Machine Learning

 

An overview of the techniques that are transforming many industries and will change our lives.

Provided ByPolitecnico di Milano
Type of providerHE Institution
Provided athttps://www.pok.polimi.it/
Learning opportunity typeMOOC
Languageen
Home pagehttps://www.pok.polimi.it/courses?search_query=AI105
Start date2022-02-21
End date2023-01-22
Duration11
Workload in hours8
Admission procedureOpen to all
Price detailsYou can access the course absolutely free of charge.
AssessmentsThe final grade for the course is based on results from your responses to the quizzes you will find at the end of each week (weekly quizzes). You will successfully complete the course if you reach 60% (or more) of the total score by the end of the edition. The course’s total score will be calculated by averaging the scores of the assessed quizzes for each individual week.
Type of credentialCertificate of participation
ISCEDF Code0619 - Information and Communication Technologiesn.e.c.
Education subject061 Information and Communication Technologies (ICTs) 0619 Information and Communication Technologies not elsewhere classified 071 Engineering and engineering trades 0714 Electronics and automation
Learning settingsnon formal learning
Learning outcomeMachine learning – LO – Classify machine
Classify machine learning problems
Learning outcome typeSkill
Reusability levelSector specific skills and competences
Related skillhttp://data.europa.eu/esco/skill/8369c2d6-c100-4cf6-bd83-9668d8678433
Learning outcomeMachine learning – LO – Classify supervised
Classify supervised learning problems
Learning outcomeMachine learning – LO – Classify unsupervised
Classify machine learning problems in unsupervised learning
Learning outcomeMachine learning – LO – Describe how
Describe how to optimize a policy in reinforcement learning
Learning outcomeMachine learning – LO – Describe the limitations
Describe the limitations of machine learning techniques in supervised learning
Learning outcome typeKnowledge
Reusability levelSector specific skills and competences
Related skillhttp://data.europa.eu/esco/skill/e465a154-93f7-4973-9ce1-31659fe16dd2
Learning outcomeMachine learning – LO – Describe the main
Describe the main techniques for identifying clusters of data
Learning outcomeMachine learning – LO – Describe the utility
Describe the utility of dimensionality reduction techniques
Learning outcomeMachine learning – LO – Explain
Explain what a value function is and how it can be estimated using reinforcement learning
Learning outcomeMachine learning – LO – Formulate
Formulate a sequential decision-making problem
Learning outcomeMachine learning – LO – Identify
Identify the key elements of supervised learning algorithms
Learning outcome typeKnowledge
Reusability levelCross-sector skills and competences
Related skillhttp://data.europa.eu/esco/skill/54924a2c-daca-40d3-9716-4b38ceb04f38
Learning outcomeMachine learning – LO – Perform
Perform model evaluation and selection in supervised learning
Assessor typeartificial intelligence
Assessment formatautomatic grading
Awarding opportunityThe Certificate of Accomplishment will be released to anyone who successfully completes the course by answering correctly to at least 60% of the questions by the end of the edition. You will be able to download the Certificate of Accomplishment directly on the website. Once you have successfully passed the course, you can request the Certificate of Accomplishment without waiting for the end of the edition. The Certificate of Accomplishment does not confer any academic credit, grade or degree.

Back to search