Summer School 2022

Aim and Organization

As part of its activities, the MSc in Data Science organizes a yearly summer school to acquire valuable credits to qualify for the enrollment into the programme.

Key information

When18/07/2022 – 30/07/2022

Schedule: Download the Summer School Schedule (2 pages)

Format: The Summer School is organized in 6 modules taking place over a two-weeks period. Modules take place in different formats:
– Mathematics and Statistics: HYBRID (remote and/or in-class lectures, check the schedule for more information).
– Economic, Psychological and Sociological Sciences: ONLINE (all lectures will take place on Zoom)
– Computer Science: EXCLUSIVELY IN-CLASS (NO online lectures)

***For further information, please check module’s description below***

Where:
– In class lectures will take place at the Department of Sociology and Social Research at UniTrento. Room numbers will be announced at the end of the registration period.
Online lectures will take place on Zoom. Links will be announced at the end of the registration period.

Teaching Language:
Modules of Mathematics and Statistics: ENGLISH
Modules of Economic, Psychological and Sociological Sciences: ENGLISH
Modules of Computer Science: ITALIAN

How to apply: Fill in the registration form at this link

Registration deadline: ***11 July 2022, 12PM****

Maximum number of courses: Students can attend up to 4 modules – max. 2 modules #1 (first week) and  max. 2 modules #2 (second week).

Course Prices:

–Modules #1 (first week): 170€ (individual fee)

–Modules #2 (second week): 80€ (individual fee)

Payment Method: Credit Card or Bank Transfer

Attendance requirements: Attendance is mandatory. In order to qualify for final exams and/or obtain an attendance certificate, students must be present at least 15 out of the 18 hours that are scheduled for each course.

CFU Recognition: Credits obtained upon completion of Summer School courses are recognized as follows:
– For undergraduate students from the Departments of Economics, Industrial Engineering, Information Engineering and Computer Science, and Matematics: CFUs are recognized as extra-numerary (i.e., crediti sovranumerari);
– For undergraduate students from the Departments of Psychology and Cognitive Science, Sociology and Social Research: only for undergraduate students, CFUs are recognized as free choice credits (i.e., crediti a scelta libera)
– For students of the MSc in Finance (DEM): only CFU obtained with the Computer Science Module of the Summer School are recognized as free choice credits (i.e., crediti a scelta libera)
– All other attendees will receive a certificate attesting the successful completion of courses. Requests for the recognition of Summer School CFUs should be addressed to the Department they belong to.

Admissions requirements: Summer School courses are open to students who own only some of the credits that are necessary to enroll in the Data Science MSc or just want to refresh their knowledge in the courses areas. Please note that the computer science modules (Informatica #1 and Informatica #2) require participants to perform a few preliminary preparation steps and to hold specific skills (Informatica #2). Check out single modules’ description for more detailed information.

Modules Description and Contents

Modules 1 – First Week – 18/23 July 2022

Informatica #1
(18/07/2022 – 23/07/2022)
18 Hrs, 3 CFU INF/01

Title: Foundations of Python Programming

Instructor: TBD

Contents:
– Tools, basics
– Strings
– Lists
– Tuples, Sets, Dictionaries
– Conditionals, for loops
– While, sequences

Suggested Readings:

– SoftPython, Fondamenti: https://it.softpython.org/#A—Fondamenti

– Allen Downey, Pensare in Python Italiano–2nda edizione: https://github.com/AllenDowney/ThinkPythonItalian/raw/master/thinkpython_italian.pdf

– Nicola Cassetta, Tutorial Python: http://ncassetta.altervista.org/Tutorial_Python/index.html

Teaching mode and Language: Classes will be exclusively in presence and in Italian. No remote learning solutions can be requested or arranged.

Final test: The final test will consist of a written exam. More detailed information on the time and the modes/platform to perform the test will be provided by the instructor upon course beginning.

Module requirements:

Computer: Students are required to bring their laptop computer (not a tablet!) with:

– at least 4GB RAM

– at least 5GB free of hard drive

– Operating System: Windows 8 or more recent, 64-bit macOS 10.13or more recent,Linux (any distribution)

Software: Before participating, you are strongly advised to install the following software:

Anaconda for Python 3.9download page (if you have less than 5GB free, install Miniconda)

LibreOffice 7.2.7:  download page

Browser:  anyamong Chrome, Firefox o Safari (InternetExplorer / Edge is not for Data Scientists…)

Software Videocall Check (extra): a software videocall will take place to ensure everybody owns the necessary software and it is working properly. Dates and Times for appointments will be communicated to enrolled students.

Mathematics and Statistics #1
(18/07/2022 – 23/07/2022)
18 Hrs, 3 CFU for any of MAT/, SEC-S/

Title: Linear Algebra

Instructor: Mario Lauria (mario.lauria[at]unitn.it)

Contents

– The set R^n. Vectors in R^n. R^n as a vector space.
Definition of a matrix. The determinant of a matrix. Inverse matrix. Rank of a matrix.
Systems of linear equations. Solutions of a system of equations: Rouche’-Capelli theorem and Cramer theorem.

– Functions: What is a function. General notions on functions. The main elementary functions. The graphs of the elementary functions: the line, the parabola, the equilateral hyperbola, the power, exponential and logarithmic functions.
Intro to statistics. Graphical representation of data. Arithmetic mean, median, mode. Measures of dispersion.

Suggested Readings: A. Guerraggio (2018). Matematica per le scienze. Person Education Limited

Teaching Mode and Language: Classes will take place in English and a in-class with the possibility to follow lectures online. In class participation is highly encouraged. If you plan to attend online, please get in touch with your instructor for arrangements before class starts. 

Final Test: The final test will consist in a written exam administered on the last day of class (Saturday). More detailed information will be provided by the instructors at the beginning of the course.

Economic, Psychological and Sociological Sciences #1
(18/07/2022 – 23/07/2022)
18 Hrs, 3 CFU for any of SPS/, SECS-P/, M-PSI/

Title: An introduction to SPSs

Contents

– Introduction to economics (6 hours): As an introduction to economics the module will first propose an overview of the principles and practices of economics:optimization, equilibrium, and empiricism; The module will then move the analysis of individual decisions: consumers and firms, to then show how market works, including the analysis of supply and demand, the competitive equilibrium and market failures. Finally a case study highlighting how data are typically used in economics will be proposed.
Instructor: Luca Piccoli

– Introduction to psychology (6 hours): A selection of some elementary concepts about psychology are presented in a simple and integrated fashion. Basic descriptions of psychological sectors (e.g., personality psychology, organizational psychology, psychometrics, clinical psychology) and basic definitions of psychological constructs/variables (e.g., motivation, individual differences, work engagement, personality traits, burnout) are illustrated within an integrated theoretical-methodological approach.
Instructor: Enrico Perinelli (enrico.perinelli[at]unitn.it)

– Introduction to sociology (6 hours): This section of the module will discuss some of the main research traditions of sociological research with particular emphasis on analytical and structural sociology, and digital sociology. We will discuss some of the main objects of sociological research, how they have been operationalized and the challenges involved.
Instructor: Elena Pavan (elena.pavan[at]unitn.it]

Suggested Readings:

– Acemoglu, D., Laibbson, D. and List, J. (2019). Economics. Pearson. 

– The CORE team, The Economy. Available at: https://www.core-econ.org.

– The CORE team, Doing Economics. Available at: https://www.core-econ.org..

– Mankiw, N. G. (2020). Principles of economics. Cengage Learning.

– Goldthorpe, J. H. (2016). Sociology as a population science. Cambridge: Cambridge University Press.

– Marres, N. (2017). Digital Sociology: The reinvention of social research. Cambridge: Polity Press.

– Veltri, G.A. (2020). Digital Social Research. Cambridge: Polity.

Teaching Mode and Language: Classes will take place in English and online on Zoom. Lectures links will be announced before the class starts

Final Test: The final test will consist of an oral exam. More detailed information on the time and place for the test will be provided by the instructors upon course beginning.

Modules 2 – Second Week – 25/30 July 2022

Informatica #2
(25/07/2022 – 30/07/2022)
18 Hrs, 3 CFU INF/01

Title: Foundations of Algorithms in Python

Instructor: TBD

Contents:
– Functions, Error handling and testing
– Matrices as list of lists, composite data structures
– Sequences, line files
– Tabular data, CSV, JSON formats
– Matrices – Numpy, Visualization
– Analytics with Pandas

Prerequisites (IMPORTANT):  If you enroll only to module 2 without having attended module 1, prior to attending make sure you have the required python skills: to assess yourself, you should be able to perform in a couple of hours part A of these old exams: https://sps.davidleoni.it/#Esami-passati

Suggested Readings:

– SoftPython, Fondamenti: https://it.softpython.org/#A—Fondamenti

– SoftPython, Analisi dati (formati, visualizzazione, pandas): https://it.softpython.org/#B—Analisi-dati

– Allen Downey, Pensare in Python Italiano– 2nda edizione:  https://github.com/AllenDowney/ThinkPythonItalian/raw/master/thinkpython_italian.pdf

– Nicola Cassetta, Tutorial Python: http://ncassetta.altervista.org/Tutorial_Python/index.html

Teaching mode and Language: Classes will be exclusively in presence and in Italian. No remote learning solutions can be requested or arranged.

Final test: The final test will consist of a written exam. More detailed information on the time and the modes/platform to perform the test will be provided by the instructor upon course beginning.

Module Requirements:

Computer: Students are required to bring their laptop computer (not a tablet!) with:

– at least 4GB RAM

– at least 5GB free of hard drive

– Operating System: Windows 8 or more recent, 64-bit macOS 10.13or more recent,Linux (any distribution)

Software: Before partecipating, you are strongly advised to install the following software:

Anaconda for Python 3.9download page  (if you haveless than 5GB free, install Miniconda)

LibreOffice 7.2.7:  download page

Browser:  any among Chrome, Firefox o Safari (InternetExplorer / Edge is not for Data Scientists…)

Software Videocall Check (extra): a software videocall will take place to ensure everybody owns the necessary software and it is working properly. Dates and Times for appointments will be communicated to enrolled students.

Mathematics and Statistics #2
(25/07/2022 – 30/07/2022)
18 Hrs, 3 CFU for any of MAT/, SEC-S/

Title: Introduction to Statistics

Instructor: Marco Chierici (chierici[at]fbk.eu)

Contents:
– Data: statistical units, variables, and measurement scales. Graphical methods, tabular tools, and numerical measures for univariate and bivariate descriptive analysis.
– Probability: basic concepts and definitions, random variables, and probability distributions.
– Sampling and sampling distributions.
– Inferential statistics: confidence interval estimation and hypothesis tests
Simple linear regression model.

Suggested Readings:
– Newbold P, Carlson WL & Thorne BM, Statistics for Business and Economics, Eighth or Ninth (Global) Edition, Pearson Education Limited.

– Illowsky B, Dean S, et al, Introductory statistics, OpenStax

Teaching Mode and Language: Classes will take place in English and online on Zoom. Lectures links will be announced before the class starts

Final Test: The final test will consist of a written exam administered on the last day of class (Saturday, July 30th, 9-12): the exam has to be submitted on the Moodle platform. More information will be provided by the Instructor upon course beginning.

Economic, Psychological and Sociological Sciences #2
(25/07/2022 – 30/07/2022)
18 Hrs, 3 CFU for any of SPS/, SECS-P/, M-PSI/

Title: Modeling and Methodology

Contents:
– Introduction to management (6 hours): Systems of work organization: Lean production features and challenges for managers, unions and workers; Comparative human resource management and employment relations;institutions and actors’ agency; Discussion of some cases on the concepts treated
Instructor: Andrea Signoretti

– Introduction to quantitative methods in psychology (6 hours): We will cover the main quantitative methods used in psychological research, with a particular focus to the study of individual differences. Topics will cover: the concepts of reliability and validity; the measurement of psychological unobservable phenomena through latent variable statistical approaches; the impact of data science advancements in psychological research.
Instructor: Enrico Perinelli (enrico.perinelli[at]unitn.it)

– Introduction to sociological methodology (6 hours): We will cover the main epistemological and methodological aspects of research with social data using quantitative,qualitative and mixed methods. We will focus more on quantitative methods, in particular on the nature of data available, the construction and use of valid research instruments and the different methods of analysis applied to social data.
Instructor: Giuseppe Alessandro Veltri (giuseppe.veltri[at]unitn.it)

Suggested Readings:
– Antilla, T., Oinas, T., and Mustosmaki, A. (2021). Lean in Europe and the USA. A New Dominant Division of Labour? In Janoski, T., Lepadatu, D. The Cambridge International Handbook of Lean Production, chapter 17, pp. 423-447.

– MacDuffie, J.P. (2021) The Industrial Relations Perspective on Lean Systems, Workers, and Unions. In Janoski, T., Lepadatu, D. The Cambridge International Handbook of Lean Production, chapter 4, pp.92-123

– Signoretti, A. (2019). Explaining variation in the social performance of lean production: a comparative case study of the role played by workplace unions’ framing of the system and institutions. Industrial Relations Journal, 50(2): 126-149 .

– Goldthorpe, J. H. (2016). Sociology as a population science. Cambridge: Cambridge University Press.

– Marres, N. (2017). Digital Sociology: The reinvention of social research. Cambridge: Polity Press.

– Veltri, G.A. (2020). Digital Social Research. Cambridge: Polity.

Teaching Mode and Language: Classes will take place in English and online on Zoom. Lectures links will be announced before the class starts

Final Test: The final test will consist of an oral exam. More detailed information on the time and place for the test will be provided by the instructors upon course beginning.