Prototyping with Data and AI (2235.YR.015762.1)

General information

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

Teaching Staff:

Group	Teacher	Department	Language
Year 1	Jose A. Rodriguez Serrano	Operaciones, Innovación y Data Sciences	ENG

Ideally, you have had some previous exposure or strong interest in at least one of these areas: either computing (e.g programming languages, business intelligence Tools), OR data analysis (using quantitative software or data visualization software) OR creating digital content (web design, video editing and creation, hands-on digital design).

Additionally, you have a strong interest in creating digital products and like hands-on practice.

Note: The goal of this course is to develop data and AI prototypes by practising. If you are interested in acquiring a basic, general understanding of AI and Machine Learning, please consider the other available course "Introduction to Machine Learning".

Lectures (about 1/3)
Individual assignments (about 1/3)
Group project (about 1/3)

Many of the digital services we use every day are powered by data or AI, such as email apps, job search apps, social media, ecommerce & banking apps, or music services. And several courses in the different MSc0s already deal with how to extract value from data.

This course takes a step beyond and considers the perspective of the product: developing a product idea based on data and AI. Indeed, we consumers experience the benefits of data and AI as part of an interaction with well-designed products.

However, coming up with the right product idea is challenging. That's precisely the goal of prototyping: to develop a tangible demonstrator of the product that can be sent for user feedback. In the case of data and AI, prototyping implies building an early-stage interactive application, or artifact, that showcases the value of the technology, usually using real data or a real call to an AI service.

In addition, prototyping is emerging as a mindset in management, to take decisions and validate assumptions "by doing?, and even to de-risk strategies.

During this course, we will learn several aspects of prototyping, such as:

- Theoretical concepts and methods to generate and validate new ideas
- Examples how companies use data & AI prototypes that lead to real products
- Specific programming tools in Python that allow easily building interactive applications

We will also have the chance to build some data & AI prototypes to acquire hands-on knowledge.

- Understand the mindset of prototyping as an inexpensive tool for generating ideas in early stages of design, for discovery, for "thinking by doing?, and for de-risking strategies.
- Get introduced to methodologies such as "working backwards?.
- Get knowledge of tools to produce interactive applications including python and some no-code tools, and to connect with data services or AI models.
- Practice by building prototypes of products powered by real data and / or AI.
- Get inspiration from companies applying these practices in products they release

1. Introduction to Prototyping - Introduction to Module, Learning Goals, Organization - Understand ¿sketching¿ as an approach for approaching the initial design of a product: - Understand benefits of prototyping as an asset for strategic management: take decisions based on uncertainty and observation, or use it to de-risk strategies. - Learn the vocabulary of `tests¿ (proof of concept, minimum viable product, sketch, prototype), and learn what (really) makes an MVP.

2. From design thinking to "design doing" and design fictions - Understand the mindset of design thinking, thinking by doing, working backwards and design fiction. - See successful examples - Learn management practices around prototyping

3. Sketching with data and AI - Understand elements available in the market that allow demo¿ing data & AI technologies in assisted ways (Google¿s teachable machine, huggingface, tensorflow.js demos¿) - Understand how to generate ideas by sketching with these tools. - Get to know how companies approach prototyping with AI.

4. Prototyping tools with python Understand Basic Tools for prototyping and add interactivity using the python language.

5. Understanding capabilities of Large Language Models and Prompt Engineering Learn to interact with tools that offer development of Natural Language Processing applications. Learn to design tasks by adapting those models (¿prompt engineering¿).

6. Other prototyping concepts Optional activity, depending on the evolution and dynamics of the course, but may include: - Prototyping with physical devices - Prototyping with data visualization tools

In this course, the methodology includes theoretical lectures about prototyping concepts or specific tools, with a strong component of practice. Apart from the lectures and class activities, students will have practical assignments focusing on the capability to create product concepts. Also, students will develop a group project from the start of the course, with several milestones during the course, where they will be protagonists of their own case study and will practice the development of a prototype in an iterative way.

General:
- Buxton, Sketching User Experiences.
- McGrath, Seeing around corners.
- Bleecker et al, The Manual of Design Fiction.
- Murray, Interactive Data Visualization for the Web.

Technical:
- Grinberg, Flask Web Development.
- Schroeder & Ward, The book of Dash.
- Nokeri, Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps.
- Rossant, IPython Interactive Computing and Visualization Cookbook - Second Edition

Group	Teacher	Department
Year 1	Jose A. Rodriguez Serrano	Operaciones, Innovación y Data Sciences