Language: English
Deep learning
Max amount of FITech students: 75 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course introduces the fundamental and current topics of deep learning. In every weekly assignment, the students get to train a deep neural network for various tasks including image
Introduction to embedded systems
Core content Complementary knowledge Learning outcomes Teaching schedule Lectures are 10.1.–21.2.2024 at 10–12 and the laboratory work groups meet starting from 5.3.2024. More information in the Tampere University study guide. You can get a digital badge after completing this course.
Secure programming
The aim of secure programming is to prevent errors as early as possible. Core content Complementary knowledge Learning outcomes After completing the course, the student is able to apply secure programming skills in programming and decision making. In addition, the student selects a topic area from the course where they deepen their knowledge. Completion methods
Human-centered product development
Core content Learning outcomes After completing the course, the student understands how to take user needs and requirements into account when developing interactive products in general and in software projects in particular. The student can apply a lean human-centered design process in design and development activities. The student also knows how to Completion methods The
Gamification: A walkthrough of how games are shaping our lives
The course gives a broad overview of how games and game-related technologies shape our lives. The course enables the student to understand and analyse the pervasiveness of games and game-related technologies in different domains of culture and society, how they affect and shape our behaviours and interactions with the world. After completing the course, the
Emerging technology adoption and use
Core content Complementary/specialist knowledge Learning outcomes After the course, the students Teaching methods Attending 50 % of the lectures on campus and successfully completing 1) three lecture diary reports (individual assignment) and 2) the course exercise (group assignment). More information in Tampere University’s study guide. You can get a digital badge after completing this course.
Machine learning algorithms
Max amount of FITech students: 10 During this course, some of the most important machine learning algorithms are presented and examples for their applications are described. After the course, the student is able to understand and use some basic and advanced machine learning methods for data mining, pattern recognition and other problems to that learning-based
Principles of programming graphical user interfaces
During the course, participants will learn how to create graphical user interfaces utilising commonly used user interface components. User interface creation is studied using both interface builders in integrated development environments and on program code level. In addition, event-based programming, software architecture designs related to graphical user interfaces and some common design models will be
Internet marketing techniques
This course deals with issues related to, for example, search engine optimisation, social media marketing, e-mail marketing, and targeted advertising. Content: After completing the course the student masters Internet marketing related technical solutions and their characteristics. The student is able to analyse the effectiveness of Internet marketing and e-commerce with different tools and meters. The
Concurrency
Max amount of FITech students: 40 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents Process and thread Parallelism as a concept Critical area, exclusion Syncronising Blockage, starvation Learning outcomes The student recognises the basic problems caused by concurrency (critical area, starvation,