Discussion Forum:

Data Science

Machine Learning, Data Mining, and Algorithmic Methods for Big, High Dimensional and Scarce Data

This forum is an informal platform for sharing ideas on educational and conceptual chalenges brought by recent, rapid development of methods that are often collectively termed as data analytics, data science, cognitive computing, Big Data methods, etc. There are no particular format or goals for this webpage except to serve as a reference for the involved discussants. One of possible positive effects would be to define the core and boundaries of the emerging discipline so that one could create meaningful educational programs at different intelectual accessibility levels.

Notes from a meeting with Combient on Wed 02 May, 2018. Jan Erik Gustasson (jan-erik.gustavsson@combient.com) Slides only for internal use. They are interested in the distant learning opportunities for their clients (MOC - massive online courses). Knowledge sharing, Hannover Messe next year is co-hosted by Sweden it is a very big and important event at the end of April.

Mediated by:

Krzysztof Podgórski

Department of Statistics, School of Economics and Management, Lund University

LINKS TO EXISTING COURSES WITHIN DATA SCIENCE

• Data Mining and Visualization, Statistics, Lund University, designed by Krzysztof Podgorski ,
• Advanced Statistical Computing , by Paul D. Baines, the University of California, Davis, recommended by Jonas Wallin,
• Natural Language Processing with Deep Learning , by Richard Socher, Stanford University, recommended by Jonas Wallin,
• Data Science MSc Program , Lancaster University, recommended by Krzysztof Podgorski,
• Machine Learning Series of Lectures , by Jeff Miller , Duke University, recommended by Hiba Nassar,
• Data Science MSc Program, Barcelona School of Economics, recommended by Krzysztof Nowicki,
• MSc in Data Sciences and Business Analytics (with ESSEC Business School) , recommended by Marie Kratz,
• Open Source natural language processing Spacy in Python, recommended by Andrzej Rusewicz,
• Martin Eklund, Karolinska Institute , a speaker in our seminar that have access to a variety of medical data that he could share.
• Another highly successful program in Data Science, Warsaw University of Technology, recommended by Jacek Wesolowski,
• A course in Functional Data Analysis, by Giles Hooker at Cronell University,
• Raazesh Sainudiin A very knowledgeable person on Bid Data databases that gave a talk in the annual Swedish Statistical Meeting. raazesh.sainudiin@math.uu.se
• The technology company Combient AB keen to get Data Science programmes started at all Swedish Universities and have supported with developing the courses at Uppsala, recommended by Raazesh Sainudiin.
• A book version of Data Science Program , recommended by Raazesh Sainudiin.
• A course in Data Science Program , recommended by Raazesh Sainudiin.
• Another course for Data Science Program , recommended by Raazesh Sainudiin.
• Master in Stochastic and Data Science Program, the University of Torino, Italy , recommended by Jakob Bergman.
• The first course about Apache Spark , by Raazesh Sainudiin, he offered the on-site training if needed.
• The International Data Science in Schools Project , initiative for promoting the data science at the high school level.
• Slides presenting the Department of Statistics proposal for Master in Data Science and Analytics.