The tutors listed below may be subject to change.
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).
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.
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.
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.
Mentor
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.
Mentor
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.
Course Tutor
Head of Innovation and Data Science Team, PwC Luxembourg
Hazal is an experienced data science professional with over 9 years of experience in the field. As the Head of Innovation and Data Science team at PwC, she is responsible for leading the development of new tools and products to automate the daily tasks of auditors and improve their efficiency using Data Science and Machine Learning.
Before joining PwC, Hazal worked as a data scientist and business analyst for banks, where she focused on Natural Language Processing (NLP) projects. She holds a Bachelor’s degree in Maths and Computer Science, and a Master's degree in Big Data Analytics.
Course Tutor
Norah Klintberg Sakal is an AI enthusiast and entrepreneur passionate about applying technology to solve real-world problems.
As the founder of Braine, Norah assists companies in enhancing productivity using AI tools like GPT-3/4.
Before Braine, Norah founded NuclAI, focusing on AI algorithms for cancer research and microbiology.
During her time at Chan Zuckerberg Biohub, Norah worked on artificial intelligence for segmentation of nuclei from transmitted images, further developing her expertise in the field. She has shared her knowledge and insights at international conferences, engaging audiences on AI, entrepreneurship, and innovation.
As an AI tutor at Oxford, Norah aims to inspire students to explore the potential of AI and create innovative solutions across industries.
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.
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).
Led by Ajit Jaokar and supported by a number of other AI and coding specialists, the course is based on the book Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition (Packt Publishing, 2022).