With this function you can construct your weekly calendar of lessons, which is customized on the basis of the courses that you intend to follow. Warning: the personal schedule does not replace the presentation of the study plan! It's an informal tool that can help you better manage the organization of class attendance before the study plan presentation. After the study plan presentation we recommend you to use the Lecture timetable service in your Online Services.
To create your customized schedule follow these instructions:
- Click on the "Enable" link to proceed. You will be asked your surname and first name in order to determine your alphabetic grouping.
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To add or remove courses from your personal schedule, use the small icons which are found next to the courses:
- addition of the course
- removal of the course
- selection of the section of the Laboratory of Architecture
(Note: the effective area in which the teaching will be carried out will be determined after the presentation of the Study Plans)
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The sidebar on the left displays the number of lessons included in schedule.
There are also these commands:
- View the schedule: allows the viewing of the weekly synoptic schedule
- Delete the schedule: cancels the selections made
When you have finished the entry, you can print the calendar you have made.
Semester (Sem) | 1 | First Semester | 2 | Second Semester | A | Annual course | Educational activities | C | Similar or integrative activities | Language | | Course completely offered in italian | | Course completely offered in english | -- | Not available | Innovative teaching | | The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching. These CFUs include:
- Subject taught jointly with companies or organizations
- Blended Learning & Flipped Classroom
- Massive Open Online Courses (MOOC)
- Soft Skills
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Academic Year
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2018/2019
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School
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School of Industrial and Information Engineering
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Name
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(Master of Science degree)(ord. 270) - MI (474) Telecommunication Engineering
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Track
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Z2A - SIGNALS
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Programme Year
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1
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ID Code
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052534
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Course Title
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RECOMMENDER SYSTEMS
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Course Type
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Mono-Disciplinary Course
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Credits (CFU / ECTS)
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5.0
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Semester
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First Semester
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Course Description
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Recommender systems aim to support users in their decision-making while interacting with large information spaces. They recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems help overcome the information overload problem by exposing users to the most interesting items, and by offering novelty, surprise, and relevance. This course gave a tutorial about the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include a number of algorithms that result in techniques. The course also explore alternative techniques of evaluating recommender systems.
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Scientific-Disciplinary Sector (SSD)
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Educational activities
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SSD Code
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SSD Description
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CFU
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C
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ING-INF/05
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INFORMATION PROCESSING SYSTEMS
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5.0
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Innovative teaching
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The course includes 2.0 credits in Innovative Teaching as follows:
- Blended Learning & Flipped Classroom
- MOOC
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Schedule, add and remove | Alphabetical group | Lecturer(s) | Language | Teaching Assignment Details |
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From (included) | To (excluded) |
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--- | A | ZZZZ | Cremonesi Paolo | | |
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