At the end of the course the student will be able to focus the connection between mathematics and automatic computation.
The student will be taught the python programming language, along with the fundamental idea of algorithms and data structure implementations.
For the exercise, the teacher will try to select examples with applications to the other courses of the first semester (Analysis and Linear Algebra), such as the application of the Newton's method to compute the square root, or the computation of the determinant of a matrix.
Course Prerequisites
Basic understanding of how computers work.
Since it is a basic course of the first year and first semester, there is not any requirement for other university courses.
Teaching Methods
Lessons and laboratories with the computer.
For the standard lectures, all the teaching material will be made available to the students using KIRO, our official moodle.
Per the lab session, the solutions of the proposed exercises will be available after two weeks, in order to leave to the students the time to elaborate a personal solution. At the end of the course, all the solutions of the exercise session will be available to the students.
Assessment Methods
Implementation of programs with the computer (live coding, on linux machines of the computer lab at the university).
The maximum final grade will be 18. During the exam the students will have to solve in average 10 coding exercises, e for each exercise the students will know the maximum points available. The sum of all the points is 31.
Duration: 2.5 hours (150 minutes)
Texts
Lecture notes available on the web page of the course on KIRO, our official moodle.
Recommended additional textbook: - Introduction to Computation and Programming Using Python - With Application to Understanding Data, by John V. Guttag. MIT Press (second edition)
Contents
Introduction to automated computing, representation of the numbers in floating points precisions, error propagations in floating point operations. Presentation of the development environment for Python: - General purpose commands - Variables, list, and built-ins functions - Expressions and logical operators - Control flow: if-then-else - Reading and writing of CSV files - Introduction to functional programming - Numerical series and graphical representations - Imperative programming vs. functional programming - Solution of basic optimization problems (knapsack, shortest path, traveling salesman problem)
Course Language
Italian
More information
The course will have (optional) tutoring activities by master or phd students.
