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Rebekah Yore, final-year PhD student in risk and disaster reduction at University College London and a volunteer with Servon, a UK-based search and rescue organisation.

I've always been passionate about making a meaningful difference in humanitarian responses. However, my work has consistently highlighted one crucial challenge: understanding how to effectively manage and analyse complex information during crisis situations.

Before the course, I'd witnessed first-hand during humanitarian responses the immense challenge of rapidly assimilating, synthesising, and collating information from various sources to understand the situation on the ground. 

While I had some prior exposure to AI in information analysis through a collaboration with the University of Oxford involving satellite imagery, the processes felt somewhat like a 'black box'.

The Space Software CPD bridging course was brilliant in demystifying the world of data science. Unlike traditional coding courses that can feel abstract and disconnected from real-world applications, this programme took an incredibly nuanced approach. It wasn't just about creating expert coders, but about context, application, and impact.

The programme took us through basic Python coding but more importantly, we learned how to think about data – how to approach information synthesis, how to ask the right questions, and how to collaborate effectively with technical teams. Crucially, it demonstrated the practical impacts of coding by applying it to things like satellite imagery. Seeing how lines of code could translate into visual data and understanding the journey from data acquisition to presentation was incredibly motivating and made it all feel so tangible.

What stood out about the course was the expert instruction from the ������� team. Their in-depth knowledge and ability to explain complex subjects to beginners like myself was invaluable. The supportive and patient learning environment they fostered was also fantastic, with instructors offering individual attention and tailoring their support to our different needs and levels of experience.

What once seemed like an impenetrable technical domain now feels like an accessible toolkit for solving complex problems. I now understand not just the 'what' of data analysis, but the 'how' and the 'why'. This means I can communicate more effectively with data scientists, articulate precise requirements, and understand the processes behind information generation and analysis.

Looking ahead, I feel much more confident engaging with data scientists in future humanitarian responses. My expectations around data processes are now far more realistic, and I believe I can be more helpful in articulating our needs and providing relevant information. Furthermore, having gained foundational knowledge and some basic coding skills in Python, I'm keen to continue this learning journey and potentially conduct basic map analysis myself. 

I would absolutely recommend this course to anyone working in humanitarian, academic, or professional fields who wants to bridge the technology gap. It's not just about learning to code – it demonstrates how technology can make us more effective, more informed, and ultimately more impactful in addressing complex global challenges.

Toby Meredith, drone safety officer and PhD student at the ������� 

“As a part-time drone safety officer at the �������, my role involves not only ensuring compliance with drone regulations but also supporting various research projects that use drone technology. 

“My work has taken me from mapping hurricane damage in Dominican Rupublic to collaborating with the UN World Food Programme on disaster management initiatives. Despite being comfortable with data collection and basic orthomosaic mapping through automated software, I always felt there was a gap in my understanding of how different remote sensing datasets were integrated to create actionable intelligence. I knew that coding was becoming increasingly essential in my field, but with my last experience dating back to an old VBC computer 30 years ago, I was essentially starting from scratch. 

“While my PhD in social sciences focuses on drone technology for search and rescue in the English Channel, I knew that understanding coding processes was essential to grasp what's possible, what isn't, and the practical considerations of transforming raw data into actionable intelligence.

“The course structure was excellent. The combination of online learning and in-person sessions was incredibly effective, allowing for hands-on practice and valuable networking with others —particularly reassuring for those of us with limited coding experience. 

“The teaching quality was exceptional; the course facilitators demonstrated extraordinary knowledge while remaining approachable and supportive. They effectively held our hands during those challenging early stages, ensuring we weren't overwhelmed as the content advanced.

“What struck me most was how the academics demystified complex concepts like AI and machine learning, making them accessible even to those without a technical background. This deeper understanding of how and why these technologies work—rather than simply how to use them—has been transformative. The step-by-step approach to learning Python, complemented by immediate visual results in our data outputs, built confidence even as we tackled unfamiliar territory.

“While I haven't emerged as a coding expert—learning Python is much like acquiring a new language that requires regular practice—the course has given me the foundation and confidence to continue developing these skills independently. I now have access to valuable resources I can reference when applying coding in practical scenarios, particularly in my volunteer work with Servon, an international search and rescue organisation.

“The ability to process drone data and generate maps for disaster response could significantly enhance both Servon's on-ground operations and their collaboration with UN agencies and local government departments. Being able to process drone data and generate real-time damage assessments could significantly improve response coordination and aid distribution. 

“The course's emphasis on data quality—the principle that "rubbish data in equals rubbish data out"—underscores the importance of proper coding processes for meaningful outputs. Whether mapping damaged buildings after a disaster or pursuing other applications, this course provides the knowledge and confidence to navigate the increasingly essential world of Python, coding, and machine learning for earth observation.

“I would highly recommend the Space Software CPD bridging course to others, regardless of their field of expertise. It equips technical professionals with the understanding and skills to handle complex data workflows, but also managers insight into what's reasonable to expect, what's possible, and the timeframes involved. Overall, my experience on this course has been transformative, and I look forward to applying these skills in in practical and impactful ways in the future.

Xavia Downs, consultant in system engineering at Sirius Analysis

The Space Software: Data and AI CPD course was a perfect fit for my professional passion and personal curiosity. Working almost exclusively in the space domain, particularly satellite communication, and with Sirius’s strong presence in space, software, and machine learning, this course matched both my career goals and our company’s strategic goals.

The programme was brilliantly structured, beginning with a comprehensive first phase that provided an incredible breadth of technical knowledge, while introducing new and unexpected applications of space technology. Given the complexity and breadth of the space sector, this was particularly useful—it levelled the playing field for all participants, ensuring we had a common knowledge base before moving into more specialised areas.

The second phase built upon this foundation with a carefully curated deep dive into technical topics, tailored to the interests and needs of the delegates. It combined knowledge acquisition with real-world relevance, allowing me to focus on areas that were directly applicable to my role. 

However, it was the third phase of the course that truly set it apart. This was where I and my colleagues at Sirius Analysis had the opportunity to take charge of our own professional development by selecting and leading our own project. We chose to investigate the use of machine learning to predict wildfires using Earth Observation data. 

The ‘fail fast’ approach meant we were encouraged to experiment, make mistakes, and learn from them rapidly. This hands-on experience was invaluable—it allowed us to consolidate our learning, apply complex concepts in a practical setting, and gain a much deeper appreciation of the challenges involved in working with real-world data in the space domain.

While I had prior experience with machine learning, the course highlighted that the most challenging part of an AI project isn’t necessarily building the model—it’s preparing the data. It's in the meticulous process of sourcing, processing, and refining data - understanding its strengths, weaknesses, and potential biases. The lecturers were extraordinary, offering insights that went far beyond textbook knowledge, drawing from years of practical, real-world experience in the field.

Beyond the technical learning, the networking opportunities were equally valuable. I connected with professionals from across the space sector, from start-ups to industry-leading companies such as BAE and Airbus. These weren't just casual interactions, but meaningful exchanges of knowledge and expertise. We tackled tutorials together, solved complex problems side by side, and created a supportive learning environment that extended far beyond the classroom.

Another major benefit of the course was its focus on the commercial side of the space sector. Understanding how to bid for space-related work is a crucial skill, particularly in a highly competitive industry where securing contracts often depends on demonstrating both technical capability and a deep understanding of client requirements. This knowledge has been instrumental in helping Sirius Analysis refine our approach to winning new business and expanding our capabilities in the space sector.

I would strongly recommend this course to any individual or organisation looking to upskill in the space sector. Whether you’re an employee seeking to deepen your technical knowledge, a company looking to enhance its capabilities, or an organisation aiming to strengthen its position in the industry, this course offers a wonderful opportunity to gain expertise, build connections, and develop the practical skills needed to succeed in the evolving world of space software.

John Chinner, Head of Outreach for Airbus Defence and Space UK 

At Airbus, we constantly face the challenge of finding experienced professionals with the right digital skills for our space and ground segment technologies. That's why the  has been instrumental in bridging that gap, equipping participants from both within and outside the space sector with the expertise we’re looking for.

Through our Community for Space Prosperity (CUSP), we've been looking for innovative ways to bridge skills gaps and bring fresh talent into the space industry. This course represents exactly the kind of solution we've been seeking. By working closely with the �������, we've helped design a programme that provides targeted training in exactly the areas we need, equipping professionals with the technical skills and confidence to transition into the space industry. 

It's not just about pumping out technically skilled graduates. Instead, it provides a comprehensive overview of the space industry, exposing participants to the breadth and depth of opportunities available. From earth observation to cutting-edge software technologies, students get a panoramic view of the sector. This approach is crucial – it helps individuals not just find a job, but discover their genuine passion within the vast world of space technology.

Participants aren't just absorbing theoretical knowledge; they're creating real-world outputs. They write code, develop projects, and most crucially, generate a portfolio that speaks directly to potential employers like Airbus. For many professionals in adjacent industries like automotive, this course provides a bridge to understand how their existing skills can translate into exciting space sector opportunities.

The course's impact extends far beyond individual skill development. It's reshaping how we think about talent in the space sector. We're not just filling job roles; we're cultivating a more diverse, innovative workforce that can drive the UK's space industry forward. Whether it's helping career changers, upskilling existing talent, or inspiring the next generation of space entrepreneurs, this programme represents a critical intervention in our skills ecosystem.

We want people to understand that space isn't just for PhD rocket scientists – it's an industry hungry for talented, adaptable professionals from all backgrounds. The more people we can bring into the sector with the right skills, the stronger and more competitive our industry will be.