Vai al contenuto principale
Coronavirus: aggiornamenti per la comunità universitaria / Coronavirus: updates for UniTo Community
Oggetto:
Oggetto:

Programming for data science

Oggetto:

Programming for data science

Oggetto:

Academic year 2017/2018

Course ID
MAT0036
Teacher
Dott. Marco Beccuti
Year
1st year
Teaching period
First semester
Type
D.M. 270 TAF F - Other activities
Credits/Recognition
3
Course disciplinary sector (SSD)
INF/01 - informatica
Delivery
Formal authority
Language
English
Attendance
Mandatory
Type of examination
Mixed
Prerequisites
ELEMENTS OF STATISTICS
Basic knowledge in Calculus as provided by the first year Mathematics course.
ELEMENTS OF COMPUTER SCIENCE
No specific computer science knowledge is required.
Oggetto:

Sommario del corso

Oggetto:

Course objectives

Aim of the course is to introduce methods, techniques and related computer science instruments for the analysis of experimental data.

It  provides the basic knowledge to use computer science applications as  Spreadsheet  (e.g. Excel, Calc,...) and  programming languages  for statistical computing and graphics (e.g. R programming language)

Oggetto:

Results of learning outcomes

KNOWLEDGE AND UNDERSTANDING – Completing the course students will be able to:

1)      use suitable descriptive and inferential statistics techniques to describe and understand the phenomena being studied;

2)      manage suitable computer science instruments such as worksheet or dedicated software programs for statistical data analysis.

APPLYING KNOWLEDGE AND UNDERSTANDING – Students will perform the statistical analyses required by the problem under study by selecting the most computationally and graphically suitable computer science support.

MAKING JUDGEMENTS – Students will decide which statistical techniques to use according to the available data sets to describe and understand the phenomena under consideration.

COMMUNICATION – The student will be able to justify the choices for the analysis to be performed and to give a synthetic description of the techniques employed and of the results obtained.

Oggetto:

Course delivery

ELEMENTS OF COMPUTER SCIENCE

The course consists of  10 hours of lectures, and 14 hours of laboratories . Laboratories  include exclusively practical activities.

The slides presented during lectures are available to students as online materials.

Attendance to lessons is not mandatory, but highly recommended due to the necessity of learning and employing specific computer science instruments.

Oggetto:

Learning assessment methods

The exam consists of a written test and requires a practice exercise on R  programming languages

WRITTEN EXAMINATION:

-  ten multiple choice questions on course topics (4 options, with the possibility of 0-4 correct options);

- a practice exercise on  R programming languages

The maximum possible score is 30 cum laude.

Oggetto:

Program

ELEMENTS OF COMPUTER SCIENCE

  • Introduction to R programming language;
  • Basic R functionalities:
    • Data structures: vector, matrix, array, list, data.frame \ldots;
    • Apply operators;
    • Input/output operator;
    • Package and library.
  • Programming with R:
    • Function;
    • Flow control: if,for, while, break ... statements;
    • Debugging in R.
  • Probability distributions:
    • Densities;			
    • Cumulatives,
    • Quantiles;		
    • Randon numbers.
  • Statistical graphics:
    • Graphical devices;
    • High level plot;
    • Low level plots.
  • Statistical functions

Suggested readings and bibliography

Oggetto:

- P. Dalgaard, Introductory Statistics with R, Springer 2008

- The R Manuals: An Introduction to R (http://cran.r-project.org/doc/manuals/r-releas /Rintro.pdf)

The teaching material used for lessons and a series of practical exercises are available on the web site of the course.

 



Oggetto:

Class schedule

Oggetto:
Last update: 29/06/2017 09:58
Non cliccare qui!