Big Data & Analytics (2235.YR.000697.1)

General information

Type:	OPT	Curs:	1	Period:	S semester
ECTS Credits:	3 ECTS

Teaching Staff:

Group	Teacher	Department	Language
Year 1	Manuel Guerris Larruy	Operaciones, Innovación y Data Sciences	ENG

In 2011, The Wall Street Journal published one article of Marc Andreessen that became famous, "Why Software is Eating the World? . If this was already true in 2011, a quick look at the graphic below shows that today, almost ten years later, software has already eaten the world. Companies that heavily leverage on AI, Big Data, Robotics, IoT and Cloud Computing dominate markets and, in many ways, shape our lives. Perhaps the scariest part is the speed at which all this happened.

This course explores this disruption and attempts to provide an intro to two of its most important triggers: A.I. & Machine Learning and Cloud.

As an intro, first, we want to understand the nature of the disruption, its triggers, the mechanisms that drive it and its limits together with concrete examples of how AI and particularly machine learning is being applied to organizations and the organizational changes that bring to them.

However, the nucleus of the course is devoted to Artificial Intelligence and Machine Learning. We will have an overview of both and then we'll go deep into some of the most classical algorithms such as clustering, decision trees, random forests, boosting trees and the basics of deep learning.

Finally, we will go in deep with the management implications of cloud computing, with a focus on Amazon Web Services (AWS).

The course is conceptual, so no coding is required, although you could use your coding skills in a group project if you want to.

Big Data & Analytics aims to approach you to technical world and the management implications of these new technologies while approaching A.I. & Machine Learning.
The course is structured around three goals,
1. Understand the AI & Cloud disruption.
a) Understand the key factors that drive it, along with its role and mechanisms of disruption.
b) Assess the impact of the disruption in different industries and areas along with their limits.
c) Visualize its potential and prospective future evolution.
b.
2. Become familiar with A.I. & Cloud.
a) Be familiar with the technologies and tools around A.I. & Cloud and be able to situate them.
b) Know more in depth the basics of the algorithms that power the most common algorithms of clustering, regression and classification in tabular data.
c) Have an overlook at the libraries, technologies and algorithms more common in Deep Learning.

3. Understand Cloud Platforms and its impact.
a) Have a deep understanding of the implications of Cloud Platforms for business.
b) Become familiar with the elements of Cloud Platforms that transformed management and competition.
c) Have an overview of how A.I. and Machine Learning is implemented in Cloud Platforms.

1. Topic 1 - The AI Disruption In this session we will focus on the forces that triggered the disruption: Big Data, AI, Cloud, IoT and the Web. We will examine their impact, why they were and are able to sustain disruption and the mechanics inside this disruption. These are the fundamental mechanisms that we must know, along with applicability, limitations and potential evolution. They are shaping and modeling the digital natives that are changing interactions, competition and how organizations are managed.

2. Topic 2 ¿ Competing with AI & Cloud The impact, methods and approaches are certainly very different depending on the industry and the functional area. For example, if we take a look at logistics, we will find that software models are embodied in robots that run warehouses, while on social media platforms these models are focus on targeting and personalization. We must deepen our understanding because the realities of disruption are not uniform, neither are their affordabilities nor its impact. This topic reviews and compares salient characteristics of how AI & Cloud are being used in a variety of industries and sectors and how they completely transformed them.

3. Topic 3 ¿ Intro to A.I. This topic provides an historical introduction of A.I. and Machine Learning while describing the main topics of the field and their evolution and finally A.I. today. It starts with the beginnings of A.I. in 1956 and the initial disciplines. Then provides and brief overlook on the actual disciplines of A.I. & M.L. From there, we go through the history of A.I. explained with its winters, the periods where A.I. had lost the attention of the world, periods that correspond to the A.I. waves in the 60¿s, 70¿s, 80¿s, 90¿s, and from 2010 onwards. Finally, we have a glimpse of A.I. today with some of its most vibrant examples.

4. Topic 4 ¿ Intro to Machine Learning In this topic we try to make sense and provide clarity to the world of Machine Learning, with its tools, algorithms and processes. First, we look at the basic building blocks: the languages, the libraries, the tools and the cloud & cloud platforms. Then we go through a description of the most important Machine Learning Algorithms, first according to learning style and after by family. Finally, we look at the process of analyzing data and building machine learning models and describe data cleaning, wrangling, feature engineering, modeling and validation.

5. Topic 5 ¿ Clustering Clustering is the most important technique in unsupervised learning, widely used for segmentation. In this topic we have a review of the most common algorithms for clustering together with an example application.

6. Topic 6 ¿ Data Trees, Random Forests & Boosted Gradient Trees The data tree family, particularly Random Forests and Boosted Gradient Trees, is the most commonly used for classification and regression in tabular data. Almost every regression and classification model running nowadays is either a Random Forest or a Boosted Gradient Tree model. In this topic will deep into the theory behind it and provide an example of its use.

7. Topic 7 ¿ Deep Learning and Recommender Systems Nowadays Deep Learning is the form of Machine Learning used in the algorithms dealing not only with image and voice but also with tabular data. In this topic we will have an overview of the basics of Deep Learning. Also, Recommender Systems are the most widely used data products around. Used both for recommendation and personalization they are responsible of a great deal of what happened in e-commerce.

8. Topic 8 ¿ The secret sauce: Cloud Platforms Behind the A.I. disruption we find the economy. Zero marginal cost, investments transformed into variable costs, virtually infinite scalability, instant deployment and compliance, to name just a few of the elements that underpin the A.I. revolution, are consequence of the use of Cloud Platforms. In addition to this, Cloud Platforms are rapidly evolving, creating new affordabilities that will further transform our organizations and our society. However, this comes at a price, the growing power of a few companies that are the new natural monopolies and the confrontation of two systems with their own tech giants.

The methodological objective of this course is to provide the elements for the deep assimilation of frameworks and knowledge that can be used to analyze and act. The course highly leverages on group discussion to collectively explore course topics before providing structure to them. The assimilation not only of the contents but also of the frameworks is reinforced by reflecting on each topic through a series of key questions that touch on its most important areas.
Your attitude will be the key factor that will determine not only the success of the course, but also your success in terms of the quality and quantity of your learning. This course aims to go beyond "learning things? to become transformative for you giving you the opportunity to repeatedly engage with the class and learn to participate in discussions presenting your arguments in a convincing and civilize manner beyond imposing yourself or forcing your ideas, values or beliefs on others.
We need two things from you to make this possible and for the course to be successful. First of all, we need you to get involved in the course. This is not a course where you can passively attend, on the contrary, we need that you take charge of your education and make active effort with both the materials and the class. Secondly, we need that you actively participate in class discussions with the idea in mind of contributing to a common discovery and an open attitude to change your ideas, beliefs and points of view.
All classes are co-created. The success of a class depends as much of you and your attitude as of the professor. However, this is even more important in this course because participation is a key element. Participation sounds many times too generic and is being reduce to a few class interventions. This is not what we mean, but your full involvement with the course.
1. Come prepared, having read or seen the materials with a learning attitude. Do your research and do it right.
2. Analyze the underlying arguments, go beyond the cheap and easy explanations. Sometimes organizations choose paths that seem incomprehensible, resist the temptation to label them "stupid?, they did it for a reason. Try to find and understand it.
3. Weight confronted and conflicting points of view. Don't be a "one-side person?. Be able to defend both points of view in a conflict without giving up your own values.
4. Listen and listen carefully to the opinions of others and try to build on them, making valuable contributions.
5. Adapt and integrate the opinions of others. New ideas and proposals come mainly from recombination, learn to hybridize intelligently. Be open to change your beliefs and views in the light of new arguments or evidence.
6. Be civil and respectful, it is not about outsmarting others and being confrontational. Do not interrupt or participate in direct confrontations. It's about confronting ideas not people.
7. Professors are different. They need to moderate and avoid the blocking or monopolization of the debate. They need to ignite it and hence you will face "cold calls?. They also need to conduct the debate to the learnings of the topic and avoid confrontations or monopolization either of a topic or of a person. They will interrupt you if necessary, this doesn't mean that you can do the same.
This course is not about learning facts or acquiring new skills but integrating frameworks and using them in practice in debates and discussions. Therefore, it requires a different approach in the learning process. It is not based on memorizing new information or the deliberate practice of a new skill, it's a process of reflection and integration of routines of reasoning and mental maps.
Three practices are necessary for this integration to be effective.
a. Reflection. You need to reflect on the learnings building your own framework and challenging it through "thought experiments?, repeatedly challenging and confronting it.

b. Visual representations such as diagrams, mind-maps, even bullet points will help you to surface and understand the connections and cause-effect relations in the framework.

c. Practicing it by using it in discussions and distilling it from discussions will not only help you to integrate it but prepare you for life.
Humans are social beings; professional and personal advancement is also a social process that is conducted through interchange. Discussions and debates play a crucial role in this process. This course will help you to excel at it and could greatly contribute to your personal and professional advancement.

What we expect from you
- Prepare and prepare thoughtfully.
- Be on time with the right attitude. Don't come to attend, but to participate and get involved (bring you name tag, professors want to be able to call you by your name, give them this opportunity!).
- Participate, participate and participate!!! This class is not a video lecture.
Electronic device policy
- NO LAPTOPS. Research shows that humans cannot do two conscious things at the same time. They can only quickly switch between them and this comes at a cost in terms of attention and attitude. Our brain gets annoyed by it resulting in a lower quality experience. It is not about being there but being in the present moment.
- Tablets. Taking notes helps, particularly if you learn to draw mind-maps of the argumentation. Always use a pencil of an electronic pen, it offers you many more opportunities of depicting the arguments than bullet points that can only be hierarchical and not networked. Social processes have multiple and many times circular interconnections and negative or positive loops.
- Smartphones must be off or in silent mode.
Our sessions are a process divided into six different phases to maximize learning.

(1) Intro (individual). The topic is introduced either with a short video or a narrative, presenting not only the topic but the materials, highlighting why this topic is relevant in terms of competition and organizational or societal disruption.
(2) Research (individual). Individually you should set aside two to three hours per session to read the materials, view the videos and reflect on the initial discussion question that we will use as a trigger for exploration.

(3) Discussion (in class). We will discuss in class the question and the topic in class. Here we expect your participation with significant contributions. Our success depends on the depth of the collective exploration of the topic.

(4) Lecture (recorded). After we will have an online lecture that will structure and frame the different aspects that emerged in the discussion. Here we will continue to provide the tools to understand, analyze and succeed in the A.I. era.
Slides and the recorded lecture will be provided only after the discussion class to preserve the "wow? effect and allow the exploration of the topic.

(5) Key learnings (recorded). The lecture will summarize the key learnings of the subject, thus providing one more element to enable assimilation and their incorporation as tools in your arsenal.

(6) Assimilation (individual). Assimilation will be further enhanced by providing post-topic questions that will allow you to reflect into the key points and give full meaning to materials, discussions and lectures.

Each topic is covered with two sessions, one in class and another one online, complemented with personal work before and after to explore and reflect on the topic covered in the sessions.

The lectures, videos and additional material will be found in the Moodle of the course. However, you might be interested in delving into some of the areas, so you can find here some additional bibliography here, mostly books.
I encourage you to read at least a few, this disruption is not only one of the most exciting topics in business and I.S. but also of crucial importance for your career.
If there is a single idea that could be the most important in this course, it is without a doubt to realize that organizations are translating their organizational routines into model in the cloud. This changes the balance between exploration and exploitation in these organizations giving rise to new structures, which are managed and compete differently.
You can find a more extensive description of this here, you may be interested in taking a moment and getting over it.
https://www.forbes.com/sites/esade/2019/01/10/from-competing-on-analytics-to-companies-as-code/

Group	Teacher	Department
Year 1	Manuel Guerris Larruy	Operaciones, Innovación y Data Sciences