29737 - Laboratory of Information Technology T

Learning outcomes

Learning the main concepts and tools required to employ Computer Science for the solution of practical problems in Chemical Engineering. Knowledge and skill to design and implement systems and algorithms using high-level languages.

Course contents

Introductory Note

This course (LABORATORIO DI INFORMATICA T) will be tightly integrated with ANALISI NUMERICA T, in terms of topics and evaluation criteria.

Students are advised to check the web page of ANALISI NUMERICA T to get a better overall picture of the integrated course.

Requirements/Prior Knowledge

A prior knowledge and understanding of the basics of mathematical analysis and linear algebra is required to attend with profit this course.

A basic understanding of classical mechanics principle is useful, but not strictly necessary.

Fluent spoken and written Italian is a necessary pre-requisite: all lectures and tutorials, and all study material will be in Italian.

Course Contents

Computer Science Basics

• Algorithm concept, structured programming
• Introduction to Matlab/Octave, data structures, operators, basic functions

Information Processing Systems

• A brief history of digital electronic computers, internal structure of a computer
• A brief introduction to programming languages
• A brief introduction to Operative Systems

Number representation

• Binary representation of integer numbers, binary representation of floating-point numbers, computation examples, cancellation errors

Simple numeric problems:

• Discrete-time dynamic systems
• Solution of linear equation systems (with applications)
• Solution of non-linear systems of equations (with applications)
• Solution of least-square problems (with applications)
• Solution of Ordinary Differential Equations (with applications)

Advanced numeric problems:

• Parameter estimation problems
• Basic optimization problems

Readings/Bibliography

The course will mainly rely on slides, made available during as the lectures and lab sessions take place.

Additionally, all lectures will be recorded and published on-line.

Teaching methods

The course will be taught mainly using:

• Lab sessions
• Short frontal lectures (typically before a lab session)

Assessment methods

The developed knowledge and skills will be assess via a practical test in the lab. The test will contain exercise also related to the program of the integrated course Analisi Numerica T.

The student should be aware that the related course of ANALISI NUMERICA T requires a final written test.

Teaching tools

• Course slides
• Exercises and exam fac-similes
• Recorded lectures (screencasts)

Links to further information

http://ai.unibo.it/teaching/LABINFO-T-1617

Office hours

See the website of Michele Lombardi