Coding Dojo: Let's do some TDD!

⌖ Cambridge · Churchill College, University of Cambridge

Hosted by ICAIDM

ICAIDM 2026 brings researchers and practitioners to Cambridge for three days of technical presentations, keynotes and discussion spanning artificial intelligence, digital infrastructure and data-driven management. The in-person conference takes place from 15–17 October 2026 at Churchill College, University of Cambridge, in Cambridge. Research themes The programme and call for papers cover both foundational AI research and real-world applications. Areas of interest include: - Machine learning and AI foundations: deep learning, reinforcement learning, transfer and meta learning, federated learning, model optimisation, explainable and trustworthy AI, and AI for scientific discovery - Communication and networking: intelligent wireless networks, traffic prediction, semantic communications, edge intelligence, AI-driven network management, and network security - Data and digital technologies: data engineering, big data analytics, knowledge graphs, cloud and edge computing, distributed platforms, IoT, cyber-physical systems, and data privacy - Digital management and AI applications: digital transformation, intelligent decision support, business analytics, smart cities, finance, industrial systems, operations optimisation, and emerging AI applications Attendees can expect an academic conference format built around paper presentations and keynote sessions. Its broad scope creates opportunities to compare methods across computer science, communications, infrastructure and management rather than treating AI as an isolated discipline. It is best suited to researchers, academics and technically focused industry professionals working on AI systems or digital management, as well as authors looking to present original work to an international audience. Publication and submission details Accepted invited and contributed papers are scheduled for publication in the ACM International Conference Proceeding Series (ACM ICPS) and submission to EI Compendex and Scopus for indexing. Proceedings papers must be at least eight pages. Full papers should be supplied in both Word and PDF formats through the conference submission route. Key deadlines are:… Register for this event

⌖ Cambridge · The Glasshouse @InnovateCambridge

Hosted by Cambridge Centre for Data-Driven Discovery

Explore how the Financial Times turns data and AI strategy into organisational value with Chief Data Officer Kate Sargent at this University of Cambridge seminar. From research to real-world AI Taking place in person on Tuesday 27 October 2026, from 4:00pm to 5:00pm, this Beyond Academia seminar offers a practical perspective on deploying data science and artificial intelligence beyond the university environment. The session will be held at The Glasshouse @InnovateCambridge, 100 Hills Road, Cambridge, CB2 1LQ. The Beyond Academia: AI & Data Science Applications series is designed to bridge the gap between high-level research and implementation inside organisations. Invited leaders and professionals examine the technical, architectural and operational realities of AI innovation while introducing attendees to career opportunities outside academia. Hear from Kate Sargent Kate Sargent, Chief Data Officer at the Financial Times, is responsible for the organisation’s Data and AI Strategy and for creating value from its data assets. Since joining the FT in 2023, she has led its award-winning Data & AI Governance, Data Science & AI, Analytics, Research and Business Intelligence disciplines. Kate brings 30 years of experience across major consumer-facing organisations in retail, travel and media. Her work focuses on using data to understand and influence customer behaviour and generate commercial value. Alongside her executive role, she is an industry commentator, board adviser and mentor, with a particular commitment to early-years skills development and increasing awareness of careers in data and analytics. Attendees can expect insight into: - How data and AI strategy operates within a global media organisation - The challenges and opportunities involved in implementing AI innovation - The role of governance, analytics, research and business intelligence - Translating data assets into practical and commercial value - Non-academic career pathways in data science and AI The format is an engaging one-hour talk with plenty of opportunity for audience Q&A, giving researchers and students direct access to an experienced data leader. Who should attend?… Register for this event

Sponsors: Bennett School of Public Policy · C2D3

⌖ Cambridge · West Hub, Room E, University of Cambridge

Explore how cutting-edge AI research becomes scalable, real-world products with BBC Head of Applied AI Dr Nikolay Burlutskiy in Cambridge on 10 November 2026. This in-person Beyond Academia: AI & Data Science Applications seminar offers a practitioner’s perspective on moving artificial intelligence beyond research and into complex organisations. Hosted by the Cambridge Centre for Data-Driven Discovery (C2D3), it takes place from 4:00–5:00pm on Tuesday 10 November 2026 in Room E at the University of Cambridge’s West Hub, JJ Thomson Avenue, Cambridge. From AI research to deployment The Beyond Academia series bridges the gap between high-level academic research and real-world implementation. Its invited talks examine the technical, architectural and operational challenges involved in deploying AI innovation, while also highlighting career paths outside academia. The format is an engaging one-hour talk with plenty of opportunity to put questions directly to the speaker. Attendees will hear from Dr Nikolay Burlutskiy, Head of Applied AI at the BBC, where he focuses on translating advanced AI research into scalable products used by millions. His career spans more than 15 years across AI research, technical product development and international enterprise strategy. Burlutskiy’s experience includes: - Serving as Senior Engineering Manager at Mars and leading the architecture and deployment of the Mars AI Experiences platform, an enterprise generative AI capability supporting more than 170,000 associates. - Working as Director of ML & AI at AstraZeneca, where he led scientists and engineers applying generative AI and computer vision to drug discovery, clinical data harmonisation and histopathology automation. - Leading AI technical product development at Sweden’s ContextVision and contributing to the creation of spin-out Inify. - Beginning his industry career as an AI engineer at Samsung Electronics in South Korea. He holds a PhD in AI, has more than 35 peer-reviewed publications and US patents, and contributes to the wider AI community as a speaker, conference organiser and reviewer. Who should attend?… Register for this event

◎ Online

Hosted by Massachusetts Institute of Technology (MIT)

Build production-ready AI and machine learning solutions without writing a single line of code. This comprehensive 12-week online program from MIT Professional Education transforms aspiring data scientists and business professionals into AI practitioners through hands-on, no-code workflows. Starting November 27, 2026, you'll master the latest AI technologies—from supervised learning and neural networks to Generative AI and autonomous agents—using intuitive platforms that eliminate traditional coding barriers. What You'll Master This industry-aligned curriculum covers the complete AI development lifecycle across 10 core modules and additional self-paced content. You'll explore data science fundamentals, prediction methods using regression and neural networks, decision systems, recommendation engines, and computer vision techniques. Advanced modules dive deep into Generative AI foundations, prompt engineering, and Agentic AI—the cutting edge of autonomous intelligent systems. The program culminates with critical training in ethical and responsible AI deployment. You'll work with powerful no-code platforms including KNIME, RapidMiner, Teachable Machine, ChatGPT, Gemini, NotebookLM, and Dall E. These tools enable rapid prototyping, testing, and operationalization of machine learning models without traditional programming knowledge. Hands-On Learning Theory meets practice through 3 comprehensive projects and over 20 real-world case studies spanning hospitality, marketing and advertising, EdTech, healthcare, food and nutrition tech, and e-commerce. You'll transform raw data into actionable business insights, build classification systems, deploy neural network solutions, and create recommendation engines—all using no-code methodologies that reflect current industry practices. World-Class MIT Faculty Learn directly from MIT's leading researchers and educators, including Stefanie Jegelka, Caroline Uhler, John N. Tsitsiklis, Munther Dahleh, and Devavrat Shah. Their expertise ensures you're learning cutting-edge techniques aligned with academic research and industry application. Flexible Online Format This fully online program requires 6-12 hours weekly commitment over 12 weeks (approximately 80 total study hours). The asynchronous format allows you to balance learning with professional and personal commitments while progressing through structured modules. Upon successful completion, you'll receive a Certificat

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⌖ Cambridge · Madingley Hall Conference Centre

Hosted by Flivo

One-day summit at Madingley Hall Conference Centre, Cambridge on 2026-11-29 exploring how intelligent AI agents are redefining decision-making.

⌖ Cambridge · Peterhouse College, Cambridge

Hosted by BCS Specialist Group on Artificial Intelligence (SGAI)

AI-2026 marks the forty-sixth edition of Europe's longest-running AI conference series, bringing together researchers, practitioners, and students to Cambridge for three days of cutting-edge artificial intelligence discourse. Hosted by the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) at the historic Peterhouse College, this leading UK-based international conference has established itself as a cornerstone event in the global AI research community. What to Expect The conference features a comprehensive programme spanning 15-17 December 2026, offering multiple streams of engagement. Attendees can participate in technical and application streams, poster sessions showcasing emerging research, and four half-day workshops running in parallel streams on the opening day. The event is designed to accommodate various formats of knowledge sharing, from full 14-page papers to short 6-page poster papers, all peer-reviewed to rigorous professional standards and published in Springer's prestigious Lecture Notes in Artificial Intelligence series. Pre-Conference Research Forum The conference kicks off on 14 December with FAIRS'26 (Forum for AI Research Students), an inclusive session open to all research students for a modest fee covering lunch and refreshments. This provides PhD candidates and early-career researchers with a dedicated platform to present work-in-progress and connect with peers. Who Should Attend AI-2026 welcomes academics, industry practitioners, researchers, and students working across all areas of artificial intelligence. Whether you're presenting groundbreaking research, exploring practical applications, or seeking to expand your knowledge of current AI developments, this conference offers valuable opportunities for learning and networking. The inclusion of both technical and application streams ensures relevance for those focused on theoretical advances as well as real-world implementations. Submission and Publication Key dates include paper submission by 26 June 2026, notification of acceptance by 1 September 2026, and camera-ready papers due 14 September 2026. All accepted papers undergo full peer review and appear in the published proceedings, providing authors with recognition in a respected academic publication series. Set in the inspiring academic atmosphere of Cambridge, AI-2026 continu