Our Senior Researcher, Mohammad Khalil, is teaching a new PhD course on practical machine learning at the Faculty of Psychology. The course is arranged in collaboration with the International Graduate School in Integrated Neuroscience (IGSIN).

Introduction to Practical Machine Learning is a new PhD course that has been developed by our Senior Researcher, Mohammad Khalil. During the course, Khalil will give students an intuitive introduction to machine learning, both in theory and practice. Machine learning is a branch of Artificial Intelligence (AI) and Computer Science, which focuses on how the use of data and algorithms might imitate the way that humans learn.

Khalil will be holding all the course lectures in English, and they will take place at the Faculty of Psychology during the Spring semester of 2023.

The PhD course has two main parts. The first part will cover the topic “Machine learning: What is it?”, describing how machine learning allows the discovery of knowledge from data. Since data is the fuel that drives machine learning, the course will dive into data management, where descriptions of the organization, storage, cleansing, filtration, and preparation of data collected and used in research projects will be explained.

The second part of the course includes a group project where PhD candidates will work together on data sets. This will either be data sets of the candidates’ own choosing (in other words: PhD-related data sets) or open data sets. The candidates will apply machine learning techniques to distill interesting patterns and knowledge. They will have three weeks to work on the project and present their results in class.

R software will be used to manage practical examples of data management and machine learning. R is a programming language and software for statistical computing and graphics, supported by the R Core Team and the R Foundation for Statistical Computing. R is used by data miners, bioinformaticians and statisticians for data analysis and developing statistical software, and it is an open source, free software environment. During the course, R software will be approached from a beginner’s mindset, with students being walked through the creation and execution of their first R scripts.

Mohammad Khalil will cover multiple topics within machine learning, including data as a source for future decision-making and supervised and unsupervised learning techniques.

More About the Course

“Introduction to Practical Machine Learning” is one of the neuroscience and statistics courses presented by the International Graduate School in Integrated Neuroscience (IGSIN). IGSIN was founded as a joint initiative of the Faculty of Medicine and the Faculty of Psychology at the University of Bergen.

The primary goal of IGSIN is bringing together people from different countries with different educational backgrounds and different expertise, to provide an interdisciplinary training and networking platform for PhD students in the broad field of neuroscience. The field spans from basic biological, molecular, and genetic neuroscience to cognitive neuroscience, as well as clinical applications related to mental and neurological disorders.

The graduate school is located at the Department of Biological and Medical Psychology at the University of Bergen.

The registration deadline for the course is January 30th: Registration form

The course will have a maximum capacity of 20 students.

Course administrator: Vivian Helen Jacobsen Fosse.

Questions regarding course content: Contact Mohammad Khalil.

Course Dates

February 14th, 09:15 – 14:45, Christies gate 12, room 005 (Faculty of Psychology).

February 16th, 09:15 – 14:45, Christies gate 12, room 002 (Faculty of Psychology).

February 21st, 09:15 – 14:45, Christies gate 12, room 110 (Faculty of Psychology).

February 23rd, 09:15 – 14:45, Christies gate 12, room 555 (Faculty of Psychology).

March 15th, 09:15 – 14:30, Christies gate 12, room 002 (Faculty of Psychology).