Target audience
Participants interested in having a practical introduction to machine learning for analysing data and addressing competition-enforcement challenges.
Intended Learning Outcomes
At the end of the course, participants will be able to:
- Understand and categorize a machine learning problem
- Choose the appropriate technique to address a machine learning problem
- Implement or use already implemented versions of the basic machine learning techniques
Estimated Time for Completion
12 hours
Level
Level 6: Bachelor’s degree (first cycle)
Type of the assessment
Quizzes and project evaluation
Form of participation in the learning activity
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Asynchronous learning (videos, quizzes, exercises)
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live training workshop (exercise resolution and clarification)
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Project work in groups
Pre-requisites
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Basics of Python programming
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Basics of linear algebra and probability
Course Content
Week 0 - Introduction to the course
Week 1 - Introduction to Machine Learning
Week 2
About Instructor
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