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R 5
Machine learning and AI – 2 days
During this course we learn how to train different kinds of machine learning models and how to evaluate the predictive performance of them. We will also discuss how modern AI systems work and build models for analysing text and images.
Machine learning models are used to make predictions, for instance to diagnose diseases or predict future stock prices. In this course we learn how to train different kinds of machine learning models, including random forest and lasso regression, and how to evaluate the predictive performance of our models. In addition, we learn about how to deal with common challenges in machine learning projects, such as missing data and imbalanced data.
Modern AI systems use machine learning models known as deep neural networks. During the second day of this course, we learn how these work, and build models for analysing text and images. We also learn about common pitfalls and the limitations of present-day AI.
Course goals: To be able to use R to build, evaluate and use machine learning models, both for regression and classification. To understand how modern AI works and be able to use R to build simple AI models for analysing text and images.
Prerequisites: R2 or similar.
Kursinformation
R 5
Course length: 2 days
Language: English
Hours: 09:00-16:30 (CET)
Price: 12 500 SEK excluding VAT
Kurstillfällen
23-24 apr 2025
Online
3-4 jun 2025
Online
Förhandsbokning
(obestämt datum)
Program
MACHINE LEARNING
Evaluation of predictive models: test-training-splits, cross-validation
Regularised regression (lasso)
Nearest neighbours models
Decision trees, random forests and boosted trees
ARTIFICIAL INTELLIGENCE
Deep neural networks
Using AI models for analysis of text data
Using AI models for analysis of images
Information & Frågor
Questions?
Send us an email or Call us
Online course
All our online courses are instructor-led and on the Zoom video platform. Course literature and exercises are either distributed in conjunction with the course or delivered through mail well in advance before the course. This information and and other important instructions are found in your booking confirmation after a reservation is made.
Onsite courses
The address and any additional information is announced in an invitation email send out the week before the course. Course literature and exercise material are distributed onsite. Make sure you have access to a computer with the current program installed for the course.
Booking terms
Statistikakademin has the right to cancel any course in the event of an insufficient number of participants. In case of that happening, you will of course be offered a new course date or be fully compensated. You have the right to rescedule and change course dates up to 15 days before the start of the course. If something comes up last minute and you are not able to attend, you can of course send a colleague instead.
Kursledare
Måns Thulin
Appreciated educator with extensive statistical expertise
Måns Thulin works as a consultant and lecturer in statistics, machine learning, and artificial intelligence. His clients include large corporations, government agencies, startups, and researchers. By using advanced statistical analysis, he has solved problems in a wide range of areas, from antibiotic resistance to nuclear fuel, from milking robots to HR issues, from herniated discs to music videos. He has twelve years of teaching experience at institutions such as Uppsala University and the University of Edinburgh. Måns is also the author of the popular textbook Modern Statistics with R. His educational goal is to help all course participants understand statistical methods – statistics should feel logical, not like black magic.
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