lecturing: from September 12th
2019 to December 12th
Holidays: October 24th,
2019 (no lecture), December 23rd
2019 until January 6th
2020 (Christmas Holidays)
Change of schedule: October 31st,
2019 has a Friday schedule
Starting date for the course: September 12th
Description of the aims of the course. Description of the team
works. Information about the IS project timeline. Deliverables
of the IS project. Examples of past ISP projects
2. Problem Analysis: Problem Feature Analysis. Information/Data
Analysis. Viability Analysis. Economic Analysis. Environmental
and Sustainability Analysis.
3. Definition of the Intelligent System project issues:
Definition of main goals of the IS project. Definition of
sub-goals. Task Analysis.
4. Development of an Intelligent System Project:
Data/Information Extraction. Data Mining & Knowledge
Acquisition Process. Knowledge/Ontological Analysis. Planning
and selection of Intelligent/Statistical/Mathematical
Methods/Techniques. Construction of Models and implementation of
Techniques. Module Integration. Validation of Models/Techniques.
Comparison of Techniques. Proposed Solution.
5. Intelligent System Project Output: Executive Summary. Project
System Documentation: User's Manual, System Manual. Project
Schedule (Gantt's Chart). The Project Time Sheet.
6. Intelligent Methods and Models: Review of main Intelligent
7. Software tools: Review of main software tools available.
The “Racó de la
FIB” is the Virtual Campus for you. There, you will find
any announcement, change in the schedule, the project related
information, the results of the evaluation of the project and
final marks, etc. There you will also find a pointer to this
WEB page of the course where you could find some other
material (slides, internet references, etc.) in electronic
The Intelligent System project will
be developed by each teamwork of 3 or 4 people.
The milestones of the project will be:
PM1 – Definition of the Project Document
PM1 is due on: October 3rd,
PM2 – Midterm Document
PM2 is due on: November 14th,
PM3 – Final Document and Software Delivery
PM3 is due on: January 8th,
PM4 – Public defence of the Project
PM4 will be on January 9th,
presentation and oral exposition of the Project will be
done on January 9th,
2020 (30 min. approx. for each group) with the
of one Technical professional of
some real company
Analysing and interpreting tweets
related to weather: talking about the past or about the
future, making some sentiment/mood analysis
Detecting talks about topics of interest
related to some business in the Linkedin Network (WhoTalk)
A prediction system for bike and spot
availabilities (Bicing predictor)
A recommendation engine for movies.
Image Search Engine for same style
PCC - Parrot Communication with children
- An intelligent interaction system for children with
difficult emotion expressing skills, through a flying drone
An online dating system based on
Robust Euro Notes Classification
Meeting the right people
A Classification System for fictional
Answering Machine (Question Answering)
Finding Lost Pets
of the achievement of the objectives of the course will be made
by assessing the achievements of an Intelligent System project
throughout the course, which will be done working in teams of 3
or 4 students.
The final grade (FGrade) is a weighted average between
the teamwork assessment (TGrade) and the evaluation of the work
of each individual student (IGrade) according to the formula:
FGrade = tp * TGrade + ip * IGrade, where the team percentage
(tp) and the individual percentage (ip) ranges from 0.3 ≤ tp ≤
0.5 and 0.7 >= ip >= 0.5, will be determined at the
beginning of each course.
The individual grade for each student (IGrade) will be
obtained by observing and assessing the ongoing work and
participation of each student throughout the project, according
to the teacher.
The teamwork grade (TGrade) will be a weighted average
between four marks related to the definition of the project
document (PM1Gr), the midterm delivery of system analysis and
design (PM2Gr) the final document and software delivery (PM3Gr),
and the final public presentation of the project (PM4Gr). It
will be computed according to the formula:
(adapted from Stanford University Honor Code)
A. The Honor Code is an undertaking of the
students, individually and collectively:
that they will not give or
receive aid in examinations; that they will not give or
receive unpermitted aid in class work, in the preparation
of reports, or in any other work that is to be used by the
instructor as the basis of grading;
that they will do their share
and take an active part in seeing to it that others as
well as themselves uphold the spirit and letter of the
B. The faculty
on its part manifests its confidence in the honor of its
students by refraining from proctoring examinations and from
taking unusual and unreasonable precautions to prevent the
forms of dishonesty mentioned above. The faculty will also
avoid, as far as practicable, academic procedures that create
temptations to violate the Honor Code.
C. While the faculty alone has the right and
obligation to set academic requirements, the students and
faculty will work together to establish optimal conditions for
honorable academic work.
Examples of conduct which have been regarded as being in
violation of the Honor Code include:
• Copying from another’s examination paper
or allowing another to copy from one’s own paper
• Unpermitted collaboration
• Revising and resubmitting a quiz or exam
for regrading, without the instructor’s knowledge and consent
• Giving or receiving unpermitted aid on a
• Representing as one’s own work the work of
• Giving or receiving aid on an academic
assignment under circumstances in which a reasonable person
should have known that such aid was not permitted
In recent years, most student disciplinary cases have involved
Honor Code violations; of these, the most frequent arise when
a student submits another’s work as his or her own, or gives
or receives unpermitted aid. The standard penalty for a first
offense or multiple violations will be proposed by the
teachers in charge of the course, and approved by the Academic
Commission of the Master MAI.
Resources for student learning
Schalkoff, Robert J.
Intelligent Systems: Principles, Paradigms and
Pragmatics. Jones and Bartlett Publishers,
Hopgood, Adrian A. Intelligent
Systems for Engineers and Scientists. CRC
Press, 2011, ISBN:1439821208.
Negnevitsky, Michael. Artificial
Intelligence: A Guide to Intelligent Systems.
Addisson-Wesley, 2004, ISBN:0-3212-0466-2.
Russell, Stuart and Norvig, Peter. Artificial
Intelligence - A Modern Approach. Prentice Hall,
2010, ISBN: 0-13-207148-7.
IEEE Intelligent Systems JournaL
International Journal of Intelligent
Applied Intelligence Journal. The
International Journal of Artificial Intelligence, Neural
Networks, and Complex Problem-Solving Technologies.
ACM Transactions on Intelligent
Systems and Technology (ACM TIST)
Statistics Institute (Institut d'Estadística de Catalunya)