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Artificial Intelligence II (18CBA11016)

General information






S semester

ECTS Credits:


Teaching Staff:

Group Teacher Department Language
Sec: A Marc Torrens Arnal Operaciones, Innovación y Data Sciences ENG

Group Teacher Department Language
Sec: B Marc Torrens Arnal Operaciones, Innovación y Data Sciences ENG


Artificial Intelligence (AI) is transforming our society in a new and unprecedented industrial revolution. AI is impacting organisations at their core, reshaping business models and enriching people's daily lives. This course provides an overview of AI technologies, and explains how they can be used in practice. Specific focus will be given to Machine Learning (ML) and Recommender Systems that are being successfully applied to disrupt many industries. This course is designed to acquire a deep understanding of the main AI techniques from a business point of view.

The course uses a mix of engaging lectures and hands-on activities on practical business cases. This course also involves using ML tools to prototype real cases. At the end of the course, students will be able to understand AI main technologies, identify business opportunities based on ML and Recommender Systems, and prototype real business cases.

Course Learning Objectives

At the end of the course, students should:
- Understand the current and future impact of AI in our society and businesses.
- Be able to identify AI-based opportunities within organizations. This implies to identify (big) data value and know how to apply AI to create new business models with innovative products and services.
- Understand the different available AI technologies and how to apply them in different contexts.
- Be acknowledgeable on available platforms and tools to successfully apply AI in companies.
- Know how to build AI prototypes based existing platforms such as BigML to validate ideas.
- Have the necessary skillset to lead and manage company transformations based on AI technologies.
- Be able to have an informed discussion about any general topic involving AI technologies including ethics, legislation, education and employment.



This introductory session gives the basic concepts of AI and guides you through its evolution to understand how it is applied to transform industries and businesses.
- What is Artificial Intelligence (AI)?
- The AI evolution and its future
- Artificial General Intelligence versus Applied AI
- The impact of AI in businesses
- The impact of AI in society
- Examples of AI systems used in our daily lives


Machine Learning (ML) is the most successfully applied AI technolgogy nowadays. ML is about analysing large data sets to discover knowledge and insights on organizations and customers. Those insights are encoded into models that are capable of predicting outcomes from data.
- Machine Learning Introduction
- Supervised and Unsupervised Learning Algorithms
- Practical Business Cases using ML


These sessions are devoted to implement prototypes with Machine Learning tools and specific data sets. It involves some pseudo-programming in order to use a ML tool. The goal is to implement simple systems to actually understand the power of ML.
- Prototype on Supervised Learning
- Prototype on Unsupervised Learning


Recommender Systems are boradly used in many industries. Companies such as Netflix, Amazon, Spotify and Facebook have built their core business around Recommendation and Personalization technologies.
- Why do we need Recommender Systems?
- What is a Recommender System?
- Collaborative-based Filtering
- Content-based Filtering
- Examples


AI includes a broad set of technologies. In this session, we will overview AI technologies and examples other than ML and Recommender Systems.
- Natural Language Processing
- Computer Vision
- Planning and Reasoning
- Robotics


AI is changing the world quickly due to its maturity, the availability of data (digitalization) and the current computing power (cloud computing). This quick industrial revolution indtroduces ethic and social topics that are important for businesses as well.
- Ethics of AI
- Labor challenges in an AI empowered society
- Education and other social impacts related to the massive use of AI
- Legislation and Regulation involved in AI


Assessment criteria

30% Prototype implementation (individual)
20% Class Participation
50% Term paper (group)
In this course we will learn how to use ML platforms (such as BigML) to prototype systems using ML algorithms. Students will individually build a prediction model based on a real case that will be given. Some very basic programming knowledge will be required but just to use the platform and deal with data files.

Grading class participation is necessarily subjective. However, I try to make it as "objective as possible?. Some of the criteria for evaluating effective class participation include:
- Is the participant prepared? Do comments show evidence of analysis of the case? Do comments add to our understanding of the situation? Does the participant go beyond simple repetition of case facts without analysis and conclusions? Do comments show an understanding of theories, concepts, and analytical devices presented in class lectures or reading materials?
- Is the participant a good listener? Are the points made relevant to the discussion? Are they linked to the comments of others? Is the participant willing to interact with other class members?
- Is the participant an effective communicator? Are concepts presented in a concise and convincing way?

Subject: Analysis of company proposal built around Artificial Intelligence. Students will work in groups of 4-5 people, preparing a paper and presenting conclusions in class.

Objective : Working on this assignment will familiarse you on how to apply Artificial Intelligence in a business.

Groups should turn in a presentation with a maximum of 20 slides to be used in your class presentation.
This slide deck should be turned in 2 days before the date assigned for your class presentation. Please send your slide deck through the intranet and/or

Presentation: Your presentation will last about 15 minutes and will be followed by a 5 minute question and answer period. You may use any teaching aid you like (transparencies, video, etc).

Date of Presentation : Last session scheduled.

Timetable and sections

Group Teacher Department
Sec: A Marc Torrens Arnal Operaciones, Innovación y Data Sciences

Timetable Sec: A

From 2019/2/18 to 2019/3/18:
From Monday to Tuesday from 9:00 to 12:00. (Except: 2019/2/19, 2019/2/26 and 2019/3/12)

From 2019/3/25 to 2019/4/8:
Each Monday from 9:00 to 12:00. (Except: 2019/3/25)
Each Monday from 14:00 to 17:00. (Except: 2019/4/1 and 2019/4/8)

Group Teacher Department
Sec: B Marc Torrens Arnal Operaciones, Innovación y Data Sciences

Timetable Sec: B

From 2019/2/11 to 2019/3/4:
Each Monday from 14:00 to 17:00.

From 2019/3/11 to 2019/4/8:
Each Monday from 9:00 to 12:00. (Except: 2019/3/25, 2019/4/1 and 2019/4/8)
Each Monday from 14:00 to 17:00. (Except: 2019/3/11 and 2019/3/18)