Summer School
Artificial Intelligence
Discover the Challenges and Opportunities of AI Applications
Application FormLearning
Face-to-face
Language
English
Start
30 June - 18 July 2025
Credits
9 ECTS
Artificial Intelligence Summer Programme
Who is it aimed at?
University students, professors, researchers and professionals from any industry. Embark on a transformative journey into the world of Artificial Intelligence this summer by enrolling in the Artificial Intelligence Programme at CUNEF Universidad!
Whether you are a university student, professor, researcher, or professional working in any field, if you are interested in learning more about AI, this programme is designed for you. No prior knowledge is required.
Why choose this programme?
- Master the foundations of AI:
Gain a comprehensive understanding of Artificial Intelligence, from machine learning to natural language processing.
- Discover real-world applications:
Learn how AI is shaping industries and unlocking new opportunities in business, health, and much more.
- Gain practical hands-on experience:
Dive into Python programming, explore data analytics, and experiment with cutting-edge tools for Generative AI.
- Prepare for the Future:
Understand the impact of AI on society and learn more about emerging professions and challenges in this dynamic environment.
Learning Objectives
Reflect on, analyse and accept with an open mind...
... the changes that we are currently experiencing, to understand their impact on today’s society and identify new professions, challenges and opportunities.Learn to program simple algorithms in Python...
... to illustrate the implementation of intelligent systems using machine-learning techniques.Learn the fundamentals of Generative Artificial Intelligence...
... and the different tools available, as well as their applications in different areas of business.Learn how to apply intelligent systems...
... such as Natural Language Processing and other cutting-edge technologies.
Methodology
The Artificial Intelligence Summer Programme uses a dynamic and comprehensive learning model to ensure that participants not only gain theoretical knowledge, but also understand how to apply it in real-world situations. You will take part in:
- Engaging lectures:
Dive into expertly crafted sessions that unravel basic and advanced concepts of Artificial Intelligence, from algorithms to generative tools.
- Critical discussions and debates:
Expand your vision by participating in thought-provoking discussions on AI ethics and societal impact, as well as its transformative role in various industries.
- Hands-on programming sessions:
Step into the lab and practice what you’ve learned! Use Python to code algorithms in, analyse data using RStudio, and experiment with the latest AI tools to create text, images, and videos.
- Assessment and Integration:
Evaluate your progress using structured module assessment tools and implement everything you’ve learned in AI projects where you will use data storytelling to share insights.
Course program
Day 1:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Introduction: Birth and evolution of Artificial Intelligence |
| 11.00 a.m.-12.30 p.m. | Fundamentals of AI: Machine Learning, Natural Language Processing and Computer Vision |
| 12.45-14.15 p.m. | Case Studies |
Day 2:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Introduction: Ethical Implications |
| 11.00 a.m.-12.30 p.m. | Fundamental Algorithms I: Design Strategies |
| 12.45-14.15 p.m. | Laboratory: AI Programming Paradigms |
Day 3:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Introduction: Cybersecurity |
| 11.00 a.m.-12.30 p.m. | Fundamental Algorithms II: Searches |
| 12.45-14.15 p.m. | Laboratory: Python Implementations |
Day 4:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Introduction: Cybersecurity |
| 11.00 a.m.-12.30 p.m. | Fundamental Algorithms II: Searches |
| 12.45-14.15 p.m. | Laboratory: Python Implementations |
Day 5:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Module Assessment Test |
| 11.00 a.m.-12.30 p.m. | Designing an Intelligent System |
| 12.45-14.15 p.m. | Laboratory: Python Implementations |
Day 1:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Data and Big Data Technologies |
| 11.00 a.m.-12.30 p.m. | Data Collection: Sensors, Networks and Social Media |
| 12.45-14.15 p.m. | Laboratory: Cloud Data Collection |
Day 2:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Open Data and Open Government |
| 11.00 a.m.-12.30 p.m. | Packages for Data Pre-Processing |
| 12.45-14.15 p.m. | Laboratory: Data Pre-Processing in Practice |
Day 3:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Data Science for Business |
| 11.00 a.m.-12.30 p.m. | Data Analytics I: Fundamentals of Statistics |
| 12.45-14.15 p.m. | Laboratory: RStudio for Data Analysis |
Day 4:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Data Science for Health and Social Care |
| 11.00 a.m.-12.30 p.m. | Data Analytics II: Clustering |
| 12.45-14.15 p.m. | Laboratory: RStudio Cluster Libraries |
Day 5:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Module Assessment Test |
| 11.00 a.m.-12.30 p.m. | Data Integration in Intelligent Systems |
| 12.45-14.15 p.m. | Laboratory: Data Visualisation |
Day 1:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Introduction to Generative AI |
| 11.00 a.m.-12.30 p.m. | Transforming Business with Generative AI |
| 12.45-14.15 p.m. | Case Studies |
Day 2:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Technological Risks of GenAI |
| 11.00 a.m.-12.30 p.m. | Natural Language Processing |
| 12.45-14.15 p.m. | Laboratory: Text Generation Tools |
Day 3:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Improving Productivity with GenAI |
| 11.00 a.m.-12.30 p.m. | Computer Vision |
| 12.45-14.15 p.m. | Laboratory: Image and Video Generation Tools |
Day 4:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Internet of Things and Robotics |
| 11.00 a.m.-12.30 p.m. | Parallel Programming and Cloud Computing |
| 12.45-14.15 p.m. | Laboratory: Building AI Projects |
Day 5:
| SCHEDULE | CLASS |
|---|---|
| 9.00-10.30 a.m. | Module Assessment Test |
| 11.00 a.m.-12.30 p.m. | Sharing Data-Driven Insights with Data Storytelling |
| 12.45-14.15 p.m. | Closing Session |
Life at CUNEF Universidad
At CUNEF Universidad, you will find an environment that supports and encourages learning and professional development, with the sole purpose of enhancing your talent.
For more than 50 years, CUNEF’s guiding principles have been the specialisation of its academic offering, the excellence of its students, professors and researchers, and its international vision. In the next 50 years, CUNEF Universidad intends to follow these same principles, combined with: academic rigour, to be a benchmark in teaching and research; dedication, to become a driving force for research and innovation; plurality, to integrate different points of view, and encourage transversality and collaboration in decision-making; and equity, to guarantee equal opportunities through a scholarship and financial aid system that enables the institution to shape leaders capable of transferring these values to their environment.
Why come to Madrid?
Madrid is a vibrant city with a vast cultural heritage and many sights and activities to explore:
- Landscape of Light (Prado, Reina Sofia, Thyssen-Bornemisza, Retiro Park)
- Wide range of cultural activities (Opera, Theatre, Ballet)
- Unique monuments and buildings (Royal Palace, Cibeles, Puerta de Alcalá)
- Culinary venues