Syllabus

LEARNING OUTCOMES

Understanding of the general principles of deep learning, and the central deep learning methods discussed in the course. After the course, you should be able to apply them to real-world data sets.

Credits: 5

Schedule: 28.02.2023 - 30.05.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Alexander Ilin

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

• valid for whole curriculum period:

  Fundamental and current topics of deep learning. Implementing algorithms on a computer are a part of the course and the programming language is Python. Python-based softwares that allow for symbolic differentiation will also be used.

Assessment Methods and Criteria

• valid for whole curriculum period:

  Exercises and exam.

Workload

• valid for whole curriculum period:

  1 lecture per week (1h 30 min total each), one computer exercise session per week (1 h 30 min total each), and the rest for studying the course material and doing exercises.

DETAILS

Substitutes for Courses

• valid for whole curriculum period:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language : English

  Teaching Period : 2022-2023 Spring IV - V
  2023-2024 Spring IV - V

  Enrollment :

  Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

Description