Artificial Intelligence Concepts: An Introduction



Overview

artificial intelligence, n.

The capacity of computers or other machines to exhibit or simulate intelligent behaviour; the field of study concerned with this.

source: Oxford English Dictionary

Artificial Intelligence (AI) has become ingrained in the fabric of our society, often in seamless and pervasive ways that may escape our attention day-to-day. The ability of machines to sense, process information, make decisions and learn from experience is a transformative tool for organisations, ranging from governments to large businesses. However, these technologies pose challenges including social and ethical dilemmas.

This course provides an essential introduction to the key topics underpinning AI, including its historical development, theoretical foundations, basic architecture, modern applications, and ethical implications. The course examines the future trajectory of AI and explores its potential to improve the world, while also highlighting its pitfalls and limitations. It is aimed at a general audience, including professionals whose work involves interaction with AI, as well as those with no prior knowledge of AI. The course aims to instil an appreciation of how our world has already been transformed by AI, to explain the fundamental concepts and workings of AI, and to equip us with a deeper understanding of how AI will shape our society, enabling us to fluently in the language of the future.

This course does not involve any coding and instead focuses on concepts in Artificial Intelligence for a general audience.

This course has no live sessions. You will study structured materials at your own pace each week. Find out more about how our short online courses are taught.

Programme details

The course is broken down into 10 units over 10 weeks, each requiring approximately 10 hours of study time. The following topics are covered:

Unit 1: What is intelligence?

Unit 2: AI and society

Unit 3: Systems and agents

Unit 4: Solving with search

Unit 5: Expert systems

Unit 6: Connectionist models

Unit 7: AI in the 21st century

Unit 8: Data science and AI

Unit 9: Machine learning and AI

Unit 10: Testing AI systems

We strongly recommend that you try to find a little time each week to engage in the online conversations (at times that are convenient to you) as the forums are an integral, and very rewarding, part of the course and the online learning experience.

Textbooks

There is no essential reading associated with this course.

Certification

Credit Application Transfer Scheme (CATS) points 

Coursework is an integral part of all online courses and everyone enrolled will be expected to do coursework. All those enrolled on an online course are registered for credit and will be awarded CATS points for completing work at the required standard.

See more information on CATS points

Digital credentials

All students who pass their final assignment will be eligible for a digital Certificate of Completion. Upon successful completion, you will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate or share it on social media if you choose to do so. 

Please note that assignments are not graded but are marked either pass or fail. 

Fees

Description Costs
Course Fee £415.00

Funding

If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. Please see the below link for full details:

Concessionary fees for short courses

Tutor

Dr Noureddin Sadawi

Dr Noureddin Sadawi specialises in machine/deep learning and data science. He has several years’ experience in various areas involving data manipulation and analysis. He received his PhD from the University of Birmingham. He is the winner of two international scientific software development contests - at TREC2011 and CLEF2012.

Noureddin is an avid scientific software researcher and developer with a passion for learning and teaching new technologies. He is an experienced scientific software developer and data analyst. Over the last few years, he has been using R and Python as his preferred programming languages.

He has also been involved in several projects spanning a variety of fields such as bioinformatics, textual/image/video data analysis, drug discovery, omics data analysis and computer network security. He has taught at multiple universities in the UK and has worked as a software engineer in different roles. Currently he holds the following part-time roles: senior content developer and lecturer at the University of London; international trainer with O'Reilly and Pearson; short course trainer and instructor at Goldsmiths University, London as well as a lecturer at the University of Oxford. He is the founder of SoftLight LTD, a London-based company that specialises in data science and machine/deep learning where he works as a consultant providing advice and expertise in these areas. Currently he is a member of the organising committee of this international conference: https://ilcict.ly/. A list of his publications can be found here.

Course aims

  • To introduce the concept of artificial intelligence and its different paradigms
  • To provide an understanding of the real-world potential and limitations of artificial intelligence
  • To describe the reach of artificial intelligence in society today.

Learning outcomes

By the end of this course students should:

  • Understand the concept of artificial intelligence versus human intelligence
  • Understand the foundational concepts in mathematics and logic underpinning AI
  • Be able to identify examples of real-world applications of AI
  • Be able to discuss the social, ethical and sustainability dilemmas posed by AI
  • Understand some of the challenges, limitations, and pitfalls of AI in real world applications.

Assessment methods

You will be set two pieces of work for the course. The first of 500 words is due halfway through your course. This does not count towards your final outcome but preparing for it, and the feedback you are given, will help you prepare for your assessed piece of work of 1,500 words due at the end of the course. The assessed work is marked pass or fail.

Application

Please use the 'Book now' button on this page. Alternatively, please complete an enrolment form

Level and demands

This course is open to all and no prior knowledge is required.

This course is offered at FHEQ level 4 (i.e. first year undergraduate level) and you will be expected to engage in independent study in preparation for your assignments. Our 10-week Short Online Courses come with an expected total commitment of 100 study hours.

English Language Requirements

We do not insist that applicants hold an English language certification, but warn that they may be at a disadvantage if their language skills are not of a comparable level to those qualifications listed on our website. If you are confident in your proficiency, please feel free to enrol. For more information regarding English language requirements please follow this link: https://www.conted.ox.ac.uk/about/english-language-requirements

IT requirements

This course is delivered online; to participate you must to be familiar with using a computer for purposes such as sending email and searching the Internet. You will also need regular access to the Internet and a computer meeting our recommended minimum computer specification.

Terms & conditions for applicants and students

Information on financial support