Mentor's Seminar

2024/2025

Учебный год

ENG

Обучение ведется на английском языке

Кто читает:

Департамент больших данных и информационного поиска

Статус:

Курс обязательный

Когда читается:

1-й курс, 1-4 модуль

Преподаватель

Бекларян Армен Левонович

Course Syllabus

Abstract

The discipline Master's Seminar takes place during the whole course of study and is compulsory for students of the Study Program "Master of Data Science";. In the course of communication with the academic supervisor, the student forms his/her individual study plan, receives additional feedback for the master's thesis.

Learning Objectives

• The aims of the discipline are: (1) to form an individual curriculum, (2) to choose a theme of the master's thesis

Expected Learning Outcomes

• know the rules of writing master thesis
• prepare a brief of the master thesis
• knows the key stages and deadlines for master thesis preparation and delivery
• An individual education plan for the second year
• Correcting the syllabus and term or master's thesis work
• Selecting a track

Course Contents

• Individual academic trajectories
• The master's thesis

Assessment Elements

• Individual Education Plan
• Master Thesis

Interim Assessment

• 2024/2025 2nd module
  0.5 * Individual Education Plan + 0.5 * Master Thesis
• 2024/2025 4th module
  0.5 * Individual Education Plan + 0.5 * Master Thesis
• 2025/2026 3rd module
  0.5 * Individual Education Plan + 0.5 * Individual Education Plan + 0.5 * Master Thesis + 0.5 * Master Thesis

Bibliography

Recommended Core Bibliography

• A Tutorial on Machine Learning and Data Science Tools with Python. (2017). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E5F82B62
• Machine learning : beginner's guide to machine learning, data mining, big data, artificial intelligence and neural networks, Trinity, L., 2019
• Machine learning : the art and science of algorithms that make sense of data, Flach, P., 2014
• Rogers, S., & Girolami, M. (2016). A First Course in Machine Learning (Vol. 2nd ed). Milton: Chapman and Hall/CRC. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1399490

Recommended Additional Bibliography

• A first course in machine learning, Rogers, S., 2012
• Foundations of machine learning, Mohri, M., 2012

Authors

• Ахмедова Гюнай Интигам кызы