ACIT4510 Statistical Learning Emneplan

The course covers the foundations and recent advances in Machine Learning from the point of view of Statistical Learning Theory. The goal of this course is to provide students with the practical skills to support the theoretical knowledge acquired during the lecture course and the practical intuitions needed to use and develop effective machine learning solutions to challenging problems.

Access to good statistical/data analysis software is paramount. Therefore, we will illustrate the use of the models throughout the course with real implementation.

For the oral exam, students will not have access to computers or other aids.

No formal requirements over and above the admission requirements.

The student should have the following outcomes upon completing the course:

Knowledge

Upon successful completion of the course, the student:

• will have a good understanding the different concepts and methods of supervised and unsupervised statistical learning and how to apply them on large data.
• has advanced knowledge of probabilistic formulation of the various learning problems

;

Skills

Upon successful completion of the course, the student:

• can apply different high-dimensional regression techniques on data
• can apply different classification techniques on data
• can apply clustering techniques on data
• can derive learning algorithms for new models and analyze new data with them.
• can apply dimensionality reduction techniques on data

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General competence

Upon successful completion of the course, the student:

• can apply different predictive models on data and assess their performance
• can use supervised and unsupervised learning in different real life problem

This course is divided into two parts. The first part with focus on covering the principles of Statistical Learning. Different seminars will be given on the different methodological aspects of Statistical learning, mainly, supervised learning and unsupervised learning.

The second part will focus on the students completing a programming project. This is a real data analysis problem, where the student is asked to carry out the analysis using the tools and techniques from the course and hand in a report documenting the steps he has taken in the analysis. The ultimate goal is to build a predictive model.

The project report will consist of at least 25 pages and max 60 pages.

During this part, there may be lectures if needed, but most of the time will be spent on individual supervision of students in lab-sessions.

Practical training

Lab sessions.

This course covers the state of the art of technology and methods in the research within human-computer interaction and available computer systems.

An individual project report approximately 2500 - 5000 words, excluding appendixes.

The exam can be appealed,

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New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for applying for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of this course the student

• has advanced knowledge of multimodal user interfaces
• has advanced knowledge of input and output technologies
• can analyse problems and issues in interactions related to context, such as accessibility in public spaces, mobility problems, and the user's affective state
• can use knowledge of interaction technology to address new problems in universal design of ICT

Skills

On successful completion of this course the student

• can independently use appropriate methods of user centred interaction design and evaluation; both heuristic and automatic, in an independent manner
• can analyse and critically deal with the results from relevant research literature, apply these to structure and formulate scientific arguments, and assess the suitability of published results on new problems and issues
• can carry out independent, limited research or development projects under supervision and in accordance with applicable ethical standards
• can present scientific work orally
• can debate and conduct scientific discussions

General competence

On successful completion of this course the student

• can apply knowledge and skills in interaction technology on new problems and issues for carrying out advanced facilitation tasks and projects
• can communicate scientific problems, analysis and conclusions in the field to both specialists and the general public
• can contribute to original thinking and innovation processes

The following required coursework must be approved before the student can take the exam:

-;Two individual oral presentations of research articles (45 min per presentation including questions)

- This course is organized as a series of lectures and seminars where students present and discuss with opponents research articles that covers core concepts and topics in the literature.

- Students work in groups on two projects under supervision.

• Two individual oral presentations of research articles (45 min per presentation including questions).
• Being opponent against two student presentations.

• One written grop project report (2000-3000 words) in group of 1-2 students. This part of the examination counts 35 % of the final grade.
• One written group project report (4000-5000 words) in group of minimum 4 students. This part of the examination counts 35 % of the final grade.
• Individual oral examination (20 minutes for each candidate). The oral examination counts 30% of the final grade.

All exams must be passed in order to pass the course.

The oral examination cannot be appealed.

;

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for applying for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.