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Dinov article: Building consensus on data science education and training

By | Research

Dr. Ivo Dinov, professor of Computational Medicine and Bioinformatics, Human Behavior, and Biological Science, and associate director of MIDAS, recently published an article on the training and education curricula needs of data science.

Title: Quant data science meets dexterous artistry
Published in: International Journal of Data Science and Analytics
DOI: 10.1007/s41060-018-0138-6
Author: Ivo D Dinov
Abstract: Data science is a bridge discipline connecting fundamental science, applied disciplines, and the arts. The demand for novel data science methods is well established. However, there is much less agreement on the core aspects of representation, modeling, and analytics that involve huge and heterogeneous datasets. The scientific community needs to build consensus about data science education and training curricula, including the necessary entry matriculation prerequisites and the expected learning competency outcomes needed to tackle complex Big Data challenges. To meet the rapidly increasing demand for effective evidence-based practice and data analytic methods, research teams, funding agencies, academic institutions, politicians, and industry leaders should embrace innovation, promote high-risk projects, join forces to expand the technological capacity, and enhance the workforce skills.

ASA Symposium on Data Science & Statistics

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SAVE THE DATE FOR SDSS 2018!

Beyond Big Data: Leading the Way

The ASA’s newest conference, the Symposium on Data Science & Statistics, will take place in Reston, Virginia, May 16-19, 2018. The symposium is designed for data scientistscomputer scientists, and statisticians analyzing and visualizing complex data.

The annual SDSS will combine data science and statistical machine learning with the historical strengths of the Interface Foundation of North America (IFNA) in computational statistics, computing science, and data visualization. It will continue the IFNA’s tradition of excellence by providing an opportunity for researchers and practitioners to share knowledge and establish new collaborations.

Offering sessions centered on the following six topic areas:
Data Science                                            Data Visualization
Machine Learning                                  Computing Science
Computational Statistics                      Applications

Key Dates:
December 5, 2017 – Contributed and E-Poster Online Abstract Submission Opens
January 18, 2018 – Contributed and E-Poster Online Abstract Submission Closes
February 1, 2018 – Conference Registration Opens

NASEM Webinar: Data Science for Undergraduates – Opportunities & Options

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Data Science for Undergraduates: Report Release Webinar

As our economy, society, and daily life become increasingly dependent on data, new college graduates entering the workforce need to have the skills to analyze data effectively. At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine organized a study to explore what data science skills are essential for undergraduates and how academic institutions should structure their data science education programs. We invite you to join us for a report release webinar on May 2, 2018 at 11am ET. During this webinar, study co-chairs Laura Haas and Alfred Hero will discuss the report’s findings and recommendations, followed by a question and answer session with webinar participants.

Learn more about the study, download the interim and final reports, and watch past webinars on the study webpage at nas.edu/EnvisioningDS.

Register for the Webinar.

WEBINAR INSTRUCTIONS

Click here to join the webinar

Password: data


NASEM Webinar: Data Science for Undergraduates – Opportunities & Options

By | Al Hero, Educational, News

As our economy, society, and daily life become increasingly dependent on data, new college graduates entering the workforce need to have the skills to analyze data effectively.

At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine organized a study to explore what data science skills are essential for undergraduates and how academic institutions should structure their data science education programs.

We invite you to join us for a report release webinar on May 2, 2018 at 11am ET.

During this webinar, study co-chairs Laura Haas and Alfred Hero will discuss the report’s findings and recommendations, followed by a question and answer session with webinar participants. Learn more about the study, download the interim and final reports, and watch past webinars on the study webpage at nas.edu/EnvisioningDS.

Register

WEBINAR INSTRUCTIONS
Click here to join the webinar
Password: data

Women in Data Science: Stanford University, March 5, 2018

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Women in Data Science (WiDS) Conference

and Datathon

Registration for Livestream

Schedule

The Global Women in Data Science (WiDS) Conference aims to inspire and educate data scientists worldwide, regardless of gender, and support women in the field. This annual one-day technical conference provides an opportunity to hear about the latest data science related research and applications in a broad set of domains, All genders are invited to participate in the conference, which features exclusively female speakers.

Next WiDS Conference: March 5, 2018 at Stanford University & 100+ locations worldwide
WiDS will be held at Stanford university, and at 100+ regional events hosted by WiDS Ambassadorsand available via livestream. The 2018 program will feature fantastic speakers on a broad array of topics ranging from cybersecurity to astrophysics to computational finance, and more. Register now for an event near you.

New for 2018: WiDS Datathon
This year, we’ll be conducting the first-ever WiDS Datathon, a joint effort between Stanford, Kaggle (a Google company), Intuit, InterMedia (a recipient of the Bill & Melinda Gates foundation, and West Big Data Innovation Hub.. The datathon runs from February 1-28, 2018, and winners will be announced at our March 5, 2018, conference at Stanford.

2017 Conference Highlights

  • 75,000+ participants from 75 countries via live stream and Facebook Live, at regional events or online
  • 80+ regional events worldwide from 30 countries, simultaneous or delayed broadcast, many with regional speakers.
  • #WiDS2017 hashtag trended on Twitter all day long
  • WiDS Stanford: 400 attendees from 31 universities and 114 companies and other organizations​, with 1/3 students and 2/3 academics and industry professionals
  • 33 distinguished female speakers, moderators, and panelists

MIDAS Working Group: Teaching Data Science

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The Michigan Institute for Data Science (MIDAS) continues to convene a working group on teaching data science. As we incorporate data science into almost every level of teaching, many issues need to be thoroughly thought out: How do we teach data science to students with various levels of preparation, from those with little quantitative training to STEM students? How do we build data science modules to incorporate into existing domain science courses? How do we raise awareness of ethics and social responsibility in data science teaching? How do we teach data science to independent researchers, including faculty, who want to build data science into their research? What teaching resources are available at UM? Our working group welcomes anyone interested in these topics. We are developing an interdisciplinary team to foster new ideas and collaborations in the development of data science teaching methods and materials.

Please RSVP.  

The agenda for the meeting includes:

  • Introduction
  • Short presentations
    • Kerby Shedden (Professor, Statistics, and CSCAR director) will share insight from his experience teaching “capstone” style courses for undergraduate and MS students, based around case studies and focus on methods, formulating good questions, and writing.
    • Heather Mayes (Assistant Professor, Chemical Engineering) will talk about the design of a Data Science ramp-up course for engineering students and how to integrate it with existing course offerings.
    • Aaron Keys (data scientist, Airbnb) will give the industry perspective on the various training paths that students can take for a career in data science.
  • Open discussion of ideas and collaboration, and sharing resources

For questions, please contact Jing Liu, MIDAS Senior Scientist and Industry Partnership Leader (ljing@umich.edu734-764-2750).

Data Science Certificate Info Session

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DS Cert program info session on 2/16 in room 1180 at the Duderstadt Building from 5:30pm to 6:30pm. The

Come learn about the Graduate Certificate in Data Science:

The certificate is focused on developing core proficiencies in data analytics:
1) Modeling — Understanding of core data science principles, assumptions and applications;
2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

Canceled – Data Science Certificate Student Social and Info Session

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Canceled due to inclement weather.
The Student Social and Information Session will be rescheduled later this semester.

 
Come chat with fellow Data Science Certificate students, or learn more about it:

The Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:
1) Modeling — Understanding of core data science principles, assumptions and applications;
2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

NAS / CATS: Integrating Ethics and Privacy Concerns into Data Science Education

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image for webpages-CATS

 Meeting & Webcast on Data Science Education in the Workplace

“Integrating Ethics and Privacy Concerns into Data Science Education”

Roundtable Meeting and Webcast on December 8, 2017

The National Academies of Sciences, Engineering, and Medicine invite you to attend the fifth meeting and webcast of the Roundtable on Data Science Postsecondary Education on December 8, 2017.  This meeting will focus on “Integrating Ethics and Privacy Concerns into Data Science Education” and will bring together experts from academia, industry, and government to discuss current practices and strategies to better integrate ethical and privacy concerns into data science courses.  Learn more about the roundtable and watch past meetings at nas.edu/dsert.

Download Preliminary Agenda

Register to Attend In Person or Online


About Math and Statistics at the National Academies

The Board on Mathematical Sciences and Analytics (BMSA) leads activities in the mathematical sciences at the National Academies in topic areas including from applied mathematics, scientific computing, and risk analysis.

The Committee on Applied and Theoretical Statistics (CATS) organizes studies and events focusing on the statistical sciences, big data and data science, statistical education, the use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.

The National Academies Webinar Series: Data Science Undergraduate Education

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Webinar

 

REGISTRATION

Webinar Series: Data Science Undergraduate Education

Join the National Academies of Sciences, Engineering, and Medicine for a webinar series on undergraduate data science education. Webinars will take place on Tuesdays from 3-4pm ET starting on September 12 and ending on November 14. See below for the list of dates and themes for each webinar.

This webinar series is part of an input-gathering initiative for a National Academies study on Envisioning the Data Science Discipline: The Undergraduate Perspective. Learn more about the study, read the interim report, and share your thoughts with the committee on the study webpage at nas.edu/EnvisioningDS.

Webinar speakers will be posted as they are confirmed on the webinar series website.

Webinar Dates and Topics

•    9/12/17 – Building Data Acumen
•    9/19/17 – Incorporating Real-World Applications
•    9/26/17 – Faculty Training and Curriculum Development
•    10/3/17 – Communication Skills and Teamwork
•    10/10/17 – Inter-Departmental Collaboration and Institutional Organization
•    10/17/17 – Ethics
•    10/24/17 – Assessment and Evaluation for Data Science Programs
•    11/7/17 – Diversity, Inclusion, and Increasing Participation
•    11/14/17 – Two-Year Colleges and Institutional Partnerships

All webinars take place from 3-4pm ET. You will have the option to register for the entire webinar series or for individual webinars.