Machine learning

  • Teaching

    Details

    Faculty Faculty of Science and Medicine
    Domain Biology
    Code UE-SBL.30002
    Languages English
    Type of lesson Lecture
    Level Master
    Semester SS-2023

    Schedules and rooms

    Summary schedule Monday 08:15 - 12:00, Cours bloc (Spring semester)
    Monday 13:15 - 17:00, Cours bloc (Spring semester)
    Wednesday 08:15 - 12:00, Cours bloc (Spring semester)
    Struct. of the schedule cours bloc - 10 jours

    Teaching

    Responsibles
    • Wegmann Daniel
    Teachers
    • Wegmann Daniel
    Description

    The aim of this course is to equip the students with the necessary skills to apply machine learning techniques in their own research. It focuses on numerical techniques such as Expectation Maximization and Markov Chain Monte Carlo, and introduces the use of Hidden Markov Models and approximate techniques to analyze genomic data. The course is paired with exercises allowing students to implement these techniques in “R” to analyze biological data.
    Softskills No
    Off field No
    BeNeFri Yes
    Mobility No
    UniPop No
  • Dates and rooms
    Date Hour Type of lesson Place
    20.02.2023 08:15 - 12:00 Cours PER 21, Room B130
    20.02.2023 13:15 - 17:00 Cours PER 07, Room 2.301
    22.02.2023 08:15 - 12:00 Cours PER 07, Room 1.309
    27.02.2023 08:15 - 12:00 Cours PER 21, Room B130
    27.02.2023 13:15 - 17:00 Cours PER 07, Room 2.301
    06.03.2023 08:15 - 12:00 Cours PER 21, Room B130
    06.03.2023 13:15 - 17:00 Cours PER 07, Room 2.301
    08.03.2023 08:15 - 12:00 Cours PER 07, Room 1.309
    13.03.2023 08:15 - 12:00 Cours PER 21, Room B130
    13.03.2023 13:15 - 17:00 Cours PER 21, Room E130
    15.03.2023 08:15 - 12:00 Cours PER 21, Room D230
    20.03.2023 08:15 - 12:00 Cours PER 21, Room B130
    20.03.2023 13:15 - 17:00 Cours PER 07, Room 2.301
    22.03.2023 08:15 - 12:00 Cours PER 21, Room D230
    27.03.2023 08:15 - 12:00 Cours PER 21, Room B130
    27.03.2023 13:15 - 17:00 Cours PER 21, Room E130
    29.03.2023 08:15 - 12:00 Cours PER 21, Room D230
    03.04.2023 08:15 - 12:00 Cours PER 21, Room B130
    03.04.2023 13:15 - 17:00 Cours PER 21, Room E130
    05.04.2023 08:15 - 12:00 Cours PER 21, Room D230
  • Assessments methods

    Written exam - SS-2023, Session d'été 2023

    Date 22.06.2023 14:00 - 15:30
    Assessments methods By rating
    Descriptions of Exams

    Written exam (90 min.). One mark

    Written exam - SS-2023, Autumn Session 2023

    Date 12.09.2023 15:30 - 17:00
    Assessments methods By rating
    Descriptions of Exams

    Written exam (90 min.). One mark
  • Assignment
    Valid for the following curricula:
    Additional Courses in Sciences
    Version: ens_compl_sciences
    Paquet indépendant des branches > Specialized courses in Biology (Master level)
    Additional programme requirements for PhD studies [PRE-DOC]
    Version: 2020_1/v_01
    Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Biology (Master level)
    Bioinformatics [3e cycle]
    Version: 2024_2/V_01
    Continuing education > Specialized courses in Biology (Master level)
    Biology [3e cycle]
    Version: 2024_2/V_01
    Continuing education > Specialized courses in Biology (Master level)
    Biology [POST-DOC]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Biology (Master level)
    MSc in Bioinformatics and Computational Biology [MA] 120
    Version: 2024_1/V_01
    MSc in Bioinformatics and computational biology, courses > MSc-BI, Module “Statistics” (from AS2022 on)
    Ma - Accounting and Finance - 120 ECTS
    Version: 2024-SP_V02 - DD Caen
    UniFr courses > Modules "Data Analytics" and "Audit et Fiscalité": min. 2 courses > DAT: Data Analytics
    Ma - Accounting and Finance - 90 ECTS
    Version: 2021-SA_V02 - Dès SA-2024
    Course - 72 ECTS > Modules "Data Analytics" and "Audit et Fiscalité": min. 3 courses > DAT: Data Analytics > Elective courses
    Ma - Business Communication : Business Informatics - 90 ECTS
    Version: 2024-SA_V03
    Information Management > Cours > Modules management > DAT: Data Analytics
    Ma - Business Informatics - 90 ECTS
    Version: 2020-SA_V01
    Classes - min. 45 ECTS > Modules management - max. 15 ECTS > DAT: Data Analytics
    Ma - Data Analytics & Economics - 90 ECTS
    Version: 2020-SA_V02
    Courses min 63 ECTS > Mandatory Modules (45 to 63 ECTS) > Module I: Data Analytics (Data) > Elective courses
    Ma - International and European Business - 90 ECTS
    Version: 2021-SA_V01 - dès SA-2024
    Courses > Modules > Elective courses of the management modules > Elective courses of the management modules > Elective courses for the Master in management
    Courses > Modules > One complete module taken from the following list > DAT Module validation element group > DAT: Data Analytics > Elective courses
    Ma - Management - 90 ECTS
    Version: 2021-SA_V03 - Dès SA-2024
    Courses: min. 72 ECTS > Modules - min 54 ECTS > Elective courses taken outside a validating module > Elective courses in the management modules > Elective courses for the Master in management
    Courses: min. 72 ECTS > Modules - min 54 ECTS > Minimum of 3 modules with a minimum of 18 ECTS and 2 core courses > DAT Module validation element group > DAT: Data Analytics > Elective courses
    Ma - Marketing - 90 ECTS
    Version: 2021-SA_V03 - Dès SA-2024
    Courses - 72 ECTS > Complementary module > DAT Module validation element group > DAT: Data Analytics > Elective courses
    MiMa - Business Informatics - 30 ECTS
    Version: 2020-SA_V01
    Cours > Modules management > DAT: Data Analytics
    MiMa - Gestion d'entreprise - 30 ECTS
    Version: 2021-SA_V01
    Elective courses - 30 ECTS > DAT: Data Analytics