OVERVIEW

The course is intended to refresh fundamental concepts in programming, data structures and algorithms, providing useful background knowledge for many courses of the Master Degree in Computer Science.

AIMS AND CONTENT

LEARNING OUTCOMES

Refreshing the fundamental concepts in programming, data structures and algorithms using the Python language and introducing students to the use of the numpy library.

AIMS AND LEARNING OUTCOMES

The student should acquire the skills to create simple applications using the Python language, the ability to empirically evaluate their performance and to choose the best data structures, among those available in the language, to carry out certain tasks. In particular, at the end of the course students will be able to

• use the online documentation on Python and some of its libraries

• analyze pieces of programs (written in Python) and understand how they work

• modify, run and test small programs

• starting from an informal specification of a problem, design and write (parts of) programs that solve the problem

TEACHING METHODS

Teaching consists of classroom lectures and some home assignments related to the topics covered so far in the course.

It is assumed that students have a laptop with anaconda3 installed. Assistance to install anaconda3 and to use Jupyter Notebook will be provided at the start of the course.

Lectures may be recorded on MS Teams (for the benefit of students abroad).

Home assignments can be done in group (of at most 3 students) and must be uploaded on aulaweb at specified deadlines.

SYLLABUS/CONTENT

• Language constructs: expressions, assignments, conditionals, iteration, functions, recursion, exceptions, list comprehension.

• Data structures: lists/sequences, dictionaries, sets

• Algorithmic techniques: divide-and-conquer, list processing, memoization, staging

• Numpy library: arrays,linear algebra operations

RECOMMENDED READING/BIBLIOGRAPHY

• https://docs.python.org/3/ online documentation

• https://greenteapress.com/wp/think-python-2e/ free book (pdf/html)

Further material (including video recordings) will be made available on aulaweb.

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

In agreement with the calendar approved by the Degree Program Board of Computer Science.

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam (of at most 3 hours) consists of programming exercises done individually in DIBRIS SW labs and submitted on aulaweb. After submission a possible solution will be made available, and students have a limited time (at most 18 hours) to confirm the submission. Only confirmed submissions are evaluated, and if they are rated less than 10/30, the student accumulates a penalty of 1 point on a future final mark.

The final mark is given by the weighted average (rounded up) of the scores obtained in the two parts

•     30% home assignments submitted during the course
•     70% final exam (lab test) after the end of the course

minus the accumulated penalty points. The exam is passed if the final mark is at least 18/30.

ASSESSMENT METHODS

The two parts assess the programming skills acquired by the students in different context:

• in home assignments submitted during the course the student is expected to make appropriate use the programming constructs presented so far and may work in team
• in the lab tests after the end of the course the student has to work individually in a limited time, and after submission has some extra time to perform self-evaluation of the submission against a proposed solution.

Exam schedule