AI Engineering: Agents, Vibe Coding and Full-Stack AI (online)



Overview

Build next-generation AI applications  

This course introduces the core skills of modern AI engineering. It is designed for developers and technical professionals who want to build intelligent systems using large language models (LLMs) and explore how AI is applied in practice.   

You will explore how AI engineers work across full-stack systems, combining software development, machine learning, prompt engineering and agent orchestration. These elements come together to build semi-autonomous, agentic systems that can receive and carry out tasks.   

Taught by industry experts, this AI engineering course combines the latest insights with hands-on tasks, giving you the opportunity to apply what you learn as you go. You will explore workflows such as vibe coding, where developers and AI write code together, and learn practical techniques for guiding the behaviour of AI systems.   

You will also learn how to work with LLMs, APIs, data and user input to create intelligent behaviours that can be applied across a range of AI applications. To implement what you’ve learned, you will then complete a final project where you design and prototype an AI-driven system.  

This course is designed for developers, engineers and technical professionals who want to expand their skills or move into AI-related roles such as AI engineer and data scientist roles. Some prior coding experience (in any programming language) is expected. If you are unsure about your background, we are happy to advise. In some tasks, AI may be used to assist with coding.   

Programme details

The course covers the following topics:   

● Foundation models and LLMs: fine-tuning, embedding, RAG, OpenAI function calling, LangGraph orchestration 

● Prompt and agent engineering: building multi-step agents, tools, tool-use reasoning, prompt scaffolding, planning 

● AI-Native Interfaces: Copilot-style UX, custom GPTs, autonomous agents in apps, voice/UI APIs 

● AI assisted development: vibe code, spec driven development (lovable) 

● Full-stack GenAI Systems: combining frontend (e.g., Vercel, Streamlit), backend (Supabase), and LLM backends 

● AI agents - stacks, components, agentic frameworks (e.g.,  LangGraph,  CrewAI, LangChain, Llamaindex) 

● AI systems: machine learning, deep learning 

● MLOps and LLMOps 

● AI product management 

● Governance, observability and guardrails: governance and safety (fairness, guardrails, explainability, observability, compliance, causality, evaluation loops)  

● Cloud-native AI: using Azure AI Foundry, AWS and open agents to deploy scalable LLM systems 

● Platform usage: use of tools and platforms that manage governance and observability 

● Introduction to AI research 

● Capstone project 

N.B. Further updates are likely to be made prior to the start of the course to reflect the fast-changing nature of the subject area.  

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

This course is delivered over 12 weeks, with two sessions delivered each week, on Tuesday evenings and Saturday mornings. 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)

Tuesday sessions:

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

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

Please note there is no session on Saturday 4 April due to public holidays in the UK.

In addition, please note that Daylight Saving Time comes into effect on Sunday 29 March, and that for subsequent sessions UK Time will be running at UTC +1.

We recommend you allow around 10 - 12 hours study time per week in addition to the hours outlined above, and the course will culminate in a capstone project.

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

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) £4135.00

Tutors

Ajit Jaokar - Course Director

Visiting Fellow, Department of Engineering Science, University of Oxford

Anjali Jain

Digital Solutions Architect, Metrobank 

Ayşe Mutlu

Data Scientist

Dr Amita Kapoor

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

Marina Fernandez

Digital Hive and Innovation consultant, Anglo American Plc

David Knott

Chief Technology Officer, UK Government

Dr Andy McMahon

Principal AI & MLOps Engineer, Barclays

John Alexander

LLM Strategy Consultant and AI Developer

Christoffer Noring

Senior Cloud Advocate, Microsoft 

Dr Martin-Immanuel Bittner

Chief Executive Officer, Redouble AI

Dr Kaouter Karboub

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

Abhinav Kimothi

Co-founder and Head of AI, Yarnit

Aleksander Molak

Machine Learning Researcher, Educator, Consultant and Author

Detlef Nauck

Head of AI & Data Science Research, BT Group 

Parth Shah

Cloud-native solution architect

Kajal Singh

Senior Data Scientist

Magnús Smárason

AI researcher and digital innovator

Shaig Abduragimov

OpenAI

Mayank Sharma

Founder, HiveMTD

Isaak Fabien Sundeman

Growth Market Specialist, Lovable

Jan Borovsky

Software Developer

Steven Kok

Member of Boston Consulting Group's Digital, Financial Institutions and Energy practices

Vignesh Manikam

AI Risk Manager Lead, Nationwide Building Society

Vikkas Arun Pareek

Senior IT and AI Consultant

David A Raho

PhD researcher in Law and Criminology at Sheffield Hallam University

Devrim Sonmez

Senior Partner and Head of AI Division at Hepapi Software

Mahesh Yadav

AI product management expert

Application

How to apply for this course

  1. Complete this short online application form
  2. The administration team will forward your application to the academic review panel, and then be in touch with an update on your application
  3. If successful, you will be asked to make payment via our secure online payment portal. 

Payment

Places will only be confirmed upon receipt of payment.

Fees include electronic copies of 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.

Terms & conditions for applicants and students

Information on financial support