Магистратура
2024/2025![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Семинар наставника
Статус:
Курс обязательный (Магистр по наукам о данных)
Направление:
01.04.02. Прикладная математика и информатика
Где читается:
Факультет компьютерных наук
Когда читается:
2-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Прогр. обучения:
Магистр по наукам о данных
Язык:
английский
Кредиты:
4
Контактные часы:
4
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
Interim Assessment
- 2023/2024 4th module1 * Individual Education Plan + 1 * Individual Education Plan
- 2024/2025 2nd module
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