2 Cohorts for 2026
Cohort 1: Starting April 2026
Cohort 2: Starting September 2026
Course Structure & Study Commitment
This foundational technology training programme—developed by Alca.ai in partnership with Digital Jersey—is designed to empower individuals in Jersey with the skills needed to thrive in the digital economy. Whether you’re a student, career changer, or entrepreneur, the course helps you build confidence and practical capability in programming and modern AI systems.
In addition to self-study, learners will take part in a blend of weekly online sessions and in-person sessions held at the Digital Jersey Academy. The programme includes 8 live sessions delivered over 9 weeks, providing opportunities for guided learning, discussion, and practical application.
The programme follows the globally recognised Stanford University “Code in Place” model and is built on principles of Human-Centred Education. It combines world-class learning content with real-world case studies, mentoring, and coaching to deliver a high-impact learning experience with strong learner support and engagement.
The course is designed to support independent learning. Participants should expect to commit around 5 hours per week, working through self-paced materials at a time and pace that suits them.
Francois Chesnay
My journey into Artificial Intelligence began in the mid-80s till the late 90s, with a pause of 15 years. It reignited in 2015 when AI was used to play Atari games, demonstrating significant advancements in deep learning, and ultimately leading me to complete Stanford’s Artificial Intelligence Graduate Certificate Program. Prior to this, I earned an MBA from the University of Chicago-Booth, a Master’s from the London School of Economics and enjoyed a career in structured finance, venture capital, and corporate restructuring. As a course facilitator for XCS221 Artificial Intelligence: Principles and Techniques and XCS224N Natural Language Processing with Deep Learning at Stanford’s Engineering Center for Global & Online Education, I support global learners in AI. I also serve as a non-executive director, advise on AI and strategy, and mentor startup founders.
Gianfranco Bombardieri
I lead the Global Business Intelligence & Automation practice at Adaptive, a fintech consultancy, where I help C-suite executives transform complex data into actionable insights that drive smarter decision-making. Teaching is equally central to my work. For three consecutive years, I’ve had the joy of instructing Stanford’s Code in Place program, teaching introductory programming to students worldwide. This experience has deepened my conviction that the best learning happens when complex concepts become accessible and engaging.
My professional journey began in sports analytics, supporting UEFA and FIFA competitions, which revealed data’s transformative power through computer vision and creative analysis. I later contributed to the London 2012 Olympics and joined the International Olympic Committee in Lausanne, shaping strategy and data initiatives for the global sports industry.
I hold an MBA focused on quantitative decision-making methods and continue expanding my expertise in AI, machine learning, and neural networks.