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Research methods for doctoral students, 2017-2018

Menetelmäopintoja jatko-opiskelijoille, 2017-2018

This page contains information on teaching and courses on research methods in 2017-2018. The page will be updated during the year – Please contact us if you wish courses or teaching to be added to the page. Please also note that access to some courses may be restricted and remember to consult your supervisor and unit about whether the course can be accepted as a part of your doctoral degree.

STUDY BLOCKS

• Computational Social Science, organizer: Centre for Research Methods
• Digital humanities, organizer: Faculty of Arts

COURSES

Below is a list of some courses organised by the Centre for Research Methods, Bachelor’s and Master’s Programme in Social Research, Master’s Programme in Mathematics and Statistics, Master’s Programme in Data Science, Master’s Programme in Contemporary Societies, Master’s Programme in Linguistic Diversity in the Digital Age, Doctoral School in Humanities and Social Sciences and its Doctoral Programme in Social Sciences, Doctoral School in Biological, Environmental and Food Sciences, Doctoral Program in Population Health, and Doctoral Programme of School, Education, Society and Culture. More detailed information on the individual courses can be found by clicking the name of the course.

I teaching period (4.9.-22.10.)

• Introduction to Computational Social Science (Computational Social Science)
• Johdatus yhteiskuntatilastotieteeseen, osa 1 (JYT1)
• Data analysis with SAS
• Survey Sampling
• Qualitative Methods: Workshop on methods of text, narrative, discourse and rhetorical analysis (cont’d on periods II & III)
• Introduction to Atlas.ti (intensive course)
• Computational statistics I
• Tapaushistoriamallien kurssi
• Sosiaalitutkimuksen tilastolliset menetelmätaidot (cont’d on period II)
• Quantitative Research Skills (cont’d on period II)
• Introduction to Data Science
• Introduction to Artificial Intelligence
• Natural language processing for low-resource languages
• Korpuslingvistiikka ja tilastolliset menetelmät
• Puheen analyysin perusteet

II teaching period (30.10.-17.12.)

• Programming in Social Science (Computational Social Science)
• Johdatus yhteiskuntatilastotieteeseen, osa 2 (JYT2)
• Register-Based Data Analysis
• Introduction to Open Data Science (IODS)
• Survey methodology (Surveymetodiikka)
• Generalized linear models II
• High dimensional statistics
• Time-series analysis I
• Computational statistics II
• Distributed Data Infrastructures
• Introduction to Machine Learning
• Introduction to Big Data Management
• Computational Creativity
• Introduction to linear mixed models and GLMM in R
• Corpus clinic

III teaching period (15.1.-4.3.)

• Introduction to Atlas.TI
• Dynamic microsimulation in the Social Sciences – an introduction; Time: 9th February 2018, 2 – 4 pm; Venue: U35, room 114
• Analysis of complex surveys
• Demographic analysis
• Nonparametric and robust methods
• Complex Systems (Computational Social Science)
• Practical medical data-analysis with R
• Introduction to general quantitative study designs and data analysis with SPSS (cont’d on period IV)
• Applications of structural equation modelling (cont’d on period IV)
• Corpus Linguistics and Statistical Methods
• Ethnographic Methodologies
• Workshop on data wrangling – How to conduct the same complex preprocessing of data with R, Stata and SAS

IV teaching period (12.3.-6.5.)

• Data Extraction (Computational Social Sciences)
• Data Extraction 2 (Computational Social Sciences)
• Analysis of Discussion Forum Data
• Mediation Analysis with a focus on the Causal Inference Approach
• Advanced course in Bayesian statistics
• Advanced Course in Machine Learning
• Interactive Data Visualization
• Methods in Comparative Cultural Sociology
• Data collection at scale
• Data science for Social Science