Operating Systems Civil Engineering Computer Hardware Computer Networking (hardware focus) Mechanical/Aeronautical Eng.
Computer Science Track CSCI-2200 Foundations of Computer Science CSCI-2300 Introduction to Algorithms CSCI-2500 Computer Organization Cognitive Science Computer Networking (software focus) Information Security Machine and Computational Learning
Information Systems Track CSCI-2200 Foundation of Computer Science CSCI-2500 Computer Organization Four credits from the following CSCI-2220 Programming in Java (2 credits) CSCI-2961 Program in Python (2 credits) CSCI-2300 Introduction to Algorithms (4 credits) ITWS-49XX Web Systems Development II (4 credits) Arts Communication Economics Entrepreneurship Finance Management Information Systems Medicine Pre-law Psychology STS
Web Science Track CSCI-2200 Foundations of Computer Science CSCI-2500 Computer Organization One of the following CSCI-49XX Web Systems Development II Web/Data Course approved by ITWS Curriculum Committee Data Science Science Informatics Web Technologies  
13
CHANGES TO THE MASTERS IN INFORMATION
TECHNOLOGY PROGRAM
  • In Spring 2013 the MS in IT core curriculum was
    revised to include Data Analytics.
  • Networking core classes were replaced with Data
    Analytics core classes Data Science, Database
    Mining, X-informatics, and Data Analytics (a new
    class offered in Spring 2014).
  • The MS in IT program also added two new
    concentrations Data Science and Analytics and
    Information Dominance.
  • The Information Dominance concentration was
    developed for a new Navy program that will be
    educating a select group of 5-10 naval officers a
    year with the skills needed for military
    cyberspace operations. Two officers started in
    Fall 2013 and three began in Spring 2014.

14
MS in IT Required Core Courses
IT Core Area Course Number Course Title Term(s) Offered
Database Systems CSCI-4380 Database Systems Fall/Spring
Data Analytics ITWS-6350 Data Science Fall
Software Design and Engineering CSCI-4440 Software Design and Documentation Fall
Software Design and Engineering ITWS-6400 X-Informatics Spring
Management of Technology ITWS-6300 Business Issues for Engineers and Scientists (Professional Track Only) Fall/Spring
Human Computer Interaction COMM-6420 Foundations of HCI Usability Fall
Human Computer Interaction COMM-696X Human Media Interaction Spring
For the research track, replace ITWS-6300
Business Issues for Engineers and Scientists with
one of the two semester courses ITWS-6980
Masters Project or ITWS-6990 Masters Thesis.
Advanced Core options for students who have
previously completed a Core Course
IT Core Area Course Number Course Title Term(s) Offered
Database Systems CSCI-6390 Database Mining Fall
Database Systems ITWS-6350 Data Science Fall
Database Systems ITWS-696X Semantic E-Science Fall
Data Analytics CSCI-6390 Database Mining Fall
Data Analytics ITWS-6400 X-Informatics Spring
Data Analytics ITWX-696X Data Analytics Spring
Software Design CSCI-6500 Distributed Computing Over the Internet Fall
Software Design ECSE-6780 Software Engineering II Fall
Software Design ITWS-696X Semantic E-Science Fall
Management of Technology MGMT-6080 Networks, Innovation and Value Creation Fall
Management of Technology MGMT-6140 Information Systems for Management Spring
Human Computer Interaction COMM-6620 Information Architecture Spring
Human Computer Interaction COMM-6770 User-Centered Design Fall
Human Computer Interaction COMM-696X Interactive Media Design Summer
15
Two New MS in IT Concentrations
Concentration Course Number Course Name Term(s) Offered
Information Dominance The Information Dominance concentration prepares students for careers designing, building, and managing secure information systems and networks.  The concentration includes advanced study in encryption and network security, formal models and policies for access control in databases and application systems, secure coding techniques, and other related information assurance topics.  The combination of coursework provides comprehensive coverage of issues and solutions for utilizing high assurance systems for tactical decision-making.  It prepares students for careers ranging from secure information systems analyst, to information security engineer, to field information manager and chief information officer.  It is also appropriate for all IT professionals who want to enhance their knowledge of how to use pervasive information in situational awareness, operations scenarios, and decision-making. The Information Dominance concentration prepares students for careers designing, building, and managing secure information systems and networks.  The concentration includes advanced study in encryption and network security, formal models and policies for access control in databases and application systems, secure coding techniques, and other related information assurance topics.  The combination of coursework provides comprehensive coverage of issues and solutions for utilizing high assurance systems for tactical decision-making.  It prepares students for careers ranging from secure information systems analyst, to information security engineer, to field information manager and chief information officer.  It is also appropriate for all IT professionals who want to enhance their knowledge of how to use pervasive information in situational awareness, operations scenarios, and decision-making. The Information Dominance concentration prepares students for careers designing, building, and managing secure information systems and networks.  The concentration includes advanced study in encryption and network security, formal models and policies for access control in databases and application systems, secure coding techniques, and other related information assurance topics.  The combination of coursework provides comprehensive coverage of issues and solutions for utilizing high assurance systems for tactical decision-making.  It prepares students for careers ranging from secure information systems analyst, to information security engineer, to field information manager and chief information officer.  It is also appropriate for all IT professionals who want to enhance their knowledge of how to use pervasive information in situational awareness, operations scenarios, and decision-making.
Information Dominance Select two or three of the following courses Select two or three of the following courses Select two or three of the following courses
Information Dominance ISYE-6180 Knowledge Discovery with Data Mining Spring
Information Dominance CSCI-6960 Cryptography and Network Security I Fall
Information Dominance ITWS-4370 Information System Security Spring
Information Dominance CSCI-4650 Networking Laboratory I Fall/Spring
Information Dominance MGMT-7760 Risk Management Fall
Information Dominance ISYE-4310 Ethics of Modeling for Industrial Systems Engineering Fall
Information Dominance If only two of the above were chosen, select one more of the following courses If only two of the above were chosen, select one more of the following courses If only two of the above were chosen, select one more of the following courses
Information Dominance CSCI-6390 Database Mining Fall
Information Dominance CSCI-6968 Cryptography and Network Security II Spring
Information Dominance CSCI-4660 Networking Laboratory II Fall/Spring
Information Dominance ECSE-6860 Evaluation Methods for Decision Making Fall
Information Dominance ISYE-6500 Information and Decision Technologies for Industrial and Service Systems Fall/Spring
Information Dominance CSCI-496X Computational Analysis of Social Processes Fall
Concentration Course Number Course Name Term(s) Offered
Data Science and Analytics Data and Information analytics extends analysis (descriptive and predictive models to obtain knowledge from data) by using insight from analyses to recommend action or to guide and communicate decision-making. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with an entire methodology. Key topics include advanced statistical computing theory, multivariate analysis, and application of computer science courses such as data mining and machine learning and change detection by uncovering unexpected patterns in data. Data and Information analytics extends analysis (descriptive and predictive models to obtain knowledge from data) by using insight from analyses to recommend action or to guide and communicate decision-making. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with an entire methodology. Key topics include advanced statistical computing theory, multivariate analysis, and application of computer science courses such as data mining and machine learning and change detection by uncovering unexpected patterns in data. Data and Information analytics extends analysis (descriptive and predictive models to obtain knowledge from data) by using insight from analyses to recommend action or to guide and communicate decision-making. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with an entire methodology. Key topics include advanced statistical computing theory, multivariate analysis, and application of computer science courses such as data mining and machine learning and change detection by uncovering unexpected patterns in data.
Data Science and Analytics Select two or three of the following courses Select two or three of the following courses Select two or three of the following courses
Data Science and Analytics ITWS-6350 Data Science Fall
Data Science and Analytics ITWS-6400 X-Informatics Spring
Data Science and Analytics ITWS-696X Data Analytics Spring
Data Science and Analytics ITWS-696X Semantic E-Science Fall
Data Science and Analytics ITWX-696X Advanced Semantic Technologies Spring
Data Science and Analytics If only two of the above were chosen, select one more of the following courses If only two of the above were chosen, select one more of the following courses If only two of the above were chosen, select one more of the following courses
Data Science and Analytics COMM-6620 Information Architecture Spring
Data Science and Analytics CSCI-4020 Computer Algorithms Spring
Data Science and Analytics CSCI-4150 Introduction to AI Fall
Data Science and Analytics CSCI-6390 Database Mining Fall
Data Science and Analytics CSCI-4220 or CSCI-6220 Network Programming or Parallel Algorithm Design Spring
Data Science and Analytics ISYE-4220 Optimization Algorithms and Applications Fall
Data Science and Analytics ISYE-6180 Knowledge Discovery with Data Mining Spring
Data Science and Analytics MGMT-696X Technology Foundations for Business Analytics Fall
Data Science and Analytics MGMT-696X Predictive Analytics Using Social Media Spring
16
Also at RPI
  • Data Science Research Center and Data Science
    Education Center (dsrc.rpi.edu, 2009)
  • http//www.rpi.edu/about/inside/issue/v4n17/datace
    nter.html
  • Over 45 research faculty, post-docs, grad
    students, staff, undergraduates
  • Data is one of the Rensselaer Plans five thrusts
  • Other key faculty
  • Fran Berman (Center for Digital Society and RDA)
  • Bulent Yener (DSRC Director)
  • Jin Hendler (IDEA Director)

17
data.rpi.edu (v0.1, 2009)
18
Soon
19
More RPI Curriculua
  • Environmental Science with Geoinformatics
    concentration
  • Bio, geo, chem, astro, materials - informatics
  • GIS for Science
  • Master of Science Data Science?? (pending)
  • Multi-disciplinary science program - PhD in Data
    and Web Science
  • DATUM Data in Undergraduate Math! (Bennett)
  • Missing intermediate statistics
  • Graphs significant potential here must teach!

20
5-6 years in
  • Science and interdisciplinary from the start!
  • Not a question of do we train scientists to be
    technical/data people, or do we train technical
    people to learn the science
  • Its a skill/ course level approach that is
    needed
  • We teach methodology and principles over
    technology
  • Data science must be a skill, and natural like
    using instruments, writing/using codes
  • Team/ collaboration aspects are key
  • Foundations and theory must be taught

21
Challenging the Heroic Science Paradigm
This national and international has drawn
attention to the need for a reassessment of
priorities to recognize that, in the new data
era, the burden of making data and information
usable shifts from the user to the provider.
22
And thus in lt10 years
About PowerShow.com