Video testimonial
Roche has been one of the first adopters of the AI Literacy Academy. Jesús López Rivera and Dr. Frank Block share their thoughts on the program in this video.
"Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons on whom the AI systems are to be used."
Testimonials
"The course is absolutely fantastic! The explanations are clear and concise, breaking down complex topics into easy-to-understand concepts"
"This course offered invaluable insights into AI fundamentals and applications. I highly recommend this course to anyone wanting to boost their AI literacy"
"Sandro has a real talent to extract the key points you need to consider when embarking on the data and AI journey. I strongly recommend this AI Literacy Academy"
"I really enjoyed the videos and suggested resources for further knowledge building. Definitely recommended"
"The course is very informative, especially in outlining what AI is all about as opposed to the misinformation that has been spread about it. It was interesting to learn how AI can be used to analyze and interpret data"
"Crisp and thorough course covering the essential elements of AI fundamentals. By the end of the course, I gained a solid understanding of AI foundations, which I found immensely valuable."
Why such a course ?
"Anyone who stops learning is old, whether at twenty or eighty." (Henry Ford)
Artificial Intelligence (AI) is generating tremendous buzz, and understanding its core concepts is essential to truly harness its power. In today’s world, data is a key asset for any company, and knowing how to effectively leverage it can unlock new opportunities. However, successful data transformation isn’t just about technology—it’s about people speaking the same language and aligning around shared goals.
As data and AI become more integral to business, building these skills is crucial for staying competitive in the job market:
Learn at your own pace, get straight to the point, and leverage my 20 years of experience in Data & AI.
Discover concepts and approaches illustrated with real use cases from various industries.
Enjoy high quality videos featuring a human speaker and customized animations.
The course should take you half a day to complete (30min per module). It includes:
A total of 10 modules, each with a short video, a quiz, an exercise, and references.
A certificate attesting to your participation in the course.
Unlimited access to the course content (incl. new modules)
There are no prerequisites for this "entry-level" course (no technical background is needed). It is particularly tailored to:
C-level executives: Understand key AI concepts to ensure your organization harnesses the full potential of data and AI to drive innovation and maintain a competitive edge.
Managers: Learn how to effectively lead data-driven initiatives, align projects with business objectives, and foster a culture of data-informed decision-making within your teams.
Employees: Discover how data and AI can be leveraged in your daily tasks, enhancing productivity and contributing to the success of your role.
Details of the course
Learn about the course, your instructor and the viadata company.
Before leveraging data using AI, it is important to acquire basic data visualization skills. The content of this module is essential for anyone dealing with data. The video covers how to read and design data visualizations.
With recent advances in AI, it is crucial for everyone to understand key concepts. For example, what is the difference between AI, Machine Learning, and Deep Learning? Additionally, we discuss the distinction between classification and regression, as well as the challenge of overfitting.
In order to imagine what is feasible with AI, it is important to explore existing AI use cases. This module explains three projects from different companies and industries. We focus on the context, the business impact, and the lessons learned.
AI projects are all unique, yet they share common characteristics. Based on best practices, a standard data science process can be applied to any data initiative. In this module, we illustrate the CRISP-DM process and provide tips and tricks for executing each step toward a successful project.
Having an idea about how to leverage data in your company is a great starting point. The next step is to transform that idea into a project proposal. To ensure all stakeholders of your data initiative are aligned, it is recommended to use a one-pager document such as the Data Initiative Canvas.
To leverage a new technology like Generative AI, it’s important to understand how it works. This module explains what Generative AI is and provides examples of image and text creation approaches. ChatGPT is used as an illustration of this new technology.
This module is a follow-up to the Generative and ChatGPT one. It explains the concept of prompting in more detail, providing tips and tricks to prompt effectively and enhance the output you get from Generative AI tools.
There is no magic behind artificial intelligence. While AI is a powerful tool, it is limited. AI has no common sense and is not intelligent in the way we - humans - define it. This course provide several examples where artificial intelligence reaches its limits. Three current trends in AI are also discussed.
Since AI systems are becoming mainstream, it is key to understand how they work. It is also crucial to understand the challenges related to black-box models, bias in the data, and the scale at which these systems are used. AI is impacting society, and companies must follow established regulations to deploy trustworthy AI applications.
Data-driven transformation is a marathon, not a sprint. Many companies struggle to progress, mainly due to the human factors involved in the transformation. This course provides advice on designing an AI roadmap and discusses several challenges associated with data-driven transformation. For each challenge, a recommendation is provided to help overcome it.
In this section, we provide details about the course certificate, a file containing further readings in Data & AI and a survey to share your feedback about the course.
Your course instructor
Data & AI advisor
I am passionate about helping companies to become even more data-driven. I have worked in various industries to foster usage of data. As Head of the Industry Unit of the Swiss Data Science Center (SDSC), I built a team of 20 data scientists and initiated 25 collaborations with companies such as Richemont, Logitech, Merck, Adecco and Firmenich. Prior to SDSC, I gained experience in a wide range of companies such as Swisscom (consultant), SICPA Security Solutions, Expedia and Nestlé Nespresso. I am a lecturer at Business School Lausanne (BSL) and in the executive certification program in Data Science & Management at HEC Lausanne. I am a member of the executive committee of CDOIQ Europe, an association that supports the role of Chief Data Officer in Europe. I co-founded the Swiss Association for Analytics in 2013 to promote Data Science in Switzerland through regular meetups. I hold a PhD in Computer Science from the Ecole Polytechnique Fédérale de Lausanne (EPFL).