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Course 2021-2022 a.y.

30586 - MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE LAB

BSU
Department of Decision Sciences

Course taught in English

Go to class group/s: 95

BSU (I sem. - OP)
Course Director:
RICCARDO ZECCHINA

Classes: 95 (I sem.)
Instructors:
Class 95: RICCARDO ZECCHINA


Suggested background knowledge

For a fruitful and effective learning experience, it is recommended a preliminary elementary knowledge of algebra, calculus and probability.


Mission & Content Summary
MISSION

The purpose of this course is to present some basic methods of modern artificial intelligence, highlighting both their strength and their limitations.

CONTENT SUMMARY

 

  • Elements of statistical inference
  • Elements of machine learning
  • Example of applications
  • Simple programming exercises

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...

- undestand the main differences between the tools which compose modern AI

- understand the elementary aspects of the methodological foundation of machine learning

APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...

- discriminate netween different problem types

- undestand tools should be used

- formulate questions in a quantitative form (optimization problem)

 


Teaching methods
  • Online lectures
DETAILS

Each online lecture will be self-contained and devoted to a specific topic.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
    ATTENDING AND NOT ATTENDING STUDENTS

    Multiple choice question will serve the scope of checking that the students have acquired a sufficient level of understanding of the most basic and elementary  methods and propblems of AI


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    huandouts will be provided prior to the course

    Last change 29/06/2021 17:15