Artificial Intelligence: Cloud and Edge Implementations (online)


Artificial Intelligence: Cloud and Edge Implementations is a pioneering online course covering artificial intelligence (AI), machine learning and DevOps (MLOps), cloud computing, and edge computing. 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 Al. Previous students have gone on to start or progress their AI careers. 

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

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. In this course, we refer to AI as: encompassing machine learning, deep learning (DL), and the evolution of algorithms such as transformers and large language models.  

This is an industry course, rather than an academic one, focusing on skills-based and commercial products.

Helping you transition your career towards Artificial Intelligence 

The philosophy of the course is based on helping you transition your career to AI. In this context, we use the term Al to mean deploying machine learning and deep learning in a production environment - considering both advanced algorithms and MLOps. 

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

Past students have used this aspect of the course to move their careers into Al. The course provides you with skills in cloud programming (Azure, AWS, and Google), Python development (TensorFlow and Keras), MLOps, and Edge (loT). You will begin coding exercises in the second session, and will continue to code throughout the course. After the completion of the course, you will have an extra month 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 Al.

Programme details

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

1. Foundations track 

  • Machine Learning principles 

  • Deep Learning principles 

  • Foundations of Edge computing 

  • Full Stack development (in context of Al) 

  • Machine learning and DevOps (MLOps) 

  • Cloud-native development 

  • Cloud architecture for AI 

  • Big Data architecture for AI 

2. 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: 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 - Principal Component Analysis and K-means), xgboost; Introduction to Pytorch.         

​3. 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 Microsoft Azure cloud

4. 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 

  • Generative adversarial networks (GANs) 

  • Bayesian approaches to machine learning and deep learning 

  • Reinforcement learning (RL) 

  • Probabilistic machine learning 

  • GPT-3, large language models and foundation models 

  • Anthos and hybrid cloud 

  • Transformers 

  • Time series

​5. 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, Microsoft Azure, and Amazon Web Services (AWS) platforms 

  • Time series development 

  • Industrial and autonomous systems (AS)  

  • Embedded Al (Intel, ARM platforms, Nvidia) 

  • Computer vision 

  • Signal processing 

6. Industry insights track  

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

  • 5G 

  • Affective computing - Al and emotions 

  • Robotics 

  • AI ethics, policy and responsible AI 

 7. Development and projects 

Spanning across all 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  

  • loT / time series models 

  • Digital twins  

  • Transport for London (TFL) innovation project with transport for London data 

 8. Ecosystem track 

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

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

  • Al innovation and policy 

  • Synthetic data generation and privacy for AI 

  • Design and user experience (UX) for AI 

  • AI, augmented reality (AR) and agricultural technology (Agtech) 

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 - Al, ML, edge, cloud architectures, maths of AI 

  • Ayse Mutlu - ML/DL algorithms, Microsoft Azure, responsibility of all development sprints 

 Cloud: Amazon Web Services  

​Cloud: Azure Microsoft Azure  

 Cloud - Google Cloud Platform 

Python development for AI - core algorithms  

 Advanced algorithms  

loT Edge 

Industry experiences and innovation 


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, UK time)

  • 18 and 25 November 2023
  • 2, 9 and 16 December 2023
  • 6, 13, 20 and 27 January 2024
  • 3, 10 and 17 February 2024

Tuesday sessions:

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

  • 21 and 28 November 2023
  • 5, 12 and 19 December 2023
  • 9, 16, 23 and 30 January 2024
  • 6, 13 and 20 February 2024

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) £3295.00


The tutors listed below may be subject to change.

Ajit Jaokar

Course Director and Tutor

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

Ajit is the Course Director and/or tutor for Continuing Education’s portfolio of artificial intelligence courses for professionals:

Ajit is also a Visiting Fellow in the Department of Engineering Science here at the University of Oxford.

He also 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).

Dr Amita Kapoor

Senior Course 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 Course 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.

Ms Ayşe Mutlu

Senior Course 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 Course 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.

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.

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.

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. 

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.

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

Kence Anderson

Course Tutor

Principal Program Manager, Machine Teaching Innovation for Autonomous Systems, Microsoft

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. 

Benjamin Auffarth

Course Tutor

Ben Auffarth is a full-stack data scientist who has more than 15 years of work experience.

With a background and Ph.D. in computational and cognitive neuroscience from one of Europe's top engineering universities, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds of thousands of transactions per day, and trained neural networks on millions of text documents.

In his work, he often notices a lack of appreciation for the importance of time-related factors, a deficit he wanted to address in this book. He co-founded and is the former president of Data Science Speakers, London.

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. 

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. 

Ruchi Bhatia

Course Tutor

Ruchi Bhatia is a Computer Engineering graduate from India and is currently pursuing her Master’s degree at Carnegie Mellon University.

She is the youngest 3x Kaggle Grandmaster in the Notebooks, Datasets, and Discussion category and one of the 21 Data Science Global Ambassadors at Z by HP.

Her passion lies in utilizing data-driven techniques in conjunction with a sound knowledge of business processes to drive meaningful insights and impact.

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.

Dr 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. 

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.

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.

Efe Erdem

Course Tutor

Efe Erdem has been the Executive Director of MEXT Technology Center at MESS (Turkish Employers’ Association of Metal Industries) since December 2018. He led the establishment of the Technology Center from concept phase to operationalization. The Center is focusing on the digital transformation of the industry by providing companies with a comprehensive up-skilling program, technical advisory services, access to a state-of-the-art Digital Factory and an extensive ecosystem of partners including technology companies, universities, and start-ups. At the same time, he is managing the WEF (World Economic Forum) Affiliate Center for Fourth Industrial Revolution in Turkey, which acts as a public-private collaboration platform for technology governance.

In addition, he is currently leading the ‘New Generation Industry’ Working Group at TÜSİAD (Turkish Industry & Business Association).Prior to this, he was Head of Innovation at Ford Otosan and led all company initiatives regarding corporate entrepreneurship and open innovation. In that capacity, he was also a member of the company’s Executive Committee. Previously, he held various roles in Product Development such as Commercial Vehicles Program Management and Powertrain Systems Integration in Turkey and the UK, as well as Manufacturing Engineering. He graduated from Industrial Engineering Department of Boğaziçi University, Istanbul and holds a Master’s degree in Management Sciences from London School of Economics (LSE).

Dr Teresa Escrig

Course Tutor

Principal Project Manager, Microsoft Autonomous AI 

Dr Teresa Escrig is a principal project manager at Microsoft Autonomous AI, evangelizing Machine Teaching. In her prior role at Microsoft Consulting Services she was leading the Responsible AI initiative.  

Dr Escrig started her career in academia where she gained her PhD in AI / Qualitative Modeling applied to Service Robotics, was the lead of the research group “Cognition for Robotics Research”, published 100+ peer review research articles, 3 books and was the PI of several research projects. She founded of a couple of startups in the AI field, where she led the development of several products from ideation to delivery, including IP protection in different fields of applications, from service robotics, to cyber security, DNA sequencing, computer vision, and edge computing.  

Dr Escrig was the AI global lead on Cognitive Computer and Computer Vision at Accenture, where she led the development of a module to provide transparency to Autonomous Vehicles (patent pending) and contributed to the patent to discover bias in ML algorithms. She recently published “Safe AI – A blueprint for executives to harness the benefits of AI without the unintended consequences.”  

Her key message to attain responsible AI is through integration of AI technologies, which is what she is working on now with the Autonomous AI group.  

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. 

Mr Antonio Gulli

Course Tutor

Office of the CTO, Google Cloud 

Antonio has a passion for establishing and managing global technological talent, for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, he serves as Eng. Director for the Office of the CTO, Google Cloud. Previously, he served as Google Warsaw Site leader, doubling the size of the engineering site.

So far, Antonio has been lucky enough to obtain professional experience in 4 countries in Europe and has managed teams in 6 countries in EMEA and U.S: In Amsterdam, as Vice President for Elsevier, a leading scientific publisher; in London, as Engineering Site Lead for Microsoft working on Bing, Search; in Italy and U.K, as CTO, Europe and UK for; and in several co-funded start-ups including one of the first web search companies in Europe.  

Antonio has co-invented a number of technologies for search, smart energy, and AI, with 20+ patents issued/applied, and he has published several books about coding and machine learning, also translated into Japanese, Russian, Korean and Chinese. Antonio speaks Spanish, English, Italian, and he is currently learning Polish and French. Antonio is a proud father of 2 boys, Lorenzo, 19, Leonardo, 14, and a little queen Aurora, 10 years. We all share a passion for inventions.

Satish Gupta

Course Tutor

Satish Chandra Gupta is a Data and Machine Learning practitioner. He has been building and deploying data pipelines and ML services for over 6 years. He shares his learnings in the Machine Learning for Developers (ML4Devs) newsletter.

In his past life, he built microservices, compilers, developer tools, and IDEs for 15 years at Amazon, Microsoft Research, and IBM. 

He received a B.Tech. at the Indian Institute of Technology, Kanpur and an M.S. at the University of Wisconsin-Milwaukee.

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. 

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.

Emily Jones

Course Tutor

Emily is a Senior Data Scientist at QuantumBlack, AI by McKinsey, where she has been working since November 2019. She has helped clients in various industries to unlock the power of AI in their organisations. Emily has a passion for Fairness in AI and has been involved in R&D work at QuantumBlack in both fairness and causal AI. ​

Before QuantumBlack, Emily studied Mathematics at Durham University followed by an MSc in Machine Learning at UCL. She wrote her MSc thesis on time series distribution prediction using Deep Learning methods. 

Dr Kaouter Karboub

Course Tutor

Dr Kaouter KARBOUB is an assistant professor of computer ccience and artificial intelligence at the Moroccan Institute of Engineering Sciences. She received her PhD degree in Microelectronics and Computer Sciences: Internet of Things and Artificial Intelligence from Lorraine University-France.

She also holds an Engineering degree in Industrial Engineering and Logistic Operations from the High School of Electric and Mechanical Engineering in Morocco. She got High Honor degree for her dissertation “Contribution to improving medical care services using IoT and AI”.

She leads many non-profit associations to help women in the African world be involved in domains like AI for healthcare and education in cooperation with universities.

She is interested in intelligent systems that operate in large, nondeterministic, nonstationary or only partially known domains.
She believes that finding good solutions to these problems requires approaches that cut across many
different fields and, consequently, her research draws on areas such as artificial intelligence, decision theory, and operations research.

Dr Kaouter has been working with Ayse Mutlu and Fabrizio Romano to implement systems for test driven
development for artificial intelligence in python.

Emre Kiciman

Course Tutor

Senior Principal Researcher, Microsoft Research 

Emre Kiciman is a Senior Principal Researcher at Microsoft Research, where his research interests span causal inference, machine learning, and AI’s implications for people and society.   

Emre is a co-founder of the DoWhy library for causal machine learning.  He received his PhD in Computer Science from Stanford University. 

Mr Matt Kirk

Course Tutor

Matt Kirk has been many things: a data scientist, software engineer, financial quant, co-founder, c-level executive, and so on. He is currently a principal machine learning scientist at Zeitworks, which is a startup focused on empowering knowledge workers using ML. His role at Zeitworks is to lead a data team and use machine learning to make the business process more streamlined.

Matt also has a deep passion for teaching machine learning. For years he has taught classes on machine learning with O'Reilly and is a published author (Thoughtful Machine Learning with Python). His focus has been encouraging students to grow through effective scaffolds and learning methods. He concentrated on education technology and machine learning during his master's program at the Georgia Institute of Technology.

Besides teaching, Matt has focused his learning and growth on edge computing of machine learning models. For instance, he has built tooling used to deploy image models and tabular models inside the browser on top of web assembly using Rust. In addition he has helped pharmaceutical companies detect drug abuse quickly at scale.

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. 

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. 

Eickhel Mendoza

Course Tutor

Eickhel Mendoza is a Microsoft Business Applications MVP with many years of experience in project management, Microsoft Azure development, and Microsoft Power Platform technologies. He is also the author of the book, Microsoft Power Apps Cookbook.

He is a team lead of the Business Apps department and oversees all Microsoft 365 and Power Platform projects. He has contributed to significant community events such as the Power Platform World Tour, Global Azure Bootcamp, Microsoft 365 Developer Bootcamp, and Dynamics 365 Saturdays.

He coordinates the TenerifeDev and Power Platform Canarias user groups with a group of like-minded developers eager to share their knowledge in different technologies. Eickhel is also a member of the organizing committee of the Business Applications Summit Spain.

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. 

Christoffer Noring

Course Tutor

Senior Cloud Advocate, Microsoft 

Chris is Senior Cloud Advocate at Microsoft with more than 15 years in the IT industry.  He's a published author on several books about web development as well as the Go language.  He's also a recognized speaker as well as keynote speaker and holds a Google developer expert title.   

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.

Warren B. Powell

Course Tutor

Mr Fabrizio Romano

Course Tutor

Fabrizio Romano was born in Italy in 1975. He holds a Master’s Degree in Computer Science Engineering from the University of Padova. He lived in London from 2011 to 2021, and now resides in Whitley Bay.

In the past ten years, he has delivered talks about software engineering, testing, and the Python programming language, at conferences such as EuroPython, Skills Matter, and ProgSCon. He is an advocate of modern software engineering practices such as Agile and Extreme Programming. He is a certified Scrum and Kanban master.

Since 2016, he has worked as principal software engineer at Sohonet, in London. In 2020 his team was honoured with an Engineering Emmy Award from the Television Academy, for advancing remote collaboration. They were also honoured by HPA for Engineering Excellence in the 2020 HPA Awards and, in 2021, they won a Lumiere Award from the Advanced Imaging Society.

Fabrizio is the author of the top-selling book Learn Python Programming, 3rd edition – Packt, 2021. He has been teaching Python to students all around the world since 2012. He is also a meditation and Reiki teacher.

Giulia Romei

Course Tutor

Giulia is a Computational Linguist. She holds a Master's degree in Linguistics from Ca’ Foscari University of Venice, where she focused on theoretical linguistics, generative grammar, philology and cognitive linguistics, and started specializing in computational linguistics. After completing her studies Giulia moved to London where she has been working as a Document Automation Specialist at WallStreetDocs for over 2 years.

At WallStreetDocs, Giulia started specializing in coding and working as a PHP developer, and she’s currently involved in researching AI applications for document automation, translation and data extraction. She divides her time between London and Italy, where she manages the Italian team of Document Automation Specialists.

Her personal interests and research focus on Cognitive Linguistics and Neurolinguistics (specifically AI applications in the analysis of the cognitive activity involved in language processing, with a focus on syntactic processing within the framework of generative grammar, and categorization, diagnosis and treatment of language disorders) and Computational Philology.

She is implementing these models in Python and GPT-3 in applications that need multimodal analysis.

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.

Kajal Singh

Course Tutor

Kajal is a Senior Data Scientist/Engineer working with Data ETL pipelines and AI projects for a large Sports-tech company.

She is a co-author of the book Applying Reinforcement Learning on Real-World Data with Practical Examples in Python.

In her professional journey, she has worked on use cases like anomaly detection, sentiment analysis, classification, transactional AI assistants, complex big data processing, data analytics, document digitisation, ETL pipelining 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.

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

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

Devrim Sonmez

Course Tutor

Devrim Sonmez is the Managing Director of IEXPAND.UK (TR.PE Group Company), a technology advisory and corporate finance boutique focused on growing and innovative companies. He is also a UK Representative for MEXT Technology Center.

Devrim Sonmez is regarded as a high performing executive and entrepreneur with over 24 years of experience at intersection of digital and technology with various industries, over 14 years of Executive Board experience and taking a strategic role in securing Mergers & Acquisition deals worth over $200 million in technology.

Mr. Sonmez’s education includes a Mathematics Bachelor of Science from the leading Turkish university in Ankara, the Middle Eastern Technical University graduating in 1998 and a Master of Business Administration from the Koc University in Istanbul, graduating in 2005. He has attended several lessons of Ajit Jaokar in Oxford University as a Guest Speaker since 2017.

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).


How to apply for this course

1. Please complete the application questionnaire no later than Thursday 10 November 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.