Periods
(27-Aug-2018
– 21-Oct-2018)
(22-Oct-2018
– 14-Dec-2018)
(7-Jan-2019
– 3-Mar-2019)
(4-Mar-2019
– 26-May-2019)
Teaching schedule for Master's Degree Programme in Computational Big Data Analytics.
See the Curricula for requirements of General, Advanced and Other and Optional Studies.
Correspondence between old and new courses, statistics curricula 2012-2015 compared to CBDA curricula 2015-2018, can be found in separate document (finnish only).
Course registration
Period I: Wed 1.8. - Sun 2.9.2018
Period II: Mon 17.9. - Sun 14.10.2018
Period III: Mon 26.11.2018 - Wed 2.1.2019
Period IV: Mon 28.1.- Sun 24.2.2019
See the course information for instructions on course registration. If a student has registered for a course but will not be taking it, he/she must cancel his/her registration. If a student does not participate in the course and does not cancel his/her enrolment by the time set by the teacher, or if he/she discontinues the course, he/she will be assigned a fail grade for the course in question.
Course feedback
Course feedback can be given through the course-specific questionnaire opened by the teacher responsible.
Cross-Institutional Studies (Tampere3)
Service for Cross-Institutional Studies lists courses offered to all degree students at Tampere University of Applied Sciences, Tampere University of Technology and the University of Tampere. For instructions and details, see the service.
Recommended and/or interesting studies for CBDA-students include
- MAT-02506 Probability Calculus (4 ECTS), and
- MAT-63807 Introduction to data mining: The B-course and GUHA-method (5 ECTS).
For details, see information on Cross-Institutional Studies in TUT (below).
Final grade and graduation
Final grade in Advanced studies (for degree certificate) can be asked from study coordinators (mtt-studies@uta.fi, cs-studies@uta.fi).
See also: Applying for the degree certificate and graduation deadlines.
Recommended Cross-Institutional Studies in TUT include
- MAT-02506 Probability Calculus, 4 ECTS (basic level course, part of prerequisities in CBDA, can not be included inside the minimum requirement of 120 ECTS of Masters Degree).
- MAT-63807 Introduction to data mining: The B-course and GUHA-method, 5 ECTS (Can be included in Advanced Studies in CBDA: "Advanced Courses in Methods of Computational Data Analytics").
For other courses, contact your personal study plan teacher or study coordinator.
- Search the course from the service for cross-institutional studies.
- Update your study plan and inform your psp-teacher.
- Apply for studies of your choice.
- Follow the instructions.
This part of the Orientation Course is compulsory also to new Finnish students selected in spring 2018.
Teachers:
- Zheying Zhang (SDE)
- Jaakko Peltonen (CBDA)
- Martti Juhola (CBDA)
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
If you wish to complete the course during the academic year 2018-2019, contact the teacher no later than March 15, 2019.
This module (54 hours) is online apart from individual teacher-student tutorials for discussion of the submitted thesis extract. The work consists of readings, group analysis tasks and thesis writing work. Students should take the module after their research proposal has been accepted by their programme and they are about to embark upon the writing of their thesis.
In cases where more students register for a course than space allows, priority is assigned as follows:
1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.
In addition, there is a quota of 5 for the Open University students in every group.
In cases where more students register for a course than space allows, priority is assigned as follows:
1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.
In addition, there is a quota of 5 for the Open University students in every group.
The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.
The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.
Contact person: Coordinator of international education, Anna Wansén-Kaseva
Enroll on the course TIETA6 Data Structures in NettiOpsu
Self studying, weekly excercises, practical work, and exam.
Read about the recommended prior knowledge from the course website.
Course Contents
Matrix basic operations, random number generation, cross-validation, Jackknife, Bootstrap, use of the R program
Modes of Study and Registration
Independent work and exercises, mainly for CBDA-students.
Please see the Moodle page for details and instructions.
Lectures of the course MTTTA14 Tilastotieteen matriisilaskenta ja laskennalliset menetelmät are held only in Finnish. The lectures are based on study material which is available in English for independent study.
In the workshop students can get support for their studies in Statistics.
The idea is that students work independently or in groups with the problems that have arisen. The workshop has a teacher and you can ask for the advice from him. However, the idea is that the teacher will not solve the problems for you. The workshop does not provide any compensation of the solved exercises.
Support in using statistical software (e.g. SPSS and R) is also available in workshop.
Period I: especially for students taking MTTTA14 Matrices for Statistics and Computational Methods.
Period II: especially for students taking MTTTA2 Matemaattisen tilastotieteen perusteet.
Period III: especially for students taking MTTTA4 Statistical Inference 1.
This course explores methods for the analysis of longitudinal data and latent variable methods for linear models, generalized linear models, and nonlinear models. Focusing on applications, this course explores: the analysis of repeated measures ANOVA, multivariate approaches, random-effects regression, covariance-pattern models, generalized-estimating equations and generalizations, latent variable methods including finite mixture modelling, and likelihood methods. Students will develop expertise using the SAS and R computer packages, although no previous programming experience will be assumed. Grading is based on homework and computer assignments and a project, as well as several exams.
Course begins with a lecture on Monday 17th of September.
There are three exams during the course.
Recommended preceding studies:
Basic courses of statistics and Regression analysis
If you are considering to begin the thesis work, it is a good time to enrol. It is recommended that you'd begin the seminar before you have agreed on the topic and/or supervisor of the thesis.
Students can enrol ANY TIME, not just at the beginning of the period. If enrolment is not open, contact the teacher by email.
Modes of study
- Lectures
- Exercises (independent work)
- Exam
Teachers:
- Zheying Zhang (SDE)
- Jaakko Peltonen (CBDA)
- Martti Juhola (CBDA)
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
If you wish to complete the course during the academic year 2018-2019, contact the teacher no later than March 15, 2019.
This module (54 hours) is online apart from individual teacher-student tutorials for discussion of the submitted thesis extract. The work consists of readings, group analysis tasks and thesis writing work. Students should take the module after their research proposal has been accepted by their programme and they are about to embark upon the writing of their thesis.
In cases where more students register for a course than space allows, priority is assigned as follows:
1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.
In addition, there is a quota of 5 for the Open University students in every group.
The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.
The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.
Contact person: Coordinator of international education, Anna Wansén-Kaseva
General description
Knowledge about statistical methods and data analysis is of great importance in almost any field of research. In this course, general concepts of statistics will be provided so that students can be able to independently carry out a small scale empirical research with the statistical software SPSS or R. After the course, students should be familiar with the basic concepts of statistics, ranging from descriptive statistics, basic inference (estimation, confidence intervals and hypothesis testing), linear models (analysis of variance, simple and multiple linear regression), non-parametric tests and logistic regression.
Space is limited in this course due to computer room capacity. Priority will be granted for the first enrolments, based on the proportions: 60% PhD students and 40% for BSc and MSc students.
Please note that this course cannot be included inside the minimum 120 ECTS of Master's Degree Programme in CBDA (basic level course).
MTTTP1 Tilastotieteen johdantokurssi lectured in period I, II or III-IV is recommended for Finnish students.
Enroll on the course TIETA6 Data Structures in NettiOpsu
Self studying, weekly excercises, practical work, and exam.
If needed, priority is given to the students in CBDA
In the workshop students can get support for their studies in Statistics.
The idea is that students work independently or in groups with the problems that have arisen. The workshop has a teacher and you can ask for the advice from him. However, the idea is that the teacher will not solve the problems for you. The workshop does not provide any compensation of the solved exercises.
Support in using statistical software (e.g. SPSS and R) is also available in workshop.
Period I: especially for students taking MTTTA14 Matrices for Statistics and Computational Methods.
Period II: especially for students taking MTTTA2 Matemaattisen tilastotieteen perusteet.
Period III: especially for students taking MTTTA4 Statistical Inference 1.
If you are considering to begin the thesis work, it is a good time to enrol. It is recommended that you'd begin the seminar before you have agreed on the topic and/or supervisor of the thesis.
Students can enrol ANY TIME, not just at the beginning of the period. If enrolment is not open, contact the teacher by email.
Modes of study
- Lectures
- Exercises (independent work)
- Exam
Teachers:
- Zheying Zhang (SDE)
- Jaakko Peltonen (CBDA)
- Martti Juhola (CBDA)
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
If you wish to complete the course during the academic year 2018-2019, contact the teacher no later than March 15, 2019.
This module (54 hours) is online apart from individual teacher-student tutorials for discussion of the submitted thesis extract. The work consists of readings, group analysis tasks and thesis writing work. Students should take the module after their research proposal has been accepted by their programme and they are about to embark upon the writing of their thesis.
In cases where more students register for a course than space allows, priority is assigned as follows:
1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.
In addition, there is a quota of 5 for the Open University students in every group.
Schedule:
16.1. Seija-Leena Nevala: Finland – 101 years of Independency
23.1. Katja Keisala: How to Communicate in Finland
30.1. Johanna Peltoniemi: Finnish Political System
6.2. Juho Kaitajärvi-Tiekso: Finnish Popular Music from "Humppa" to Lordi
13.2. Hannu Sinisalo: Boundaries of Finnishness and Ethnic Minorities in Finland
20.2. Marko Seppänen: Finnish Innovations - Past, Present and Future
27.2. no lecture
6.3. Tuija Koivunen: Women, Men and Work
13.3. Ari Vanamo: Finnish Forests and Forestry
20.3. Lina van Aerschot: Finnish Welfare and Social Services
27.3. Raisa Harju-Autti: Finnish Education System
3.4. Katja Fält: Finnish Art History in a Nutshell
10.4. Arja Luiro: Finnish Gastronomy
17.4. Jyrki Jyrkiäinen: Special Features of Finnish Mass Media
24.4. exam
+ the date of retake exam will be announced later
Please enrol before the first lecture (16.1).
The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.
The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.
Contact person: Coordinator of international education, Anna Wansén-Kaseva
In the workshop students can get support for their studies in Statistics.
The idea is that students work independently or in groups with the problems that have arisen. The workshop has a teacher and you can ask for the advice from him. However, the idea is that the teacher will not solve the problems for you. The workshop does not provide any compensation of the solved exercises.
Support in using statistical software (e.g. SPSS and R) is also available in workshop.
Period I: especially for students taking MTTTA14 Matrices for Statistics and Computational Methods.
Period II: especially for students taking MTTTA2 Matemaattisen tilastotieteen perusteet.
Period III: especially for students taking MTTTA4 Statistical Inference 1.
If you are considering to begin the thesis work, it is a good time to enrol. It is recommended that you'd begin the seminar before you have agreed on the topic and/or supervisor of the thesis.
Students can enrol ANY TIME, not just at the beginning of the period. If enrolment is not open, contact the teacher by email.
Modes of study
- Lectures
- Exercises (independent work)
- Exam
Contents
- Introduction to functional and shape data analysis with R and Matlab
- Functional principal component and canonical correlation analysis
- Linear and mixed models for functional and shape data sets
- Linear differential operators in functional data analysis
- Procrustes analysis in statistical shape analysis
- Shape distributions
TTY:n opiskelijat ilmoittautuvat kurssille ristiinopiskelupalvelun ohjeiden mukaisesti.
Recommended preceding studies:
Understanding of basics of statistics and probability. For example minimum of UTA courses consists of MTTTP1 Introduction to Statistics and MTTTP5 Basics of Statistical Inference (or equivalent).
Note one exercise group in Central campus (Pinni B ML40) on Fri 10-12.
In TUT POP portal.
This course is organized by TUT and UTA students must
- Apply for study right through Service for Cross-Institutional Studies.
- Make sure to apply for the right to study well in advance so that you have enough time to also activate the user account of TUT and
- to sign up for the studies according to the schedules of TUT.
Read carefully the UTA instructions
This course cannot be taken if student has done TIETS39 Machine Learning Algorithms.
Note. The prerequisite SGN -courses are not required from UTA students.
Teachers:
- Zheying Zhang (SDE)
- Jaakko Peltonen (CBDA)
- Martti Juhola (CBDA)
This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.
If you wish to complete the course during the academic year 2018-2019, contact the teacher no later than March 15, 2019.
This module (54 hours) is online apart from individual teacher-student tutorials for discussion of the submitted thesis extract. The work consists of readings, group analysis tasks and thesis writing work. Students should take the module after their research proposal has been accepted by their programme and they are about to embark upon the writing of their thesis.
Schedule:
16.1. Seija-Leena Nevala: Finland – 101 years of Independency
23.1. Katja Keisala: How to Communicate in Finland
30.1. Johanna Peltoniemi: Finnish Political System
6.2. Juho Kaitajärvi-Tiekso: Finnish Popular Music from "Humppa" to Lordi
13.2. Hannu Sinisalo: Boundaries of Finnishness and Ethnic Minorities in Finland
20.2. Marko Seppänen: Finnish Innovations - Past, Present and Future
27.2. no lecture
6.3. Tuija Koivunen: Women, Men and Work
13.3. Ari Vanamo: Finnish Forests and Forestry
20.3. Lina van Aerschot: Finnish Welfare and Social Services
27.3. Raisa Harju-Autti: Finnish Education System
3.4. Katja Fält: Finnish Art History in a Nutshell
10.4. Arja Luiro: Finnish Gastronomy
17.4. Jyrki Jyrkiäinen: Special Features of Finnish Mass Media
24.4. exam
+ the date of retake exam will be announced later
Please enrol before the first lecture (16.1).
In the workshop students can get support for their studies in Statistics.
The idea is that students work independently or in groups with the problems that have arisen. The workshop has a teacher and you can ask for the advice from him. However, the idea is that the teacher will not solve the problems for you. The workshop does not provide any compensation of the solved exercises.
Support in using statistical software (e.g. SPSS and R) is also available in workshop.
Period I: especially for students taking MTTTA14 Matrices for Statistics and Computational Methods.
Period II: especially for students taking MTTTA2 Matemaattisen tilastotieteen perusteet.
Period III: especially for students taking MTTTA4 Statistical Inference 1.
Recommended preceding studies: Data Structures, basics of statistics, basics of mathematics and linear algebra.
NOTE, contact teaching (lectures and excercises) is in Finnish. The lectures are based on study material which is available in English. Weekly exercises will be available in English and are to be sent to the teacher.
For summer course see Weto
See instructions on coursepage.
Read about the recommended prior knowledge from the course website.
If you are considering to begin the thesis work, it is a good time to enrol. It is recommended that you'd begin the seminar before you have agreed on the topic and/or supervisor of the thesis.
Students can enrol ANY TIME, not just at the beginning of the period. If enrolment is not open, contact the teacher by email.
Modes of study
- Lectures
- Exercises (independent work)
- Exam
Content
It is quite common that we do not get all the information we want for our statistical analysis. For example, in medical research a person can refuse to provide certain information they feel sensitive, such as weight, substance abuse, sexual orientation etc. Particularly, missing data in longitudinal studies is more the rule than an exception. Missing data in statistical analysis causes all sorts of problems. For example, the desired statistical method cannot be directly applied; loss of information or the results obtained can be biased if the analysis is not done properly accomplished. The course introduces various missing data mechanisms and their effects on statistical analysis. In addition, it presents and evaluates some of the commonly used methods for statistical analysis with missing data. Also advanced methods are presented, as well as special methods for the analysis of longitudinal data including likelihood-based methods and multiple imputation.
Modes of Study
Course work, exam.
This course is an advanced study version of MTTA2 Statistical Analysis with Missing Data, and the student can only complete one of the two versions.