Register your interest in the September 2026 cohort of Code in Place, a foundational technology training programme delivered by Digital Jersey in partnership with Alca.ai.
Designed as a beginner-friendly introduction to programming, the course helps individuals in Jersey build practical coding skills and confidence in modern digital technologies, including AI.
Whether you’re a student, career changer, entrepreneur, or professional looking to build digital skills, the programme provides a structured and supportive way to learn the fundamentals of programming.
Developed by Stanford University and delivered locally through the Digital Jersey Academy, Code in Place combines world-class learning content with practical application and guided support.
Course Structure & Study Commitment
The programme combines self-paced learning with guided support.
In addition to independent 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:
The programme follows the globally recognised Stanford University “Code in Place” model and is built on principles of Human-Centred Education. It combines high-quality learning materials with real-world case studies, mentoring, and coaching to deliver a high-impact learning experience.
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.