What you will learn
- Select the best ANN architecture for the certain task
- Construct training dataset for the certain task
- Train ANN manually
- Train ANN using Google colab
About this course
Tha main goal of this course is to study the basic principles of artificial neural networks (ANN).
This course is a part of double degree master program RCSE between KNRTU-KAI and TU Ilmenau. The main part of further research and further courses is concentrated on Deep learning techniques, so it is important to know the basic principles of ANN.
After this course students will know how to effectively solve different practical tasks with using artificial neural networks. They would select the best ANN architecture, train and evaluate it.
This course includes the following chapters:
- Basic concepts of neural networks
- Single layer ANN
- Mulitlayer perceptron
- Self-organizing networks
- Recurrent neural networks
- Deep learning models
Each chapter contains several mini-lectures with the short video, interactive Web 2.0. instruments to reinforce the study material, practical tasks needed to decide manually or with using Google colab.
Проект реализуется победителем конкурса "Академический десант" благотворительной программы "Стипендиальная программа Владимира Потанина" Благотворительного фонда Владимира Потанина"
Whom this course is for
The course is designed for undergraduates of technical universities, as well as technical specialists with a basic technical or mathematical education. This course is a part of double degree master program RCSE between KNRTU-KAI and TU Ilmenau. Other MSc or BSc students who is interested artificial neural networks can study it.
To successfully study the course "Basics of neural networks", students should be familiar with such disciplines as "Linear Algebra", "Numerical Methods".
Meet the Instructors
How you will learn
Training takes place sequentially, from the topic "Basic concepts of neural networks", then the topic "Single layer ANN", "Multilayer perceptron", "Self-organizing maps", "Recurrent neural networks", "Deep learning models". For each topic video lectures, lectures in the form of text and tests are provided. Theoretical tests are checked automatically. The results of the laboratory work are checked by the teacher. Additionally, students can discuss the studied topics in special "Discussion Rooms". Also, if desired, each student can comment on scientific articles proposed for study.
What you will get
- You will gain knowledge and skills in the field of artificial neural networks that are in demand in real life.