nllano / 2020-2021

The GitHub repository containing all the material related to the Computational Thinking and Programming course of the Digital Humanities and Digital Knowledge degree at the University of Bologna (a.a. 2020/2021).

Computational Thinking and Programming

This space contains all the material related to the Computational Thinking and Programming course of the Digital Humanities and Digital Knowledge degree at the University of Bologna.

Academic year 2020/2021

Table of content

• Computational Thinking and Programming
  • Academic year 2020/2021
    • Table of content
    • Book and notes
    • Material
    • Schedule
    • Exam sessions
• Links

Book and notes

The official book of the course, Computational Thinking and Programming book, is available online in PDF format. Google Docs links are provided for each chapter, to enable students to comment and suggest improvements. The suggested accompanying book for Python coding, How To Code in Python by Lisa Tagliaferri, is also freely available online in PDF and EPUB formats.

All the lecture notes and additional material of the laboratory are available at https://comp-think.github.io/2020-2021/laboratory/.

Material

Keys:

• the = theoretical lecture
• lab = laboratory session

1. [14/10/20, the] Introduction to the course
   • slides: HTML

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2. [14/10/20, the] Introduction to Computational Thinking
   • book chapter: PDF, Google Docs
   • slides: HTML
   • exercises: 1, 2, 3
   • solutions: 1, 2, 3

   ---

3. [16/10/20, the] Algorithms
   • book chapter: PDF, Google Docs
   • slides: HTML
   • exercises: 1, 2, 3
   • solutions 1, 2, 3

   ---

4. [19/10/20, the] Computability
   • book chapter: PDF, Google Docs
   • slides: HTML
   • exercises: 1, 2, 3
   • solutions 1, 2, 3
   • additional material: Asymptotic notation, Introduction to Asymptotic Analysis, Analysis of Algorithms

   ---

5. [21/10/20, the] Programming languages
   • book chapter: PDF, Google Docs
   • slides: HTML
   • from How To Code in Python:
     • Chapter "Understanding Data Types": introductory paragraphs and sections "Background", "Numbers", "Floating-Point Numbers", "Booleans", "Strings"
     • Chapter "How To Use Variables": introductory paragraphs and sections "Understadning Variables", "Naming Variables: Rules and Style", "Reassigning Variables", "Multiple Assignment"
     • Chapter "Understanding Boolean Logic": all content
     • Chapter "How To Write Conditional Statements": all content
     • Chapter "How To Define Functions": introductory paragraphs and sections "Defining a Function", "Working with Parameters", "Returning a Value"
   • Python: first_algorithm_empty.py, first_algorithm_no_assignments.py, first_algorithm.py
   • exercises: 1, 2, 3
   • solutions 1, 2, 3

   ---

6. [23/10/20, lab] 1st Lesson
   • material: HTML

   ---

7. [26/10/20, the] Organising information: ordered structures
   • book chapter: PDF, Google Docs
   • slides: HTML
   • from How To Code in Python:
     • Chapter "How To Write Comments": all content
     • Chapter "How To Import Modules": all content
     • Chapter "Understanding Data Types": section "Lists"
     • Chapter "Understanding Lists": introductory paragraphs and section "Indexing Lists"
     • Chapter "How To Use List Methods": introductory paragraphs and sections "list.append()", "list.extend()", "list.remove()"
   • Python: define_functions.py, list_instructions.py, stack_instructions.py, queue_instructions.py
   • exercises: 1, 2, 3
   • solutions 1, 2, 3

   ---

8. [28/10/20, lab] 2nd Lesson
   • material: HTML

   ---

9. [30/10/20, the] Brute-force algorithms
   • book chapter: PDF, Google Docs
   • slides: HTML
   • from How To Code in Python:
     • Chapter "How To Construct While Loops": all content
     • Chapter "How To Construct For Loops": all content
     • Chapter "Understanding Tuples": all content
     • Chapter "Understanding Lists": section "Constructing a List with List Items"
     • Chapter "How To Use List Methods": section "list.insert()"
   • Python: stack_from_list.py, run_forever.py, linear_search.py, insertion_sort.py
   • exercises: 1, 2, 3, 4, 5
   • solutions 1, 2, 3, 4, 5

   ---

10. [09/11/20, the] Organising information: unordered structures
    • book chapter: PDF, Google Docs
    • slides: HTML
    • from How To Code in Python:
      • Chapter "Understanding Data Types": section "Dictionaries"
      • Chapter "Understanding Dictionaries": all content
      • Chapter "How To Construct Classes and Define Objects": all content
    • Python: set_instructions.py, dictionary_instructions.py
    • exercises: 1, 2, 3
    • solutions: 1, 2, 3

    ---

11. [11/11/20, lab] 3rd Lesson

• material: HTML

  ---

11. [13/11/20, the] Recursion
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: run_forever_recursive.py, multiplication.py
    • exercises: 1, 2
    • solutions: 1, 2

    ---

12. [16/11/19, lab] 4th Lesson

• material: HTML

  ---

13. [20/11/20, the] Divide and conquer algorithms
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: immutable_values.py, mutable_values.py, immutable_and_mutable_variables.py, merge.py, merge_sort.py
    • exercises: 1, 2, 3
    • solutions: 1, 2, 3

    ---

14. [23/11/20, the] Dynamic programming algorithms
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: fib_dc.py, fib_dp.py
    • exercises: 1, 2
    • solutions: 1, 2

    ---

15. [25/11/20, lab] 5th Lesson

• material: HTML

  ---

16. [27/11/20, the] Organising information: trees
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: tree_instructions.py
    • exercises: 1, 2
    • solutions: 1, 2

    ---

17. [30/11/20, lab] 6th Lesson

• material: HTML

  ---

18. [02/12/20, the] Backtracking algorithms
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: peg_solitaire.py
    • exercises: 1, 2
    • solutions: 1, 2

    ---

19. [04/12/20, lab] 7th Lesson

• material: HTML

  ---

20. [09/12/20, the] Organising information: graphs
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: graph_instructions.py, multigraph_instructions.py, graph_attribute_instructions.py
    • exercises: 1, 2
    • solutions: 1, 2

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21. [11/11/20, lab] 8th Lesson
    • material: HTML

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22. [14/12/20, the] Project: specification
    • slides: HTML
    • material: GitHub

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23. [16/12/20, the] Greedy algorithms
    • book chapter: PDF, Google Docs
    • slides: HTML
    • Python: line_wrap.py
    • exercises: 1, 2
    • solutions: 1, 2

    ---

24. [16/12/20, the] Ask a thesis
    • slides: HTML

Schedule

Date	Time	Title
14/10/20	9:30-11:30	Introduction to Computational Thinking
16/10/20	12:30-14:30	Algorithms
19/10/20	9:30-11:30	Computability
21/10/20	9:30-11:30	Programming Languages
23/10/20	12:30-14:30	Laboratory
26/10/20	9:30-11:30	Organising information: ordered structures
28/10/20	9:30-11:30	Laboratory
30/10/20	12:30-14:30	Brute-force algorithms
09/11/20	9:30-11:30	Organising information: unordered structures
11/11/20	9:30-11:30	Laboratory
13/11/20	12:30-14:30	Recursion
16/11/20	9:30-11:30	Laboratory
20/11/20	12:30-14:30	Divide and conquer algorithms
23/11/20	9:30-11:30	Dynamic programming algorithms
25/11/20	9:30-11:30	Laboratory
27/11/20	12:30-14:30	Organising information: trees
30/11/20	9:30-11:30	Laboratory
02/12/20	9:30-11:30	Backtracking algorithms
04/12/20	12:30-14:30	Laboratory
09/12/20	9:30-11:30	Organising information: graphs
11/12/20	12:30-14:30	Laboratory
14/12/20	9:30-11:30	Project: specification
16/12/20	9:30-11:30	Greedy algorithms

Exam sessions

• 29 January 2021
• 15 March 2021
• 17 May 2021
• 14 June 2021
• 7 July 2021
• 20 September 2021

Links

• First partial examination: text and solutions
• Second partial examination: text and solutions
• Written examinations: text and solutions