Artificial Intelligence and Machine Learning (B11030)

General information

Type:	OP	Curs:	5	Period:	S semester
ECTS Credits:	4 ECTS

Teaching Staff:

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

None

Basic computer science knowledge.

Workload distribution:
Lectures: 15 hours
Participatory sessions: 12 hours
Independent study: 30 hours

Artificial Intelligence (AI) is transforming our society in a new and unprecedented industrial revolution. AI is impacting organizations 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.

The aim of this course is for students to learn how to:
- 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.

This course is structured in 5 main topics. Most of the topics includes a lecture and a discussion on a practical business case or an AI-based prototyping exercise.

1. TOPIC 1 (SESSIONS 1-2). AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE 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

2. TOPIC 2 (SESSIONS 3-4). MACHINE LEARNING Machine Learning (ML) is the most successfully applied AI technology nowadays. ML is about analyzing 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

3. TOPIC 3 (SESSIONS 5-6). MACHINE LEARNING IN PRACTICE 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

4. TOPIC 4 (SESSIONS 7-8). RECOMMENDER SYSTEMS AND PERSONALIZATION Recommender Systems are broadly 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

Lectures: The faculty will present theoretical explications in conjunction with exercises and cases studies.

Participatory sessions: During these sessions the students will undertake a range of activities such as the completion of exercises and case studies, learning how to use the Access database management system, team presentations of studies undertaken and the analysis and diagnosis of a business scenario. From time to time students will also be tested on the knowledge they have acquired through their independent study.

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