Working practices
Experiment with examples and divide your work
When reading the materials, try out the examples, experiment, and search for more information online. Most importantly, set up a local working environment from the get-go and use it for the programming-related coursework. This way, you will also learn to work with the tools of the trade.
Schedule-wise, as research on learning has shown over and over again that distributed practice leads to better learning outcomes than massed practice, divide your work over multiple days each week. If you feel like you are lacking focus, try the Pomodoro technique or other time management techniques, and remember to take breaks.
Coursework
The course materials include graded quizzes, programming assignments, and an overarching project. Trying out the examples helps you in solving the programming assignments. Some of the coursework is automatically graded, while some is graded by the course staff upon course completion.
For Aalto University students and exchange students, the course has an on-campus end-of-course exam. Exam details are available in Aalto MyCourses.
Some of the programming assignments in the early parts of the course can be returned directly using an embedded programming environment. For larger assignments and the overarching project, use a local programming environment for development and testing.
For some coursework, possible template code is given as zip-files and coursework is returned as zip-files.
Academic integrity
The coursework is to be completed individually. Sharing your solutions with others is strictly forbidden.
As the coursework have been created to help everyone learn, do not take away that opportunity. Do not share your solutions to the coursework or store them in any publicly available location.
All submitted coursework is also periodically checked for plagiarism. Plagiarism, i.e. representing the work of others as your work, will naturally lead to a failed course and other ramifications. For further details, see Aalto University Code of Academic Integrity and Handling Violations Thereof.
Use of generative AI
Learning takes effort. Generative AI tools have been shown to be useful for learning, especially when you know what you are doing, and explicitly focus on making sure that you learn the content and practices that the tools are helping you with. At the same time, such tools can also be used to avoid learning, if you do not pay attention to what you are doing.
In this course, the use of generative AI and large language models for assisting with the coursework is allowed. This includes tools such as Github Copilot and ChatGPT. If you do not have access to a generative AI assistant, the platform provides an assistant. You can find it on the lower right corner of the material pages when logged in — clicking it opens up a chat.
The course staff will not provide support for using generative AI assistants, and any help requests related to issues from using them may be completely skipped. For more details, see support and discussion.