Calendar and presentation links updated!
November 21st, 2021 22:00
Data Collection available to the participants!
November 12th, 2021 11:00
Calendar and presentation links updated!
November 1st, 2021 22:00
September 15th, 2021 23:41
This class will start on Monday September 20th.
September 19th, 2021 16:30
Last modification: December 3th, 2021 10:20
The Fall 2021 Edition of the course Studies on Human Behaviour is delivered in the classrooms. We will also provide some complementary asynchonous material
The idea behind this course is that the students do most of the work during the course duration (up to December) because we believe this should yield considerably better results.
The course runs from September 20, 2021 till December 13, 2021 with the following schedule:
Mondays, time 11:15 - 13:00 (Classroom 10)
Wednesday, time 14:15 - 16:00 (Classroom 11)
Always check the official University calendar on Moodle.
You might want to read the Instructions to understand how to take the course.
Notice also the titles and structure of the lessons yet to be delivered might change slightly . The rule of the thumb is: if there are links with materials, things won’t change; if there are no links to the materials, titles and content are just suggestions.
|Date||Id||Modality||Starts at||Zoom||Recordings||Material||Content of Lesson||Professor(s)|
|20 Sep, 2021||L1||11:15||Slides||Course Introduction.||I. Bison|
|Slides||Course Introduction. Projects organization.||F. Giunchiglia|
|Slides||Course Introduction. Planning a project.||M. Chierici|
|Slides||Course Introduction. Technical bits.||M. Rodas|
|22 Sep, 2021||L2||14:15||Theory driven vs. Data driven vs. Knowledge Driven||I. Bison|
|15:00||Theory driven vs. Data driven vs. Knowledge Driven||F. Giunchiglia|
|27 Sep, 2021||L3||-||-||Why Human Behaviour? Why diversity? From a computer science perspective.||F. Giunchiglia|
|29 Sep, 2021||L4||14:15||Why Human Behaviour? Why diversity? From a sociological perspective.||I. Bison|
|Slides||How to do a literature review. How to write a research project (1st part).||M. Chierici|
|4 Oct, 2021||L5||11:15||Active data: Questionnaire for synchronic and diachronic data & Type of social data.||I. Bison|
|Slides||How to write a research project 2nd Part.||M. Chierici|
|11 Oct, 2021||L6||14:15||-||Slides, i-Log video||Methods and tools for data collection. Passive data: smartphones or other devices.||M. Rodas|
|13 Oct, 2021||-||-||-||-||-||-||iLog data collection starts.||-|
|13 Oct, 2021||L8||14:15||-||Groups: project plan discussion.||I. Bison, F. Giunchiglia, M. Chierici, M. Rodas|
|18 Oct, 2021||L9||-||-||Slides||Data Science Pitfalls.||M. Chierici|
|20 Oct, 2021||L10||14:15||-||Slides, Material||Instruments for data collection. Capture in-the-time data (diachronic and streaming data).||M. Rodas|
|25 Oct, 2021||L11||11:15||Sample design, sampling, and Field Experiment.||I. Bison|
|27 Oct, 2021||-||-||-||-||-||-||iLog data collection ends.||-|
|27 Oct, 2021||L12||14:15||Sample design, sampling, and Field Experiment; The timing (frequencies) of data collection.||I. Bison|
|3 Nov, 2021||L13||11:15||-||Groups: data collection architecture.||I. Bison, F. Giunchiglia, M. Chierici, M. Rodas|
|8 Nov, 2021||L14||14:15||-||Groups: data collection architecture.||I. Bison, F. Giunchiglia, M. Chierici, M. Rodas|
|10 Nov, 2021||L15||14:15||The recruitment; Field supervising; Ethical & GDPR aspects.||Ronald Chenu Abente Acosta, Ivano Bison|
|15 Nov, 2021||L16||11:15||-||Slides||Data platforms for big data.||M. Rodas|
|17 Nov, 2021||L17||14:15||Slides, Material||Data visualization in biology.||M. Chierici|
|17 Nov, 2021||-||-||-||-||-||-||Data from the i-Log data collection experiment is made available to the students. (Done!)||-|
|22 Nov, 2021||L18||-||-||Slides||Data cleaning and methods for data preparation.||F. Giunchiglia|
|24 Nov, 2021||L19||11:15||Synchronic and Diachronic statistical models.||I. Bison|
|29 Nov, 2021||L20||-||-||Slides||Data Integration Methodology Structure||F. Giunchiglia|
|01 Dic, 2021||L21||11:15||Slides, Materials||Networks and differential network analysis||I. Bison, M. Chierici|
|6 Dec, 2021||L22||14:15||?||Network models.||I. Bison|
|8 Dec, 2021||L23||11:15||-||Final groups presentations||I. Bison, F. Giunchiglia, M. Chierici, M. Rodas|
|13 Dec, 2021||L24||11:15||-||Final groups presentations||I. Bison, F. Giunchiglia, M. Chierici, M. Rodas|
The aim of this course is to study the behaviour of people. The course is data intensive and hands on. It covers all the phases from experiment design, data collection, data preparation and data analysis. After a brief theoretical introduction, the course will consist of running real world experiments, on large amounts of data. The exam will consist of presenting the results of the experiment in a public presentation. This inter-disciplinary course bridges competences in sociology, ethics and computer science.
People interested in knowing more details about what we do in this course can refer to these books:
Mainly about Data Science:
Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006.
Grus, Joel. Data science from scratch: first principles with python. O'Reilly Media, 2019.
VanderPlas, Jake. Python data science handbook: Essential tools for working with data. O'Reilly Media, 2016.
Mainly about systems and frameworks for Big Data:
Carpenter, Jeff, and Eben Hewitt. Cassandra: the definitive guide: distributed data at web scale. O'Reilly Media, 2021.
Chambers, Bill, and Matei Zaharia. Spark: The definitive guide: Big data processing made simple. O'Reilly Media, 2018.
The examination consists in the preparation of a written paper that will be presented at the end of the course in December.
The slots when the paper has to be presented are highlithed in the calendar.
IMPORTANT: You must register to ESSE3 in order to take part to the written exam. The registration (mandatory) concludes the exam.
Multiple positions are available as 150h and internships. They should be considered as the first part of a research project and thesis with the Knowdive group. The general activities of the group are listed on the website (http://knowdive.disi.unitn.it/), while activities already scheduled and available now can be found at http://knowdive.disi.unitn.it/work-with-us/. The 150h activities have variable length and are strictly related to software development: for this reason, knowledge of software development with at least onr programming language is a must. All the activities can also be carried on in a remote fashion.
Anyone interested in these opportunities can send an email to email@example.com, providing already information about preferences in terms of topics or activities (if known). For 150h activities it is important to provide information about known programming languages with the corresponding level, a value in the range [1 - 5] where 1= basic knowledge, 5= advanced knowledge.
The applications to the “150 ore” program can be done at the link: https://www.unitn.it/servizi/224/collaborazioni-studenti-150-ore Notice that the deadline for applications for the A.Y 2021-2022 is September 30, 2021