Developing Artificial Intelligence Applications (online)

Overview

Developing Artificial Intelligence Applications using Python and TensorFlow is for developers who know Python or coding in other languages and want to enhance their skills to learn AI applications development using machine learning and deep learning. 

We are pleased to announce an exciting new development: this course will now also include GPT-3/LLM(large language models).

The course will look at the workflow and development of a chatbot end-to-end, from being given a set of resources in an enterprise, and exploring how you would train a chatbot using those resources. 

The session will explore OpenAI integration with PowerBI, Copilot and AI Builder. We will also cover building and training a GPT based chatbot using Python and the Open AI and chatGPT APIs.

This course offers a concise way for developers to transition their careers towards artificial intelligence (AI) through development in Python and TensorFlow. The course takes a practical approach to applying AI to solve business problems. We work with AI problems in financial services (both for business and data/code). Note that the choice of financial services as an application domain for AI is illustrative, i.e. the approach outlined can apply to any business-related application of AI.     

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).

A free e-copy of this book is included in the course fees.

After completing the course, you should be able to understand the workings of the algorithms explored in the course and how they can solve specific business problems.

Dates, Times and Delivery

You should allow for around 8 - 12 hours study time per week.

The taught course will run over six weeks. 

Tutorials will be delivered live on Saturdays via Microsoft Teams, as two sessions each week.

Course times: 09:30 - 14:00 UK time.

There will be a thirty-minute break between the sessions.

A world clock, and time zone converter can be found here: https://bit.ly/3bSPu6D

The tutorials will be recorded and published on the VLE (virtual learning environment), where you can also view and download the course materials and submit assignments. Please note your attendance at all live sessions is still required for certification of attendance.

Hands-on coding exercises, to demonstrate and reinforce learning, will be set during the week via Microsoft Teams, with full support provided by the tutors. These will be both individual and group projects.

Dedicated channels within MS Teams will be used for discussion forums, peer support and collaborative/group projects.

The course remains open and the materials are available to you for six additional weeks after the end of the taught course.

Assignment deadlines may be up to four weeks after the end date of the taught course. 

Accessing Your Online Course 

Details about accessing the private MS Teams course site will be emailed to you during the week prior to the course commencing.  

Please get in touch if you have not received this information within three working days of the course start date. 

Programme details

The program comprises the following modules: 

  • Concepts of machine learning, deep learning, and artificial intelligence 

  • Python for machine learning covering the core python libraries for machine learning and deep learning Numpy,  Pandas,  Matplotlib, Sklearn 

  • Machine learning and deep learning applications: Regression, Classification, Clustering, Multilayer perceptrons 

  • Understanding deep neural networks, NLP, transformers, large language models, and their applications 

  • Designing AI solutions  

  • Understanding AI applications in financial services 

  • Understanding the use of cloud platforms (AWS) for machine learning 

  • Implementing solutions in xgboost and the significance of gradient boosted models 

Coding Exercises: 

Hands-on coding exercises will be set during the week via Microsoft Teams, with full support provided by the tutors. These will be a mix of individual and group projects. 

The above may be subject to minor changes and adjustments

Certification

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 of 75% of the online sessions.
  2. Submit the required practical assignments to demonstrate learning. These involve coding / hands-on exercises (individually and also in groups).
  3. Participants are expected to actively participate in the online discussions.

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

Fees

Description Costs
Course fee £1095.00

Tutors

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.

Ms Ayshe 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.

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

LLM Strategy Consultant and AI Developer

John Alexander is a highly experienced and accomplished professional with a diverse background in technology, strategy consulting, and education. He has a passion for designing and building accessible experiences using machine learning coupled with vision, voice, touch, and virtual/mixed reality. Currently, he serves as an LLM Strategy Consultant and AI Developer, where he focuses on implementing LLM strategies and experimenting with cutting-edge tools like LangChain and Pinecone. Additionally, John is a Tutor at the University of Oxford, where he lectures on Artificial Intelligence applications and Cloud and Edge Implementations.

Prior to his current roles, John spent several years at Microsoft, where he held various positions including Lead Developer and Engineer Relations, Autonomous Systems, and Lead Content Developer on ML.Net. John participated in the Xbox Accessible Controller beta and the launch video. He was on the award-winning Hackathon 2020 Elev8: Accessible Guitar Team. These are two of his proudest accomplishments. His expertise also extends to content development and instruction, as he has developed Coursera courses and Learn modules on Autonomous Systems in collaboration with prestigious institutions like the University of Washington and the University of Oxford.

Before joining Microsoft, John was the co-founder of a digital agency and consultancy and had the honor of being a Microsoft Regional Director for 19 years, where he participated in scheduled strategic feedback sessions with Microsoft senior leadership teams. John co-founded the largest technical blogging community in the world, Geekswithblogs.Net, before selling it several years ago. He’s co-authored three best-selling technical books and Microsoft Official Curriculum. John has a proven track record in high-profile international public speaking and presentations in front of some of the most demanding audiences, both executive and technical.

He’s coached several teams of developers, leading one directly responsible for earning their organization a place on CIO Magazine’s “Agile 100” list. John 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 21 years to process billions of dollars in transactions. In his spare time, he's 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.

Marina Fernandez

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.

Anjali Jain

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.

Hazal Kantarci

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. 

Norah Klintberg Sakal

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.

Christoffer Noring

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.   

Kajal Singh

Course Tutor

Senior Data Scientist

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).

Application

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 register on the course, we will contact you regarding payment of the course fee.

Payment

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, tuition and a copy of the course textbook in eBook format.

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.

You will not be required to purchase any specific software to take part in this course.