INTRODUCTION TO CODING AND DATA MANAGEMENT-1
|Academic year||2020/2021 Syllabus of previous years|
|Official course title||INTRODUCTION TO CODING AND DATA MANAGEMENT-1|
|Course code||ET7006 (AF:332689 AR:178839)|
|Modality||For teaching methods (in presence/online) please check the timetable|
|ECTS credits||6 out of 12 of INTRODUCTION TO CODING AND DATA MANAGEMENT|
|Degree level||Bachelor's Degree Programme|
|Educational sector code||ING-INF/05|
|Moodle||Go to Moodle page|
Students will learn some basic techniques for problem solving and how to use a programming language to provide a sound and formal description of a designed problem solution.
Programming is intended as a way to model real-world problems and to design algorithmic solutions to solve them.
The students will achieve the following objectives:
- algorithms and data structures
- Python programming language
- learn basic problem solving techniques.
- understand and interpret computer programs written in the Python programming language.
- generate basic data visualizations for preliminary analysis.
- Computational Thinking
- Information binary representation
- Introduction to the Python programming language
2. Python Data Types
- Variables, values and types
- Integer, Float, String, Boolean data types and their operators
3. Simple programs
- From pseudo-code to code
4. Functions and Conditional Statements
- Function definition
- Variable's scope
- Conditional Statements
5. Iterative Computation
- Formalization of iterative solutions
- The while loop
- The for loop
6. Iterative Computation II
- Nested loops
7. Python Lists
- Creating and manipulating lists
- Iterating through lists
8. Introduction to matplotlib
- Plotting functions with matplotlib
- Customizing appearance
- Using matplotlib to validate data analysis tasks
9. Python Lists II
- Time-series analysis through list processing
10. Python Lists III
- List comprehensions
- List sorting
- Mutable and Immutable types
- Anonymous functions
11. Python Strings
- String slicing, concatenation and traversal
- String manipulation methods
12. Python Strings II
- Text processing, string manipulation and sub-string search
13. Python Dictionaries
- Dictionaries and mapping, keys and values
- Dictionary creation and access
14. Python Dictionaries II
- Iterating through dictionaries
- Efficiency of presence checking
15. Problem Solving
- Binary search
- Think Python. How to Think Like a Computer Scientist. Green Tea Press. Allen Downey. Second Edition.
Other suggested readings:
- Learning Python. O'Reilly. Mark Lutz.
Additional resources may be provided during the course.
The written exam assess the capability of the student to apply problem solving techniques to simple problems. The exam consists in a set of programming exercises, where the student is asked to write a small program to solve a given simple problem.