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PROGRAMMING COURSE: PYTHON

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PROGRAMMING COURSE: PYTHON

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Academic year 2023/2024

Course ID
SEM0183
Teacher
Alberto Turigliatto (Lecturer)
Year
1st year
Teaching period
First semester
Type
Other activities
Credits/Recognition
3
Course disciplinary sector (SSD)
INF/01 - informatics
Delivery
Formal authority
Language
English
Attendance
Optional
Type of examination
Written
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Sommario del corso

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Course objectives

The objective of the course is to provide a good mastery of the basics of programming and the ability to formulate problems, develop solutions and implement these solutions in Python in a clear, accurate and optimal way. Particular emphasis will be placed on the economic applications of the acquired concepts.

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Results of learning outcomes

At the end of the course, students will be able to:

  • Understand computational logic and create simple algorithms
  • Know the main Python commands and the use of Jupyter Notebook
  • Use Python commands to acquire and manage databases

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Course delivery

  • Lectures
  • Computer exercises to apply the concepts explained (the use of a personal laptop is recommended)

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Learning assessment methods

The assessment of learning will be carried out through

  1. a test consisting of 10 multiple answers about Python language basics (maximum score 20 points)
  2. drafting of a report on the analysis of a database chosen by the student, following the guidelines described during the course (maximum score 10 points). It is possible to carry out the report in groups of at most three students.

The final mark will be the sum of the marks obtained in the two phases.

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Program

  • How to install Python
  • Programming languages: interpreters and compilers
  • How to write a program
  • Variables, expressions, instructions
  • Conditional execution
  • Alternative execution
  • Functions
  • Iterations
  • Strings
  • Files
  • Lists
  • Dictionaries
  • Tuples
  • Fundamentals of NumPy: Arrays and vectorized computation
  • How to use Pandas
  • Data loading, storage and file formats
  • How to operate on data
  • Graphic representations
  • Data aggregation
  • Time series
  • Financial and economic applications

Suggested readings and bibliography



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Book
Title:  
Think Python
Year of publication:  
2012
Publisher:  
Green Tea Press, Needham
Author:  
ALLEN DOWNEY
Permalink:  
Required:  
No
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Refer to the official site (https://www.python.org) for further information (documentation, tutorials, guides) on Python language.



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