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Artificial Intelligence: an Introduction

Artificial Intelligence: an Introduction

An intensive summer programme designed to introduce students aged 19+ to the principles of Artificial Intelligence.

A one-week programme, residential in a college of the University of Oxford.

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Course Summary

This course is focussed on providing students with knowledge and understanding in the  various strands and concepts of modern day Artificial Intelligence (AI) such as big data machine learning, deep learning along with programming languages such as R, Python and Hadoop.

It will take both a theoretical and applied approach through hands on exercises as well as sharing case examples and demonstrations throughout the course with students to strengthen their knowledge, understanding and skills in using AI techniques. A notable feature of the course will be underlying technical coverage of conversational agents such as Siri, Alexa, Cortana and so on.

The course will start by laying out the essential components of machine learning systems and discuss the practical application of various AI programming languages along with their relative strengths and weaknesses and will introduce the regression technique for inferring continuous values. From here the course will aim to develop students’ skills in natural language processing tasks and assist students in finding the right machine programmable representations for both text and spoken documents.

In addition, students will be shown how machine translation techniques can be used without the need for human intervention and students will be shown complex information retrieval methods such as web crawling and indexing techniques along with statistical and technical tools. The final day will focus on ‘the deep learning revolution’ that is taking place around the world and will involve a critical discussion of contemporary machine learning models and future developments in AI that are on the horizon.

Learning Objectives

By the end of the course students will understand:

  • The technical elements and theories behind modern AI programmes and take steps to study further AI theories, research and real world applications
  • How to further build expertise in AI and machine learning technologies
  • How to assess and investigate further the role that AI and machine learning technologies can play in different industries and aim to potentially develop AI, machine and deep learning models for these industries

Course Outcomes

Monday Lecture 1: Modern AI Principles-core concepts
Seminar 1: Hands on practical experience in the use of programming tools and languages
Tuesday Lecture 2: Current developments in Machine Learning and Big Data
Seminar 2:Applying machine learning principles to tasks in regression, classification and model generality problems Big data set case study analysis
Wednesday Lecture 3: Natural Language Processing- using programming to process and analyse large natural language data sets
Seminar 3: Work through practical exercises to develop skills in language modelling, ,text representation, machine translation and conversational agents
Thursday Lecture 4: Information Retrieval-focusing on automated internet algorithms
Seminar 4: Applied technical practice in using web crawling, indexing and ranking tools. Applied case study analysis of information retrieval systems in use
Friday Lecture 5: Deep Learning and the evaluation of machine learning models
Seminar 5: Presentations, course review and action planning


Assessment Methods

1 x Written Assignment (500-750 words)

1 x Group Presentation


Oxford College Accommodation

  • Location Oxford
  • Ages Ages: 12+, 13-15, 16-18, 19+
  • Bedroom Type Single and twin
  • Bathroom Type En-suite & Shared (single gender)
  • Year Built Founded in 1096 (University of Oxford)

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