AI, Science and the Cutting Edge (2235.YR.015876.1)

General information

Type:	OPT	Curs:	3,4	Period:	S semester
ECTS Credits:	2 ECTS

Teaching Staff:

Group	Teacher	Department	Language
Year 3	Luis Garcia Pareras	Esade	ENG

Group	Teacher	Department	Language
Year 4	Luis Garcia Pareras	Esade	ENG

There are no prerequisites for this course.

No previous knowledge is required for this course.

In this course titled "AI, Science, and the Leading Edge", we delve into the heart of an extraordinary era - where cutting-edge, science-driven companies are shaping the frontier of human progress. Our journey takes us to the intersection of Artificial Intelligence (AI) and various scientific disciplines, examining how AI is driving revolutionary scientific discoveries. This course is designed to explore the unique challenges and opportunities presented by the symbiosis of AI and science. We tackle key topics such as how AI is used to solve the 'big questions' in science, the application of AI in synthetic biology, and the art of algorithmic thinking for scientific exploration. We also examine the use of AI in predictive modeling, which plays a critical role in strategic decision making.

This course is a unique opportunity as well to explore how to predict the future using AI - a tool that not only enhances our predictive capabilities but also opens doors to understanding future trends and market movements. Through these lessons, students will gain an invaluable toolkit for navigating and pioneering within the evolving landscape of AI and science-driven businesses.

By the end of the course students will be expected to:

- Understand the Intersection of AI and Science: Gain a clear understanding of the pivotal role AI is playing in driving scientific discoveries and progress. Recognize how this relationship is shaping the industry and the wider society.
- Appreciate the Landscape of Science-Driven Companies: Acquire comprehensive knowledge of the ecosystem of science-driven or DeepTech companies. Understand their unique characteristics, challenges, and the dynamic trends shaping this sector.
- Grasp Algorithmic Thinking and its Application: Develop a solid foundation in algorithmic thinking and learn how it is applied in scientific problem-solving and AI.
- Understand AI in the context of specific fields: Understand the specific applications and implications of AI in fields like synthetic biology. Recognize the transformative potential of AI across different scientific disciplines.
- Predict Future Trends using AI: Learn to use AI as a predictive tool to anticipate future trends in the AI and science-driven landscape. Understand how to apply these predictions in strategic decision-making and innovation.
- Recognize the Science of AI: Gain an in-depth understanding of the principles underlying AI and its development trajectory. Explore the current challenges and future possibilities in AI advancement.
- Apply Knowledge to Real-World Scenarios: Translate theoretical knowledge into practice by applying learned concepts to real-world case studies and simulations. Develop a practical understanding of how to navigate the field of AI and science-driven companies.

1. Lesson 1 - Artificial Intelligence in Science This lesson will delve into the transformative role that AI is playing in accelerating scientific discoveries. We will explore examples of its application across various scientific fields and analyze its broader implications on society and business.

2. Lesson 2 - AI in Synthetic Biology Focusing on a specific field, this lesson will examine the intersection of AI and synthetic biology. We will look at how AI is catalyzing advancements in this field, explore case studies, and discuss the potential future trajectories.

3. Lesson 3 - Algorithmic Thinking and Scientific Approach This lesson will provide students with an understanding of algorithmic thinking and its application in AI and scientific problem-solving. We will delve into the principles of algorithmic thought and explore its role in tackling complex business and scientific challenges.

4. Lesson 4 - Using Science to Predict The fourth lesson will focus on how scientific knowledge and tools, including AI, can be used to predict trends and outcomes. We'll discuss different predictive models and techniques and their relevance in decision-making.

5. Lesson 5 - The Science of AI This lesson will cover the fundamental principles underlying AI and its development trajectory. We will discuss the current state of AI, the scientific challenges it faces, and its potential future advancements.

6. Lesson 6 - Predicting the Future with AI The final lesson will delve deeper into the use of AI as a predictive tool, specifically in the context of the AI and science-driven landscape. We will explore various predictive algorithms, their application, and how these predictions can be used to inform strategic decisions and innovation in businesses.

The methodology for this course will blend theoretical frameworks with practical case studies to ensure a deep understanding of the topics and their applicability in a business context.

- Lectures: Each session will be initiated with a lecture to introduce the fundamental concepts. The lectures will be interactive, encouraging students to participate and engage with the course content.
- Case Studies: A key component of the course methodology will be case studies, which are carefully selected to represent a wide range of scenarios and challenges in the AI and science-driven landscape. These cases will help students understand how theoretical concepts are applied in real-world situations, promoting a problem-solving mindset.
- Group Work: In several sessions, students will work in groups to analyze case studies, formulate strategies, or solve specific business challenges. This approach fosters collaboration, encourages diverse perspectives, and hones critical thinking skills.

The bibliography will be made available through the course website in eCampus

Group	Teacher	Department
Year 3	Luis Garcia Pareras	Esade

Group	Teacher	Department
Year 4	Luis Garcia Pareras	Esade