ECS8060: AI Engineering
Queen's University Belfast
ECS8060
AI Engineering
Queen's University Belfast — Summer 2026

Schedule

This tentative schedule outlines all lectures, assignments, and deadlines across the three parts of the course: building intelligent systems with foundation models, adapting foundational models with post-training methods, and deploying them as production systems. Materials will be posted before each session on Canvas. The schedule is subject to change.

Books

The following books may be helpful resources for the course, but they are not required reading.

  • AI Engineering: Building Applications with Foundation Models by Chip Huyen.
  • Reinforcement Learning from Human FeedbackA short introduction to RLHF and post-training focused on language models by Nathan Lambert
  • Date Topic Readings
    Part 1: Building with Foundation Models
    Jun 01 Lecture 1: Introduction, Foundational Models
    Readings Attention Is All You Need
    Improving Language Understanding by Generative Pre-Training
    Attention Is All You Need
    Improving Language Understanding by Generative Pre-Training
    Jun 03 Lecture 2: Problem Framing, Evaluation, and Model Selection
    Readings Holistic Evaluation of Language Models
    Holistic Evaluation of Language Models
    Jun 05 Quiz 1
    Jun 08 Lecture 3: Prompting and In-Context Learning
    Readings Large language models are zero-shot reasoners
    Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
    Large language models are zero-shot reasoners
    Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
    Jun 08 Assignment 1 Released
    Jun 10 Lecture 4: Context Engineering - RAG, Memory, Tools
    Readings Retrieval-Augmented Generation
    Retrieval-Augmented Generation
    Jun 12 Guest Lecture - AMD
    Jun 15 Lecture 5: Multimodal Foundation Models
    Readings Learning Transferable Visual Models From Natural Language Supervision
    Whisper: Robust Speech Recognition
    Learning Transferable Visual Models From Natural Language Supervision
    Whisper: Robust Speech Recognition
    Jun 17 Quiz 2
    Jun 19 Assignment 1 Due
    Jun 26 Quiz 3
    Part 2: Agentic AI
    Jun 22 Lecture 6: Agentic AI
    Readings ReAct: Reasoning and Acting in Language Models
    ReAct: Reasoning and Acting in Language Models
    Jun 24 Lecture 7: Agentic AI
    Jul 27 Lecture 15: Agentic AI
    Part 3: Adapting Foundation Models
    Jun 29 Lecture 8: Why Fine-tune, Memory Math, Instruction Tuning
    Readings Training language models to follow instructions
    Training language models to follow instructions
    Jun 29 Assignment 2 Released
    Jul 01 Lecture 9: Distillation, Parameter-Efficient Fine-Tuning
    Readings Alpaca: A Strong, Replicable Instruction‑Following Model
    LoRA: Low-Rank Adaptation
    Alpaca: A Strong, Replicable Instruction‑Following Model
    LoRA: Low-Rank Adaptation
    Jul 06 Lecture 10: Preference Optimisation, RLHF, Verifiable Rewards
    Readings Direct Preference Optimization
    Direct Preference Optimization
    Jul 08 Quiz 4
    Jul 10 Project Proposal Due
    Jul 10 Assignment 2 Due
    Part 4: Deploying Foundation Models
    Jul 13 Lecture 11: Inference Optimisation
    Readings Efficient Memory Management for LLM Serving with PagedAttention
    Efficient Memory Management for LLM Serving with PagedAttention
    Jul 13 Assignment 3 Released
    Jul 15 Lecture 12: Building Model APIs
    Jul 20 Lecture 13: Building Backend Systems
    Jul 22 Lecture 14: Observability and Feedback
    Jul 24 Quiz 5
    Aug 03 Assignment 3 Due
    Aug 10 Project Office Hours
    Aug 12 Project Report Due
    Aug 14 Project Presentations