Artificial Intelligence: Cloud and Edge Implementations (online)


Artificial Intelligence: Cloud and Edge Implementations is a pioneering online course covering AI, MLOps (Machine Learning and DevOps), cloud computing, and edge computing. For the first time, the course is also available online. Designed for industry practitioners with some background in coding, the course is ideal if you have development, design, or software architecture experience and want to transition your career toward AI.

This course is designed to create a new breed of engineer through a solid grounding in artificial intelligence (AI), edge computing (Internet of Things), MLOps, and Cloud technologies to develop production systems within a full-stack environment.

Previous students have used the course to start or progress their Artificial Intelligence career or have their skills upgraded by their employer. To make the most of the course, we expect you to have a mindset of exploration and study and learn beyond the class material itself (depending on your familiarity with the subject).

Python (TensorFlow) is the course's primary language, and while we do not expect you to have full proficiency in it, we expect you to have a programming background. This is an industry course, rather than an academic one, focusing on skills-based/commercial products.

Helping you transition your career towards Artificial Intelligence 

The philosophy of the course is based on helping you transition your career to Artificial Intelligence. In this context, we use the term AI to mean deploying machine learning and deep learning in a production environment.

While AI is a new topic, it does not exist in isolation. Especially in large enterprises, AI is deployed within the framework of existing systems. Thus, there are three job categories related to AI i.e., the data engineer, the data scientist, and the DevOps engineer. Because the course takes a full-stack/MLOps approach, the course allows you to approach new ideas within your existing knowledge framework.

Past students have leveraged this comprehensive aspect of this course to change their careers towards AI by expanding on a set of skills for the AI pipeline, which best suits them. The course provides you with skills in cloud programming (Azure, AWS, and Google), Python development (TensorFlow and Keras), MLOps, and Edge (IoT). You start coding from the second session and continue to do so throughout the course. You get an extra month after completion of the course to complete the coding exercises.

We also provide a firm grounding in Cloud technologies and support through one-on-one career mentorship (if requested). While we cannot guarantee a specific outcome, past students have successfully transitioned to AI.

Programme details

The course comprises of the following tracks and themes (note that these tracks progress in parallel).

Foundations track

  • Machine Learning principles
  • Deep Learning principles
  • Foundations of Edge computing
  • Full Stack development (in context of AI)
  • MLOps – Machine learning and DevOps
  • Cloud-native development
  • Cloud development process flows

Hands-on Python for Data Science track

We use Python (TensorFlow). The track spans almost the entire length of the course. This track covers:

  • Hands-on machine learning development including the main libraries like NumPy, Pandas, Matplotlib, SciKit-Learn
  • Hands-on deep learning development for the main algorithms
  • This track covers: Classification using Multi-layer perceptron (MLP) by establishing a baseline and improving that baseline using techniques like dropout; Regression – linear regression, logistic regression, multivariate regression, etc.; Convolutional Neural Networks; Natural Language Processing; Recurrent Neural Networks; Autoencoders and Unsupervised Learning (PCA and K-means)

MLOps development track

The MLOps development track is a hands-on set of modules that span almost the course's entire length. Track contents include:

  • Build and deploy modules using containers on edge devices
  • End to End deployment of machine learning and deep learning models using the Azure cloud

Deep Learning and advanced algorithms track

The Deep Learning and advanced algorithms track covers more advanced algorithms, including:

  • Autoencoders
  • Natural Language Processing (NLP)
  • Unsupervised Learning
  • Representation Learning
  • Generative Adversarial Networks (GANs)
  • Bayesian approaches to machine learning and deep learning
  • Reinforcement Learning
  • Probabilistic machine learning

Cloud and Edge Implementations track

The Cloud and Edge implementations track covers the main themes for the course and covers modules, including:

  • Machine Learning and Deep Learning implementation in the Google Cloud, Azure and Amazon Web Services platforms
  • Azure Sphere for deploying Machine Learning and Deep Learning implementation models on embedded devices
  • Time series development
  • Industrial IoT
  • Embedded AI (Intel, ARM platforms)
  • Computer Vision
  • Predictive Maintenance with MATLAB & Simulink
  • Signal Processing for Deep Learning with MATLAB

Industry insights track

This track brings in industry experts who provide implementation details across domains. These include:

  • Bioinformatics and Drug discovery
  • 5G
  • Affective Computing - AI and Emotions
  • Robotics

Coding and Projects

Spanning across tracks, examples of the coding and projects included in this course:

  • MLOps – deployment of Machine Learning and Deep Learning models in containers – on edge devices
  • Machine learning track – end to end
  • Deep learning track – end to end
  • IoT / time series models
  • IoT anomaly detection

Ecosystem track

The ecosystem track includes modules which cover the broader AI/Edge development issues, including:

  • Career mentorship in brief pre-planned sessions with Ajit Jaokar
  • AI innovation in countries

Note: the program details and tutors named on this course may be subject to minor changes.

Tutors and their teaching subjects on this course

Senior Course Tutors

Ajit Jaokar - AI, ML, edge, cloud architectures, maths

Ayse Mutlu - ML/DL algorithms, Azure and also responsible for all development sprints

Marina Fernandez - machine learning and deep learning algorithms

Dr Amita Kapoor - machine learning and deep learning algorithms, natural language processing (NLP)

Anjali Jain - machine learning and deep learning algorithms, cloud architectures

Paul Clarke - digital twins

Course Tutors: Cloud - Amazon Web Services

Dr Mustafa Aldemir - AWS, robotics

Course Tutors: Cloud - Microsoft Azure

Paul Foster - Azure IoT

Amy Boyd - Azure AI

Course Tutors: Cloud - Google Cloud Platform

Laurence Moroney - Google Cloud Platform, mobile and edge devices

Dr Saed Hussain - AI on Google Cloud Platform

Course Tutors: Python coding - core algorithms

Dan Howarth - Python core models

Jean Jacques Bernard - PyTorch

Course Tutors: Advanced Algorithms

Hamaad Shah - representation learning and feature engineering

Jakub Langr - GANs

Phil Osborne - reinforcement learning

Kajal Singh - reinforcement learning

Francesco Ciriello - signal processing for deep learning

Alexander Denev - probabilistic graphical models

Dr. Matt Taylor - reinforcement learning

Course Tutors: IoT Edge

Jahanzeb Ahmad - Intel FPGAs

Bojan Komazec - Nvidia Jetson

Dr Robert Dimond - ARM

Cynthia Joachimpillai - 5G/ IoT

Course Tutors: Industry experiences and innovation

Barend Botha - UX

Maria Pocovi - affective computing

Dr Martin-Immanuel Bittner - AI in healthcare

Dr Saeed Khalfan Al Dhaheri - AI ethics in government

Dr Ghida Ibrahim - AI for IT operations (AIOps)

Tugce Yalcin and Matthew Berrick - AI and intellectual property rights (IPR)

Jan Zawadzki - AI and design



Participants who satisfy the course requirements will receive a University of Oxford electronic certificate of completion. To receive a certificate at the end of the course you will need to:

  1. Achieve a minimum attendance at online sessions of 75%.

  2. Answer all the learning quizzes provided (these are short quizzes designed to ensure you have understood the material in each unit).
  3. Participants are expected to actively participate and complete the exercises which will be given during the course. These exercises involve coding / hands-on exercises (individually and also in groups) in sprints relating to AI, Cloud, IoT and Robotics. 

The certificate will show your name, the course title and the dates of the course you attended.

Dates, Times and Delivery

The course takes place online on Saturdays and Tuesdays. There is a minimum attendance requirement of 75%.

Saturday sessions:

4 to 6 hours of virtual classroom learning on Saturdays (10:00 - 16:30 including breaks)

  • 4, 11, 18 December 2021
  • 8, 15, 22, 29 January 2022
  • 5, 12, 19, 26 February 2022
  • 5 March 2022

Tuesday sessions:

1 to 2 hours online each week on Tuesdays (usually starting at 19:00)

  • 7, 14, 21 December 2021
  • 11, 18, 25 January 2022
  • 1, 8, 15, 22 February 2022
  • 1, 8 March 2022

A world clock, and time zone converter can be found here:

We recommend you allow around 10 - 12 hours study time per week in addition to the hours outlined above.

You will be fully supported by the core team of tutors who will be available during the week to answer questions.

A limited number of participants ensures that all those taking this course gain the maximum possible value.


Description Costs
Course fee (standard) £2995.00


Ajit Jaokar

Senior Tutor

Based in London, Ajit's work spans research, entrepreneurship and academia relating to artificial intelligence (AI) and the internet of things (IoT). 

He is the course director of the course: Artificial Intelligence: Cloud and Edge Implementations. Besides this, he also conducts the University of Oxford courses: AI for Cybersecurity and Developing Artificial Intelligence Applications.

Ajit works as a Data Scientist through his company feynlabs - focusing on building innovative early stage AI prototypes for domains such as cybersecurity, robotics and healthcare.

Besides the University of Oxford, Ajit has also conducted AI courses in the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM) and as part of the The Future Society at the Harvard Kennedy School of Government.

He is also currently working on a book to teach AI using mathematical foundations at high school level. 

Ajit was listed in the top 30 influencers for IoT for 2017 along with Amazon, Bosch, Cisco, Forrester and Gartner by the German insurance company Munich Re.

Ajit publishes extensively on KDnuggets and Data Science Central.

He was recently included in top 16 influencers (Data Science Central), Top 100 blogs (KDnuggets), Top 50 (IoT central), and 19th among the top 50 twitter IoT influencers (IoT Institute). 

His PhD research is based on AI and Affective Computing (how AI interprets emotion).

Ms Ayşe Mutlu

Senior Tutor

Data Scientist

Ayşe Mutlu is a data scientist working on Azure AI and devops technologies. Based in London, Ayşe’s work involves building and deploying Machine Learning and Deep Learning models using the Microsoft Azure framework (Azure DevOps and Azure Pipelines).

She enjoys coding in Python and contributing to Open Source Initiatives in Python.

Marina Fernandez

Senior Tutor

Digital Hive and Innovation consultant, Anglo American Plc

Marina is an Analyst Developer and Software consultant at Anglo American Plc working at the Digital Hive on innovative trading analytics and optimisation projects.

She has over 18 years’ experience in Software Engineering, Business Analysis, Data Science and full software development life cycle in a variety of business domains including Commodity trading and optimisation, Finance, Machine Learning and Artificial Intelligence, e-commerce, e-learning, web-development.

Marina holds an MSc, with distinction, in Software Engineering from the University of Oxford and a degree in Applied Mathematics from Lomonosov Moscow State University. 

In February 2020, Marina completed the course "Data science for internet of things" from the University of Oxford.

Dr Amita Kapoor

Senior Tutor

Associate Professor, Department of Electronics, SRCASW, University of Delhi 

Amita Kapoor is an Associate Professor in the Department of Electronics, SRCASW, University of Delhi, and has been actively teaching neural networks and artificial intelligence for over twenty years, and she is an active member of ACM, AAAI, IEEE, and INNS.

Amita completed her masters in Electronics in 1996 and her Ph.D. in 2011.
During her Ph.D she was awarded a prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. Amita was awarded the Best Presentation Award at the Photonics 2008 international conference.

Amita has more than 50 research publications in international journals and conferences, and has co-authored four books, including the best-selling “Deep learning with TensorFlow2 and Keras” with Packt Publications.

Passionate about using her skills for the betterment of society and humankind, Amita spends her spare time in various AI-related IoT and healthcare open source projects. She was recently awarded the Intel AI Spotlight Award 2019 for her work on the early detection of Acute Myeloid Leukemia using AI.

Amita’s present research areas include Machine Learning, Artificial Intelligence, IoT, Deep Reinforcement Learning, and Robotics.

Anjali Jain

Senior Tutor

Digital Solutions Architect, Metrobank 

Anjali is a Digital Solutions Architect at Metrobank, where she helps to deliver advanced technology driven business solutions around diverse themes of Internet Banking, Mobile App, Business banking, and Open banking/PSD2, using agile methodology.

She has over 16 years of IT experience and worked across Banking, Telecom and logistics domains, from inception to the delivery of complex projects.

Anjali is passionate about AI and Machine learning and completed the course "Data science for internet of things" in February 2019 from the University of Oxford.

Paul Clarke CBE FREng

Senior Tutor

Ex-Chief Technology Officer, Ocado

In November 2020, Paul Clarke stepped down as Chief Technology Officer at Ocado, having led the sharp end of Ocado's innovation factory since early 2012.  

Paul is passionate about the recipes for successful invention, innovation and disruption, which in his experience are all about embracing non-linearity, mess, uncertainty, intersectional thinking, unconventionality, intuition and leaps of faith.
He believes building a successful innovation factory is all about the people, culture, creativity, leadership and vision rather than the underlying technologies, and he has spent much of his career being a piece of disruptive grit in a number of different oysters, trying to help people see what they can’t see and trying to inspire teams to do things they never dreamed possible.  

Paul's current focus is on enabling cyber-physical infrastructure at a national scale, woven from a blend of technologies such as data, AI, IoT, synthetic environments, digital twins and smart machines. He now sits on a number of government and industry advisory boards including the AI Council, Robotics Growth Partnership (co-chair), Innovation Expert Group, ISCF Future Flight, ISCF RAI Extreme Environments and the National Food Strategy, whilst at the same time advising a number of exciting start-ups.  

Paul read Physics at Oxford University before then entering the software industry. He has worked in software engineering, consultancy, interim management and a number of software start-ups. In what little spare time he has alongside his work and family, Paul loves to invent and build stuff, design PCBs, write software and generally tinker.

Mr Mustafa Aldemir

Course Tutor

Head of Robotics, Amazon Web Services (AWS)

Mustafa Aldemir is an experienced technology leader in the field of AI and IoT. He holds a BSc in Electronics Engineering, a MSc in Mechatronics, and he is pursuing PhD studies in Computer Science.

Mustafa previously worked as a software engineer at Siemens and ING. He delivered numerous AI & IoT workshops at universities around Europe while working as a tech lead at Intel.

He is currently working as a senior prototyping architect at AWS to develop innovative cloud solutions for leading companies around EMEA and leading the Robotics domain at AWS.

Dr Saeed Khalfan Al Dhaheri

Course Tutor

Dr. Saeed is a futurist, thought leader, author, and a public keynote speaker. He is a veteran of the UAE technology industry with over 30 years of experience in driving technology adoption in various public sector organisations. He has been in many positions: the founder and former Director General of the Emirates ID Authority, a former member of the scientific advisory committee of the UAE Space Agency, and a former Advisor to the Minister of Foreign Affairs on information technology.  

Currently, he is the director of the Center for Futures Studies at the University of Dubai, an adjunct lecturer of public policy science & technology track at the Mohammed Bin Rashid School of Government, the chairman of the board of Smartworld (a leading digital solutions provider in the UAE), President of the Digital Engineering Chapter at the UAE Society of Engineers, and a board member of the Emirates Safer Internet Society.  

He is on advisory board of well-known startups including Virtual Rehab Inc and 01Gov, and also on advisory boards of several universities in the UAE.  

He co-authored the book Digital Nation: How the UAE is building a future based on tech innovation. A first-of-its-kind book on the unique journey of the UAE to build a future based on harnessing disruptive technologies such as artificial intelligence and driving digital innovation.  

He has written several articles and reports that were published at Harvard Business Review Arabia and Dubai Policy Review Journal.  

Dr. Saeed’s main interest is in foresight and researching the impact of emerging technologies on business and society. He strives to drive futures thinking in leadership to influence shaping the future of governments and creating a better world for all.  

He was recently interviewed as a special guest with Professor Dame Wendy Hall on Brave Conversation Southampton. Dr. Saeed has earned his PhD in biomedical Engineering from Drexel University, Philadelphia, USA in 1994. 

Kence Anderson

Course Tutor

Principal Program Manager, Machine Teaching Innovation for Autonomous SystemsMicrosoft


Kence Anderson is Principal Program Manager, Machine Teaching Innovation for Autonomous Systems at Microsoft. Kence has designed over 100 autonomous decision-making AI systems for commercial uses, including at PepsiCo, Bell Flight, and Shell. Kence is the son of a master teacher and is trained in mechanical engineering, and he utilizes both aspects by researching how the principles of teaching combined with human expertise can be used to design and build useful AI. 

Jean-Jacques Bernard

Course Tutor

JJ Bernard has an MSc in Engineering from the Ecole Centrale de Marseille and an MBA from the University of Cambridge. He is also a certified Lean Six Sigma Black Belt.

He currently works at Oracle as a strategy consultant, advising client on their technology investment with regards to their business strategy.

Previously, he has worked as a project manager for Orphoz, a subsidiary of McKinsey & Company, focusing on defining and executing transformation projects.

He has worked in diverse environments such as manufacturing, FMCG, public sector, steelmaking, mining, healthcare and automative.

He has also worked for Accenture, both on business and IT transformation projects, for the financial services industry and the public sector. 

Pinckney Benedict

Course Tutor

Pinckney Benedict graduated from Princeton University, where he worked primarily with the author Joyce Carol Oates, in 1986 with a bachelor’s degree in English and from the Iowa Writers’ Workshop in 1988 with an MFA in Fiction.

He has published a novel and three collections of short fiction, the most recent of which is  Miracle Boy and Other Stories. His work has been published in, among other magazines and anthologies, Esquire, Zoetrope: All-Story, the O. Henry Award series, the Pushcart Prize series, the Best New Stories from the South series, The Ecco Anthology of Contemporary American Short Fiction, and The Oxford Book of the American Short Story.

Benedict is a professor in the MFA program at Southern Illinois University Carbondale and the founder and director of SIUC’s Digital Humanities Laboratory. 

Dr Martin-Immanuel Bittner

Course Tutor

Chief Executive Officer, Arctoris

Martin-Immanuel Bittner MD DPhil is the Chief Executive Officer of Arctoris, the world's first fully automated drug discovery platform that he co-founded in 2016. He graduated as a medical doctor from the University of Freiburg in Germany, followed by his DPhil in Oncology as a Rhodes scholar at the University of Oxford.

Dr Bittner has extensive research experience covering both clinical trials and preclinical drug discovery and is an active member of several leading cancer research organisations, including EACR, AACR, and ESTRO. In recognition of his research achievements, he was elected a member of the Young Academy of the German National Academy of Sciences in 2018.

Barend Botha

Course Tutor

Consultant, Data Visualisation

Barend Botha is a UK-based consultant working predominantly in the field of data visualisation.

He is particularly interested in the growing future potential and roles that data analytics and visualisation will play across IoT verticals in in combination with Artificial Intelligence and the resulting products and insights for business and consumers alike.

He draws upon past experience in research, design, development, management and marketing across various domains and disciplines.

Amy Boyd

Course Tutor

Senior Cloud Advocate, AI/ML, Microsoft

Amy Boyd is a Senior Cloud Advocate at Microsoft, having obtained a degree in Computer Science, completing a research project in Natural Language Processing/Machine Learning and an internship at Microsoft’s search engine, Bing.

Amy is passionate about Data Science and Machine Learning and her roles at Microsoft have allowed her to work on many different areas of data science (visualisation, ML, big data, IoT) as well as working on projects with customers across the globe.

Her role as a Senior Developer Advocate helps developers to engage with Microsoft around Microsoft Azure and specifically the Azure AI services by providing content, learnings, and sample code. You will find her sharing her content and learnings online and at in-person events.

Francesco Ciriello

Course Tutor

Lecturer in Engineering Education, King’s College London

Francesco is a Lecturer in the Department of Engineering at King’s College London, where he teaches interdisciplinary design and mechatronics. He previously worked in the Education Group at MathWorks and provided consultancy services to educators and researchers on the use of MATLAB & Simulink. Francesco has broad expertise in Simulation and Artificial Intelligence, with application to Robotics & Control systems, signal processing and IoT. He also holds a PhD in Engineering from the University of Cambridge for his work in experimental fluid dynamics and a MEng in Civil Engineering from Imperial College London. 

Alexander Denev

Course Tutor

Alexander is a former Head of AI and the Data Science team for Financial Services - Risk Advisory. His responsibilities included development of AI products and advisory around risks and ethical implementation of AI. He also focussed on Alternative Data, AI for Data Quality and AI for Retail Banking. Previously, Alexander was a former Head of Quantitative Research & Advanced Analytics at IHS Markit.  

Prior to that, Alexander has worked in Risk Dynamics (McKinsey & Company), The Royal Bank of Scotland, European Investment Bank (EIB) and European Investment Fund (EIF), National Bank of Greece and Societe Generale.  

Alexander holds a degree in Mathematical Finance from University of Oxford where he has been a Visiting Lecturer on Bayesian Risk Management and Alternative Data. He wrote several papers and books on quantitative topics, ranging from stress testing and scenario analysis to asset allocation through Machine Learning techniques and alternative data.  

Robert Dimond

Course Tutor

System Architect, Arm

Rob Dimond is System Architect and Fellow at Arm. Rob works in the Architecture and Technology group at Arm where his focus is developing technology in a 3-5 year time horizon for the infrastructure segment (servers and networking). Prior to Arm, Rob was Chief Hardware Architect at FPGA computing startup Maxeler. Rob holds degrees in Electronic Engineering and Computer Science from Imperial College, London.

Paul Foster

Course Tutor

Senior Software Engineer, Microsoft

Since joining Microsoft in 1994, Paul Foster has worked across a wide range of sectors and customers, providing a mix of technical and strategic guidance around the creative use of technology in relation to their business needs.

Paul is currently a principal software engineer at Microsoft. As an established public speaker across Europe and having spent a considerable amount of time working on the cutting edge of technology providing leadership and inspiration on topics like Smart Devices, Cloud Computing, Education and App Development.

Paul is currently focusing on the building of next generation sensor webs which automate the gathering of data from disparate sources, and how to enable the creative analysis of this data to start a new era of perception.

For a short time Paul was a member of a high-wire flying trapeze circus troupe, is a keen roboticist and an international marathon runner.

Dan Howarth

Course Tutor

Head of Services, Smartia Ltd.

Dan runs the Data Science team at Smartia, an IOT and AI start-up, where he uses data science to provide value to manufacturing companies.

He previously worked as Senior Consultant for Altran Digital, an engineering and R&D consultancy, and as a Data Scientist at Rolls-Royce, working to apply machine learning to improve manufacturing processes for high value parts.

As well as qualifications in machine learning, Dan is a Chartered Management Accountant. 

Saed Hussain

Course Tutor

Senior Data Scientist, HomeServe (

Dr Saed Hussain has a PhD in applied AI in defence, which was sponsored by BAE Military Air and Information.

After a few years of contributing to the UK government and military innovation projects, he has moved on to commercial sector AI projects.

Currently, he is leading the machine learning capability development at Leakbot, an arm of the HomeServe group.

Besides his interest in AI, he is passionate about IoT and blockchain technologies. 

Dr Ghida Ibrahim

Course Tutor

Technical Lead & Senior Quantitative Engineer, Facebook

Ghida is a technical lead & senior quantitative engineer in the infrastructure team at Facebook London, where she drives cross-functional efforts around leveraging automation and data science to help scale and optimize Facebook massive infrastructure. In this context, she co-leads an effort around deploying and operating a more product-aware infra, and was recognized as an outstanding contributor to keeping Facebook infra stable in the wake of COVID19-induced demand explosion on Facebook family of apps. Prior to joining Facebook, Ghida worked for 6+ years in the Telco and media industries, in France and the Netherlands in multiple analytics and engineering roles, mainly focusing on capacity scaling and performance optimization of large-scale distributed systems. She holds a PhD and master’s (Diplome d’Ingénieur) in computer engineering from Telecom ParisTech, France top Grande Ecole in ICT. She got her PhD at 26.

In addition to her job, Ghida built Rafiqi, an award-winning platform that leverages artificial intelligence (AI) for connecting refugees to life opportunities. She is a data science trainer who delivered in-person workshops on data science and machine learning to hundreds of domain outsiders, and prepared and delivered the first MOOC on data science in Arabic attracting 27k+ learners. She is an appointed member of the World Economic Forum (WEF) Global Future Councils since 2016, a member of the WEF expert Network, and a WEF Global Shaper who served as a co-curator of the Oxford Hub.

Ghida is a TED speaker and has delivered dozens of lectures and technical talks in academic and industry settings. She also served as an advisor and board member of many NGOs working on bringing more minorities into tech. Ghida has multiple patents and academic publications to her name, and occasionally contributes to technology blogs and to the World Economic Forum Agenda. Most recently, she was recognized as a Franco-British Young Leader, among 20 other leaders from the UK and France including MPs, reputed scientists and artists, in charge of fostering relationships between France and the UK and shaping its future across sectors of society and economy.

Cynthia Joachimpillai

Course Tutor

Manager, Verizon 5G London Lab

Cynthia manages Verizon’s 5G London Lab and works closely with senior stakeholders of FTSE 100 companies to identify and solve business challenges through the use of 5G and multi access edge compute. She previously worked for Verizon’s Innovation Lab based in Waltham, MA and San Francisco, CA in a similar capacity, primarily focused on IoT and applications of the future as the standards for 5G were being tested and developed. 

Cynthia holds a Bachelor’s degree in Child Advocacy and family policy from the University of New Hampshire.

Bojan Komazec

Course Tutor

Senior Software Engineer, Avast Software

Bojan Komazec has been working in IT industry for over 15 years. He currently holds the position of Senior Software Engineer in Avast Software where he develops various security and privacy products.

Bojan's interests span from code craftsmanship and cyber security to Artificial Intelligence and Internet of Things. He is an active blogger and speaker at several IT Meetup groups where he enjoys sharing experience and knowledge.

Bojan studied Electrical Engineering and Telecommunications and in 2004 received master's degree from University of Novi Sad, Serbia.

Jakub Langr

Course Tutor

Co-Founder, Hypermile AI

Jakub Langr is the Co-Founder of Hypermile (Y Combinator S20). Jakub graduated from the University of Oxford and started his career in machine learning in 2013. He was previously working at Mudano (acquired by Accenture), where he grew the machine learning team from just himself to 15 people, and Founders Factory leading ML and computer vision teams. He was the lead author of the best-selling book GANs in Action: Deep Learning with Generative Adversarial Networks (Manning Publications, 2019) and is a well-known speaker/author on generative AI (Forbes, PyData, AI EXPO etc).

Laurence Moroney

Course Tutor

Laurence Moroney leads AI Advocacy at Google, working with the Google AI Research and product development teams. He's the best-selling author of 'AI and Machine Learning for Coders,' as well as the instructor on the Fundamentals of TinyML course at HarvardX, and the popular TensorFlow specializations with and Coursera.

He's passionate about empowering software developers to succeed in Machine Learning, democratizing AI as a result. Laurence is based on Washington State in the USA. 

Philip Osborne

Course Tutor

University of Manchester 

Philip is a doctoral student currently studying Artificial Intelligence at the University of Manchester with a Masters Degree in Data Science and Bachelors Degree in Mathematics. The primary focus of his research relates to the application of Reinforcement Learning to Real-World Tasks with the integration of Natural Language.

Philip first applied Reinforcement Learning in a commercial environment with his Master's dissertation to recommend the order and design of data visualisations for client presentations within an insurance consulting business.

Since then, he has demonstrated some of his other ideas publicly including meal planning and recommending strategy decisions within a popular video game. The public demonstrations have gained notoriety within the data science community, including two separate monetary awards from Kaggle (Google) for their novelty, and has put him at the forefront of the field. 

Maria Pocovi

Course Tutor

CEO and founder, Emotion Research Lab

Maria Pocovi is CEO and founder of Emotion Research Lab, a computer vision company which explores how machines understand human emotions. Since 2014 the company has provided facial emotion recognition algorithms with on-line and on-premises solutions for real time applications. Emotion Research Lab has been acquired by Uniphore.

Maria is passionate about human technology interaction and the process of bringing new applications to the market which help companies empower emotional sensing on devices to prepare brands to provide the next generation of services, products and experiences to their customers.

Maria graduated in Marketing and Business Administration from ESIC University, has an MBA from Catholic University in Valencia and an MBE from European University of Madrid.

Hamaad Shah

Course Tutor

Vice President, Columbia Threadneedle Investments

Hamaad is a senior data scientist with expertise and experience in machine learning and quantitative analytics applied to banking and insurance.

He has extensive expertise in deep learning, Bayesian inference and Natural Language Processing (NLP), etc., applied to various financial services use cases such as Asset Liability Management (ALM), actuarial pricing, trader surveillance, etc.

Hamaad holds an MSc in Applicable Mathematics from the London School of Economics and Political Science (LSE) and a BSc in Economics from the University of Manchester. He also has first time passes for the CFA levels 1 and 2 exams with level 3 to be attempted in due course.

Kajal Singh

Course Tutor

Kajal is a Machine Learning Engineer working with Machine Learning and AI projects for a large global consultancy.

She has worked on use cases like anomaly detection, sentiment analysis, classification, transactional AI assistants, complex big data processing, data analytics, document digitisation etc. Kajal also has been a part of multiple hackathons conducted within and across IT industries.

She is also awarded with Amazon Pride Card for her research contribution to “Women In AI” project of IIIT, Bangalore

She has won special recognition for her project 'Transactional AI assistant'. She also has been honoured as 'Master Hacker' in Makeathon at a regional level in India.

Kajal has also been leading a research project (non-commercial) working with a German company on pricing optimization using Reinforcement Learning (RL). 

Her project involves working on RL on pricing optimisation strategy for revenue increase and customer retention using a mixture of algorithms based on Markov Decision Processes (MDP).

Dr Matthew Taylor

Course Tutor

Associate Professor of Computing Science, University of Alberta 

Matthew (Matt) E. Taylor focuses his research on developing intelligent agents, physical or virtual entities that interact with their environments. His main goals are to enable individual agents, and teams of agents, to learn tasks in real-world environments that are not fully known when the agents are designed; to perform multiple tasks, rather than just a single task; and to robustly coordinate with, and reason about, other agents.

Additionally, he is interested in exploring how agents can learn from humans, whether the human is explicitly teaching the agent, the agent is passively observing the human, or the agent is actively cooperating with the human on a task.

Current approaches that his teams are investigating include working on improving reinforcement learning through demonstrations, teaching reinforcement learning systems through action advice, and training agents with discrete human feedback.

Matt is an Associate Professor of Computing Science at the University of Alberta and a Fellow and Fellow-in-Residence at Amii. He is the Director of the Intelligent Robot Learning (IRL) Lab and a Principal Investigator at the Reinforcement Learning & Artificial Intelligence (RLAI) Lab, both at the University of Alberta.

Matt is also Adjunct Professor at Washington State University and was formerly the Principal Researcher at Borealis AI in Edmonton, the artificial intelligence research lab for the Royal Bank of Canada.

He has been a PI or co-PI on over $6M USD in competitively awarded research funding from federal, state, and industrial sources, including the National Science Foundation CAREER award. He has (co-)supervised seven graduated PhD students and six graduated MS students, as well as published over 100 peer-reviewed papers in conferences and journals.

He has delivered invited talks for the Association for the Advancement of Artificial Intelligence (AAAI) and at the International Joint Conference on Artificial Intelligence (IJCAI).

Tugce Yalcin

Course Tutor

Senior Consultant, DLA Piper 

Tugce is Senior Consultant in the M&A/Corporate practice of DLA Piper (London/Vienna) and Head of its "Austria-China-Desk", having obtained degrees in law, political science and the bilingual (German and English) Master's Programme in European Union Studies.

She advises national and international clients on cross-border M&A and financial transactions as well as corporate restructurings and has been working with technology companies as part of her work ranging from a number of areas such as acquisitions of leading AI/ICO companies. Tugce regularly publishes on Foreign Direct Investment (FDI) in M&A transactions in peer-reviewed journals and is currently working on a survey paper for AI and Intellectual Property Rights covering industries such as bioinformatics and cybersecurity.

Tugce passed the Austrian Bar Exam with summa cum laude. Tugce is also a Visiting Researcher at the University of Oxford and a PhD student at the University of London where she also edits the Student Law Review, and is also the Editorial Board Member of the journal The Company Lawyer (Sweet & Maxwell / Thomson Reuters).

Mr Jan Zawadzki

Course Tutor

Head of Artificial Intelligence, CARIAD SE

Jan Zawadzki is the Head of Artificial Intelligence at CARIAD SE, Volkswagen Group's central software development unit. With its 4,000 employees and goal to ramp up to 10,000 until 2025, CARIAD SE will become Europe’s second largest software company behind SAP. AI plays an integral role in CARIAD’s mission to developing the VW.OS, which will power VW Group vehicles in the future. Jan is also an experienced global Management Consultant and Data Scientist. He has a BA in Business Administration from Goshen College, IN, USA, a M.Sc. in Computer Science from Trier University of Applied Sciences, Germany, and currently studies towards his Part-time MBA from ESMT Berlin. Jan is passionate about advancing the automotive industry through machine learning and sharing his knowledge in the fields of Project Management and AI. He is a top contributor to the “Towards Data Science” Publication on Medium and enjoys supporting the team around Deep Learning Luminary Andrew Ng.

Sumaya Al Hajeri

Course Tutor

Sumaya Al Hajeri is a professional in the field of Technology, Telecommunication and Outer Space regulations with 14 years of experience. She is currently heading the Governance and Data section at the AI office in the Prime Minister Office. She was assigned the responsibilities of implementing the AI National Strategy through rolling out a number of policies, strategies and initiatives. Moreover, she was the Head of Space Policies and Regulations at the UAE Space Agency and contributed towards achieving several projects such as: the UAE participation at the UN Committee of the Peaceful Uses of Outer Space (COPUOS) and the UN Office of Outer Space Affairs, the Federal law No (12) of 2019 regarding the regulation of the UAE Space Sector and other related strategies and policies.

Sumaya worked at the Telecommunication Regulatory Authority since 2007 as a Radio Planning Engineer where she developed the National Spectrum Plan as per the outcomes of the World Radiocommunication Conferences by the International Telecommunication Union. She also served as a consultant in Spectrum Management for UAE armed forces. In 2012, she was involved in the Telecommunication Competition Regulations and Licensing and contributed towards: licensing major space telecom operators in the UAE and development of the Universal Service Obligation Policy. She graduated from the Future Foresight Program in 2018, and developed a future foresight scenario of Space Accessibility based on international legislations and R&D uncertainties. Also, arranging several Future Foresight workshops with international organizations, in which the most recent one is the International Space University (ISU) in Strasbourg – France.

Sumaya is a holder of a bachelor in Communication and Electronics Engineering 2007 from UAE University, and two Masters: International Law, Diplomacy and International Relations 2011 from Paris Sorbonne University and a Master in Public Policy (Science, Technology and Innovation) from Mohamed Bin Rashid School of Government.

Sumaya has a number of professional and academic contributions in the field of: Competition regulations, competitiveness, Industry and Technology Cluster Policies, Smart Specialization Policies, Microeconomic Cluster Mapping tool, women in ICT as part of the ITU agenda, Women in Space as part of the UNOOSA agenda, increasing Emirati women participation in the workforce, Space Policies and Strategies.

Mr John Alexander

Course Tutor

John Alexander is a Sr. Machine Teaching Advocate on the Microsoft Project Bonsai team. 
He sat in Kirk's Chair on the bridge, recorded cartoon pilots as part of a voice ensemble cast, is the co-creator of the "Geek" t-shirt (found at most Microsoft conferences), and was Facebook friends with Patrick Swayze.

John has a passion for designing and building accessible experiences using AI coupled with vision, voice, touch, and virtual/mixed reality.

In a previous life, he was the co-founder of a digital agency and consultancy, and also had the honor of being a Microsoft regional director for 19 years.

In the previous, previous life before that, John co-founded the largest technical blogging community in the world, Geekswithblogs.Net, before selling it several years ago.
He also built music chart applications for Billboard Magazine used by "American Top 40", and architected a highly scalable Mutual Funds Trading SOA-based platform used non-stop the last 18 years to process billions of dollars in transactions.

A trainer since 1996, with 26 Microsoft product certifications, John has coached several teams of developers, leading one directly responsible for earning their organization a spot on CIO Magazine’s “Agile 100” list.
He’s co-authored three best-selling technical books, Microsoft Official Curriculum and co-hosted two technical focused podcasts.

Based in Kansas City, Missouri USA, John loves to paint, draw, game, do voiceovers, and spend time with his spouse and three children on all sorts of adventures.

Roy Allela

Course Tutor

Roy Allela is a Senior Deep Learning Software Engineer within the Developer Relations team at Intel.
He currently works on Intel optimized frameworks for Deep Learning and the OpenVINO toolkit.

Roy has a background in Microprocessor Engineering from The University of Nairobi. He has worked on several AI and IoT projects, notably Sign-IO that earned him a Royal Academy of Engineering LIF Fellowship and ASME recognition.

He is passionate about developer advocacy and moonshot projects

Matthew Berrick

Course Tutor

Matthew Berrick is an author with experience working in various law firms and will become a solicitor at Pinsent Masons.

Matthew has had both legal and non-legal experiences ranging from working in the House of Commons and at the United States Congress in Washington D.C. to working at law firms based in the U.K. and San Francisco. Matthew published his book - Legal Insider - which was mentioned in the 2020 Innovative Lawyers series of the Financial Times and cited by a New York Times best-selling author. The book focuses on various aspects of a career in law as well as delving into legal tech by featuring experts/professionals working at law firms and in house companies such as Uber, Arsenal and the BBC.

Paul DeCarlo

Course Tutor

Paul DeCarlo is a Principal Cloud Developer Advocate for Microsoft and Professor for the Bauer College of Business at the University of Houston.  His current technology interests focus on Internet of Things, Artificial Intelligence, and Edge-to-Cloud Applications.  He is an experienced start-up founder for WinCoder LLC ( ).  During time off, he enjoys taking care of his thirteen trees, riding mountain bikes, and taking care of his dog – Chief and cat – Kitty.

Bas Geerdink

Course Tutor

Bas is a technology leader in the AI and big data domain. His academic background is in Artificial Intelligence and Informatics. Trained as a software engineer and architect, he has 15 years’ experience in delivering successful data-driven projects with a wide range of companies and technologies. He is a regular speaker on conferences and co-authored two books on data engineering. 

Dr Julia Hoerner

Course Tutor

Dr Julia Hoerner is the AI Academic Liaison Manager at MathWorks in Cambridge, UK.
She supports members of European universities in all AI-related aspects in MATLAB.

Julia has a background in engineering, renewable energy, and energy forecasting. After her PhD at the University of Hull on Offshore Wind Energy, Julia worked on energy forecasting using deep learning at the University of Reading and University of Strathclyde.

Prof Nilesh Nalawade

Course Tutor

Prof. Nilesh Nalawade currently serves as the CEO of Agricultural Development Trust Baramati, one of India’s premier agricultural research and development organizations which is also the parent organization of Krishi Vigyan Kendra Baramati, India’s national and international award winning farm science centre.  

Prof. Nalawade completed his post-graduate studies in animal sciences at the Wageningen University, Netherlands.  

He has a rich and varied experience in conceptualization and development of various successful bilateral initiatives such as starting the first international undergraduate programme at Baramati, India, in the agriculture sector in collaboration with Van Hall Larenstein University in the Netherlands, setting up of the Indo-Dutch Centre of Excellence for Vegetables, setting up of Centre of Excellence for Animal Genetic Improvement, etc.  

He has a natural affinity for technology and innovation and has implemented his ideas in these spaces by leading the setting up of the Atal Incubation Center ADT Baramati Foundation, India’s largest Innovation and Incubation Centre, where he mentors over 30 of the brightest start-ups and many more aspiring entrepreneurs and innovators from across India.  

He has received various national and international awards for his work such as the prestigious Rastriya Vidya Saraswati Pursaskar. He has also published multiple high-impact, peer reviewed research papers in the agriculture and animal sciences sectors and held a position as a Member of the Management Committee  of National Institute of Abiotic Stress Management Baramati. 

Mr Sarang Nerkar

Course Tutor

Founder and CEO  

Innosapien Agro Technologies  

Sarang Nerkar is an electrical and computer engineer from the University of Toronto, Canada. His research centers around wearable computing, augmented reality, artificial intelligence and computational photography.  

For over 3 years he served as a research scientist with Professor Steve Mann (also known as the “Father of Wearable Computing”) at the Humanistic Intelligence Lab, University of Toronto. Based on his research he has developed novel modular augmented reality eyeglasses, smart time-lapse cameras and various other wearable computing, augmented reality, computational photography and machine learning platforms. His work has resulted in various peer reviewed research publications, trade secrets and multiple patent filings. The focus of his work has been public sector application of these novel technologies via Innosapien Agro Technologies, a startup he founded.  

He also currently serves as the Climate Ambassador for India at the World Bank Group’s Global Youth Climate Network. His published work and products have received multiple accolades including the Gandhian Young Technological Innovation Award presented by the Honorable President of India, Zee Yuva Sanmaan, Top Innovator Award by World Bank Ag Observatory and Most Futuristic Award in Japan among others. His work was exhibited at the Presidential Palace in India for 6 days at the Festival of Innovation and Entrepreneurship.  

He has been invited to present his work at various prestigious forums such as Defence Expo 2020 (Lucknow), Army Commanders Conference 2020 & 2019 (Delhi), Aero India 2019 (Bangalore), Viva Tech 2019 (Paris), ACM SIGGRAPH 2018 (Vancouver), ACM Tangible Embedded & Embodied Interactions 2017 (his work won the “Most Futuristic Award” at this conference in Japan), ACM International Symposium on Wearable Computers 2017 (Hawaii), Hello Tomorrow 2017 (Korea), Asian Leaders Conference 2017 (Korea), Mobile World Congress 2017 (Barcelona), Consumer Electronics Show (Las Vegas), Canadian National Exhibition 2016 (Toronto), etc. He has been interviewed many times, including by Through the Wormhole with Morgan Freeman (Discovery Science Channel), Zhejiang Provincial News (China), etc. for his work. 

Peter Piatetsky

Course Tutor

Peter Piatetsky leads strategy, growth and product design at Castellum.AI, working closely with clients to achieve risk-aligned coverage for all of their compliance needs. Prior to co-founding Castellum.AI, he served at the US Treasury Department in multiple roles, including as Senior Policy Advisor, advising the President, Treasury Secretary and other principals on sanctions, anti-money laundering and terrorist financing. Peter was detailed to the Financial Action Task Force, representing the US as an assessor for the mutual evaluation of Bahrain.

Following Treasury, Peter held a leadership role at Woori, one of Korea's largest banks, supervising all of its financial crimes compliance in the US and advising the Chief Compliance Officer. As part of that role, he led the bank's compliance technology efforts, including model validations, data integrity audits, and the RFP process for screening system and data vendor selection and replacement. He speaks regularly at industry conferences and is an Adjunct Professorial Lecturer at American University.

Ben Scott-Robinson

Course Tutor

Rikesh Shah

Course Tutor

Rikesh leads Transport for London’s award winning market innovation activity to create new value for London by working with start-ups, corporates, academia, accelerators and venture capitalists. He was responsible for creating TfL’s first Innovation Hub which has delivered some pioneering projects. The Hub sets out the organisation’s key challenges and problem statements, bringing in the best innovators from across the world, piloting and scaling innovative solutions with the potential to commercialise, as well as establishing the right culture in the company focusing on agility and design thinking to work with market innovators who either have a new mobility product or an innovative idea to help solve an existing city challenge through new technologies by doing things better, quicker or cheaper.

Rikesh was previously responsible for TfL’s world leading open data programme which has 17,000 registered users, 700 apps powered by TfL data used by 42% of Londoners which an independent review stated that it’s worth to London is £130m per annum. He also was actively involved during the 2012 Olympic Games and TfL’s response to COVID-19.

Most recently, Rikesh has been recognised in the Top 100 Asian Stars in UK Tech in 2019 and 2020, being named one of the top five for sustainability.

Rikesh also sits on the Smart London Board to deliver the Mayor of London’s vision to make London the smartest city in the world, as well as sitting as a Non-Executive Director at the London Transport Museum on the Enterprise Board. He also sits on the Advisory Board for Nitrous and Citytech Collaborative in Chicago. In academia, he Co-Chairs the Institute of Civil Engineering Data and Digital Advisory Board as well as Guest Lecturing on Open Innovation at the Royal College of Arts.

Julian Vasilkoski

Course Tutor

Julian Vasilkoski leads the technological interests that drive research and development at Castellum.AI. With a background in physics he's applied his analytical skills across multiple industries including medical research, finance, and currently regulatory data and compliance.

Prior to co-founding Castellum.AI, Julian led numerous projects on the financial engineering team at Virtu Financial where he worked on several products that would ultimately drive trading decisions at some of the largest money management firms on Wall St. The products he's been involved with include trading cost models, fair value, a regulatory requirement for mutual funds, as well as numerous stand-alone analytics that power high-touch and algorithmic trading. As part of a small team he's worked with data vendors on building data pipelines for global market data across multiple asset classes, he's worked with data scientists on developing core analytics, and he's worked with developers to bring these products from inception to production.


How to apply for this course

1. Please complete the application questionnaire to give us a sense of your knowledge and experience. 

Important: We do not expect you to have knowledge or experience in all of the areas on this questionnaire!

2. If, after the academic panel have reviewed your questionnaire, you are invited to apply for the course, we will contact you regarding payment of the course fee.


Note that we accept applicants on a rolling basis and expect this course to be oversubscribed. Places will only be confirmed upon receipt of payment.

Fees include all course materials and tuition.

Course fees are VAT exempt.

IT requirements

This course is delivered online using Microsoft Teams. You will be required to follow and implement the instructions we send you to fully access Microsoft Teams on the University of Oxford's secure IT network.

This course is delivered online; to participate you will need regular access to the Internet and a computer meeting our recommended Minimum computer specification.

It is advised to use headphones with working speakers and microphone.