- Email: [email protected]
Learning Opportunities
APPENDIX D
Learning Opportunities There exist a variety of courses covering text mining at the time of writing, the majority of which explore the subject as part of a broader topic area such as data analytics. A few are listed below. Inclusion in this list does not constitute a recommendation and failure to include courses should not be taken as deliberate exclusion.
D.1 UNITED KINGDOM MSc in Information Management, University of Manchester Technical and organisational challenges of “Big Data”; text mining is covered as an optional element. MSc in Computer Science with Speech and Language Processing, University of Sheffield Run by the Department of Computer Science in collaboration with the Speech and Hearing and Natural Language Processing groups, this course combines text processing, speech processing, machine learning, speech technology, natural language processing and research methods. MSc in Data Mining, University of Westminster “The entire data mining process”, with a focus on SAS Enterprise Miner, SAS Text Miner and Oracle Data Mining Suite. Text mining is covered as an elective.
D.2 IRELAND MSc in Computing, DCU (Dublin City University) Data analytics, cloud computing, software engineering and human language technology; includes an introduction to linguistics.MSc in Data Mining and Business Intelligence, ITB (Institute of Technology Blanchardstown) Business intelligence and data mining, data preprocessing; web content, text mining, geographic information system and multimedia mining are offered as electives.
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Learning Opportunities
D.3 SWEDEN MSc in Statistics and Data Mining, Link€ oping This course includes data analysis, machine learning, text mining and statistical methods in bioinformatics.
D.4 FRANCE Master of Science in Informatics, University Paris 13 Second-year elective in Data Mining, Analytics and Knowledge Discovery; electives include neural networks, statistical and machine learning, social networks, time series analysis, bioinformatics and text mining. Master in Business Analytics, EISTI (Ecole Internationale des Sciences du Traitement de l’Information) A multidisciplinary MSc including statistics, data mining, operational research and architecture; methods include opinion mining, social networks and Big Data, optimisation. The course is taught in English. DKM2 – Master in Data Mining and Knowledge Management Offered by a consortium of universities – France (University of Pierre and Marie Curie Paris 6, University of Lyon Lumie`re Lyon 2, Polytec’Nantes), Romania (University Polithenica of Bucharest), Italy (University of East Piedmont) and Spain (Technical University of Catalonia). Beginning with the technical and mathematical prerequisites, the course includes data mining with social science applications, statistical modelling and data mining.
D.5 UNITED STATES MSc in Computer Science, Stanford University Text mining is a topic in the Information Management and Analytics track. Data Mining M.S., Lewis University Data Mining MSc, CCSU M.S. in Analytics, Georgia Tech Web Search and Text Mining module is an elective element of this M.S. M.S. in Intelligent Information Systems, Carnegie Mellon University Text mining is an elective in this Computer Science degree.
D.6 SHORT COURSES, TRAINING COURSES AND MOOCs Short courses are an appealing alternative to postgraduate courses for those currently in education or research. A variety of short courses are held on a
Learning Opportunities
321
yearly or occasional basis as “summer (or autumn or winter) schools”. These are sometimes a relatively inexpensive option. Training courses are also available on various topics; these vary greatly in price depending on the subject matter and organiser, from free to extremely expensive. The developers and maintainers of popular text mining tools often run courses on their use. GATE training courses, for example, are currently held yearly in Sheffield; course material from previous years is freely available online. MOOCS (massive open online courses) are available in several topics of relevance to text mining. A disadvantage of the MOOC format is the periodic unavailability of these courses. However, it is often the case that where courses are not currently running, material from courses remains openly available and can be used for self-directed study. Data Mining with Weka, University of Waikato This course covers the Weka toolkit. Corpus Linguistics, University of Lancaster (FutureLearn) Run by Tony McEnery, Professor of English Language and Linguistics (and author of a canonical textbook on corpus linguistics), this MOOC introduces the essentials of corpus linguistics. Natural Language Processing, Stanford (Coursera) Information Visualisation, Indiana University This course is part of Indiana’s Online Certificate in Data Science, but can be followed for free. Mining Massive Datasets, Stanford (Coursera) This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well. Process Mining: Data science in Action, Eindhoven University of Technology (Coursera) Process mining connects data-centric observation of behaviour with process analysis in order to develop an understanding of how event data and process models interact. The University of Illinois at Urbana-Champaign currently runs a Data Mining specialisation on Coursera, including the following courses: • Pattern Discovery in Data Mining • Text Retrieval and Search Engines • Cluster Analysis in Data Mining
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Learning Opportunities
Text Mining and Analytics Data Visualization Data Mining Capstone (project)
Learning Opportunities There exist a variety of courses covering text mining at the time of writing, the majority of which explore the subject as part of a broader topic area such as data analytics. A few are listed below. Inclusion in this list does not constitute a recommendation and failure to include courses should not be taken as deliberate exclusion.
D.1 UNITED KINGDOM MSc in Information Management, University of Manchester Technical and organisational challenges of “Big Data”; text mining is covered as an optional element. MSc in Computer Science with Speech and Language Processing, University of Sheffield Run by the Department of Computer Science in collaboration with the Speech and Hearing and Natural Language Processing groups, this course combines text processing, speech processing, machine learning, speech technology, natural language processing and research methods. MSc in Data Mining, University of Westminster “The entire data mining process”, with a focus on SAS Enterprise Miner, SAS Text Miner and Oracle Data Mining Suite. Text mining is covered as an elective.
D.2 IRELAND MSc in Computing, DCU (Dublin City University) Data analytics, cloud computing, software engineering and human language technology; includes an introduction to linguistics.MSc in Data Mining and Business Intelligence, ITB (Institute of Technology Blanchardstown) Business intelligence and data mining, data preprocessing; web content, text mining, geographic information system and multimedia mining are offered as electives.
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320
Learning Opportunities
D.3 SWEDEN MSc in Statistics and Data Mining, Link€ oping This course includes data analysis, machine learning, text mining and statistical methods in bioinformatics.
D.4 FRANCE Master of Science in Informatics, University Paris 13 Second-year elective in Data Mining, Analytics and Knowledge Discovery; electives include neural networks, statistical and machine learning, social networks, time series analysis, bioinformatics and text mining. Master in Business Analytics, EISTI (Ecole Internationale des Sciences du Traitement de l’Information) A multidisciplinary MSc including statistics, data mining, operational research and architecture; methods include opinion mining, social networks and Big Data, optimisation. The course is taught in English. DKM2 – Master in Data Mining and Knowledge Management Offered by a consortium of universities – France (University of Pierre and Marie Curie Paris 6, University of Lyon Lumie`re Lyon 2, Polytec’Nantes), Romania (University Polithenica of Bucharest), Italy (University of East Piedmont) and Spain (Technical University of Catalonia). Beginning with the technical and mathematical prerequisites, the course includes data mining with social science applications, statistical modelling and data mining.
D.5 UNITED STATES MSc in Computer Science, Stanford University Text mining is a topic in the Information Management and Analytics track. Data Mining M.S., Lewis University Data Mining MSc, CCSU M.S. in Analytics, Georgia Tech Web Search and Text Mining module is an elective element of this M.S. M.S. in Intelligent Information Systems, Carnegie Mellon University Text mining is an elective in this Computer Science degree.
D.6 SHORT COURSES, TRAINING COURSES AND MOOCs Short courses are an appealing alternative to postgraduate courses for those currently in education or research. A variety of short courses are held on a
Learning Opportunities
321
yearly or occasional basis as “summer (or autumn or winter) schools”. These are sometimes a relatively inexpensive option. Training courses are also available on various topics; these vary greatly in price depending on the subject matter and organiser, from free to extremely expensive. The developers and maintainers of popular text mining tools often run courses on their use. GATE training courses, for example, are currently held yearly in Sheffield; course material from previous years is freely available online. MOOCS (massive open online courses) are available in several topics of relevance to text mining. A disadvantage of the MOOC format is the periodic unavailability of these courses. However, it is often the case that where courses are not currently running, material from courses remains openly available and can be used for self-directed study. Data Mining with Weka, University of Waikato This course covers the Weka toolkit. Corpus Linguistics, University of Lancaster (FutureLearn) Run by Tony McEnery, Professor of English Language and Linguistics (and author of a canonical textbook on corpus linguistics), this MOOC introduces the essentials of corpus linguistics. Natural Language Processing, Stanford (Coursera) Information Visualisation, Indiana University This course is part of Indiana’s Online Certificate in Data Science, but can be followed for free. Mining Massive Datasets, Stanford (Coursera) This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well. Process Mining: Data science in Action, Eindhoven University of Technology (Coursera) Process mining connects data-centric observation of behaviour with process analysis in order to develop an understanding of how event data and process models interact. The University of Illinois at Urbana-Champaign currently runs a Data Mining specialisation on Coursera, including the following courses: • Pattern Discovery in Data Mining • Text Retrieval and Search Engines • Cluster Analysis in Data Mining
322
• • •
Learning Opportunities
Text Mining and Analytics Data Visualization Data Mining Capstone (project)