Artificial Intelligence: Generative AI, Cloud and MLOps (online)

Overview

Generative AI and large language models (LLMs) such as generative pre-trained transformers (GPT) have transformed the AI landscape - both as creative and as development platforms.    

This Artificial Intelligence: Generative AI, Cloud and MLOps (online) course covers workflows for designing and developing autonomous AI agents and systems using cloud, non-generative (classical) AI, generative AI, and MLOps.  

There are three main modalities for LLMs:  

  • Language (e.g. GPT) 

  • Code (e.g. using GPT to generate code) 

  • Images (e.g. Dall-E and Stable diffusion) 

These modalities transform the overall workflow of developing AI by automating significant elements of the data science workflow. 

It is ironic that, of all the jobs AI will affect, the role of the AI developer/data scientist is at the forefront.  

This course is designed for anyone who has a technical background and who wants to transition their career towards AI. You are expected to have been a developer at some point in your career (in any coding language). In exceptional circumstances, we can accept people who do not have a development background. Please contact us if you have any questions. We use Python in the course, and we also use GPT to generate Python code for machine learning and deep learning (where applicable).   

Programme details

1. Open Source AI models - llama 3 and beyond, fine tuning, LlamaIndex and LangChain 

2. AI Engineering MLOps and LLMOps 

3. OpenAI/ GPT ecosystem  

4. Low code data scientist - ie using gen AI/GPT to write code 

5. Coding using Python libraries to create core ML and DL algorithms 

6. Responsible and Ethical AI  

7. Prompt engineering 

8. AGI, AI and Reasoning  

9. Agentic workflows and Autonomous AI agents   

10. Knowledge graphs and AI 

11. Autonomy (robotics)  

12. RAG - including RAG evaluation metrics, Agentic RAG and others.  

13. Small language models 

14. Multimodal AI 

15. Innovative AI applications in industry 

16. An awareness of the significance of Hardware acceleration and edge AI (hardware acceleration projects are not hands-on)

17. Cloud platforms (with an emphasis on AWS) 

18. Enterprise deployment of AI 

The course also covers other significant themes like causal machine learning, computational linguistics, etc in relation to AI. The course also provides viewpoints from industry innovators. This approach empowers you to be prepared for current and future roles in this fast-paced, AI-driven ecosystem primarily targeting the job titles of ‘AI Engineer’ and ‘Data Scientist’.

NB. further updates are likely to be made prior to the start of the course to reflect the fast-changing nature of the subject area. 

Digital Certification

Participants who satisfy the course requirements will receive a University of Oxford digital 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 the AI topics covered in class. 

The certificate will show your name, the course title and the dates of the course you attended. You will also be able to download your certificate or share it on social media if you choose to do so.

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 (10am - 4.30pm UK time, including breaks)

  • 18 and 25 January 2025

  • 1, 8, 15 and 22 February 2025

  • 1, 8, 15, 22 and 29 March 2025

  • 5 April 2025

Tuesday sessions:

1 to 2 hours online each week on Tuesdays (7pm - 9pm UK time)

  • 21 and 28 January 2025
  • 4, 11, 18 and 25 February 2025
  • 4, 11, 18 and 25 March 2025
  • 2 and 8 April 2025

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

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.

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.

Fees

Description Costs
Course fee (standard) £3595.00

Tutors

Ajit Jaokar

Course Director and Tutor

Visiting Fellow, Department of Engineering Science, University of Oxford

Anjali Jain

Senior Course Tutor

Digital Solutions Architect, Metrobank 

Ayşe Mutlu

Senior Course Tutor

Data Scientist

Marina Fernandez

Senior Course Tutor

Digital Hive and Innovation consultant, Anglo American Plc

Dr Amita Kapoor

Senior Course Tutor

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

Mr John Alexander

Course Tutor

LLM Strategy Consultant and AI Developer

Dr Martin-Immanuel Bittner

Course Tutor

Chief Executive Officer, Arctoris

Ruchi Bhatia

Course Tutor

Product Marketing Manager in Data Science and AI, HP

Barend Botha

Course Tutor

Consultant, Data Visualisation

Mr Jesus Serrano Castro

Course Tutor

Microsoft

Geeta Chauhan

Course Tutor

Applied AI group, Meta 

Amitkumar Chougule

Course Tutor

Specialist Registrar in Psychiatry, Cambridge University Hospitals

Dr Francesco Ciriello

Course Tutor

Lecturer in Engineering Education, King’s College London

Kelly Coutinho

Course Tutor

Head of Data Science & Analytics, Ralph Lauren

Kobie Crawford

Course Tutor

Developer Advocate, Mosaic AI at Databricks 

Bhushan Gosavi

Course Tutor

Agricultural scientist and entrepreneur

Sean Hughes

Course Tutor

AI Ecosystem Director, ServiceNow

Dan James

Course Tutor

Founder at Jobgraph, Advisor to UK Cabinet Office and Director of AI at Ministry of Justice

Dr Kaouter Karboub

Course Tutor

Assistant Professor of Computer Science and Artificial Intelligence, Moroccan Institute of Engineering Sciences

Emre Kiciman

Course Tutor

Senior Principal Researcher, Microsoft Research 

Tingyi Li

Course Tutor

Enterprise Solutions Architect, Amazon Web Services (AWS)

Liu Jerry

Course Tutor

Co-founder/CEO of LlamaIndex

Mr Matt Kirk

Course Tutor

Zeitworks

Norah Klintberg Sakal

Course Tutor

AI enthusiast and entrepreneur

David Knott

Course Tutor

Chief Technology Officer for UK Government

Ishan Kumthekar

Course tutor

Computer Scientist, Universtity of Florida

Giulia Romei

Course Tutor

Computational Linguist

Parth Shah

Course Tutor

Cloud-native solution architect

Kajal Singh

Course Tutor

Senior Data Scientist

Magnus Smarason

Course Tutor

AI researcher and digital innovator

David Stevens

Course Tutor

Regional Director for Customer Success, Neo4j 

Dr Erika Tajra

Course Tutor

Associate Lecturer in the Personalised Medicine Division, Great Ormond Street Institute of Child Health and UCL Genomics 
Founder, Rejuven Health

Dr Andy McMahon

Course Tutor

Head of MLOps, NatWest Group

Aleksander Molak

Course Tutor

Machine Learning Researcher, Educator, Consultant and Author

Raphael Mansuy

Course Tutor

Chief Technology Officer, Author, AI Strategist, and Data Engineering Expert

Aishwarya Naresh Reganti

Guest Tutor

Tech Lead, AWS-Generative AI Innovation Center

Detlef Nauck

Course Tutor

Head of AI & Data Science Research, BT Group 

Christoffer Noring

Course Tutor

Senior Cloud Advocate, Microsoft 

Application

How to apply for this course

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

The final date to submit your application is Friday, 13 December 2024. Please note that we accept applicants on a rolling basis and expect this course to be oversubscribed.

We aim to respond to applicants within 10 working days. If your application is successful, you will be sent an email inviting you to purchase your place on the course.

Payment

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.