COMP08182 2021 Artificial Intelligence
Full Title
Artificial Intelligence
Transcript Title
Artificial Intelligence
Code
COMP08182
Attendance
N/A %
Subject Area
COMP - 0613 Computer Science
Department
BUS - Business
Level
08 - Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2021 - Full Academic Year 2021-22
End Term
9999 - The End of Time
Author(s)
Aine Doherty, Mary Loftus
Programme Membership
SG_MBUSI_H08 202100 Bachelor of Arts (Honours) in Business and ICT
SG_MBUSI_H08 202200 Bachelor of Arts (Honours) in Business and ICT
Description
This module provides an Introduction to the field of Artificial Intelligence, with a particular emphasis on applications for 'real-world' problem-solving, including Machine Learning. Data and AI are an ever-increasing source of power in so many aspects of lived experience - as Bucher (2018) puts it, ‘we live algorithmic lives’. Our bank determines our credit-worthiness, our search engines determine the results we see, our TV streaming service determines what movies to show us, our education institutions choose whether to admit us, all from algorithmic decisions made from our data. And now that connected, autonomous, Artificial Intelligence (AI) powered systems are controlling more and more everyday things like vehicles, security access, and our exercise regimes, this trend is only going to increase.
We will explore the evolution of AI from early work in the 1940s and 1950s by Alan Turing and many others, to today's AI revolution spearheaded by Jeff Hinton's revitalisation of the field through Deep Learning. We will differentiate between the goal of general AI and today's 'weak AI'. We will also outline the main sub-fields of AI before concentrating efforts on some modern approaches to today's dominant sub-field of Machine Learning.
With an understanding of the history and basic concepts, this module then progresses to look at how AI is becoming a key technology lever for a wide variety of business scenarios. Armed with this understanding of business applications, students will then build a practical AI implementation in a business area that is of interest to them.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Describe the evolution of Artificial Intelligence from its early beginnings to today's Machine Learning AI systems found in business, healthcare, econometrics, psychology, finance, and the future applications that may emerge in decades ahead, and analyse some seminal approaches to the development of AI.
2.
Implement a basic Machine Learning algorithm using some business data to predict outcomes
3.
Apply Machine Learning techniques to a 'real world' problem domain in a business context after evaluating some possible approaches
4.
Evaluate applicability of a selection of Artificial Intelligence approaches to given business scenarios
Teaching and Learning Strategies
Work will be predominantly conducted in small lab-based groups, typically working in pairs. The emphasis will be on experimentation to explore the interplay between AI frameworks and data to problem solve a business issue. The objective is to assist the student in identifying embedded knowledge in the problem domain, work to understand it in praxis and attempt to apply it in the context of his/her own need.
Module Assessment Strategies
Assessment will be 100% continuous assessment given the practical nature of the module. The aim is to assess tacit knowledge as well as explicit codified knowledge (both self- and open-sourced), testing the student's ability to deal with problems as they arise. The ability to analyse, identify & recognise bugs/incompatibilities/faults/solutions is best gauged over an extended assessment period.
Ongoing quiz and online discussion activity will be conducted between weeks 3 and 10.
Repeat Assessments
Repeat assessments will follow a similar form to the continuous assessments presented over the module. In the case of non-attend repeat students, it may be necessary to purchase a micro-controller board & a small set of related components, all of which is readily available.
Indicative Syllabus
Describe the evolution of Artificial Intelligence from its early beginnings to today's Machine Learning AI systems found in business, healthcare, econometrics, psychology, finance, and the future applications that may emerge in decades ahead, and analyse some seminal approaches to the development of AI.
- History of AI
- Early AI Concepts
- Search Strategies & Heuristics
- Machine Learning
- Case Studies of modern business applications of Artificial Intelligence
- Ethical Considerations in designing Machine Learning applications
Implement a basic Machine Learning algorithm using some business data to predict outcomes
- Defining Machine Learning
- Supervised vs Unsupervised ML
- Common ML Algorithms e.g. Decision Trees, Naive Bayes, Bayesian Networks, Deep Learning
- ML Frameworks, Approaches & Workflows
- Working with Data
- Training, Testing & Validating data outcomes
Apply Machine Learning techniques to a 'real world' problem domain in a business context after evaluating some possible approaches
- Identifying Requirements for a Machine Learning application
- Ethical Review
- Collecting, cleaning and categorising data
- Evaluating most suitable ML approaches for a business domain
- Building and evaluating the application
- Testing the application
Evaluate applicability of a selection of Artificial Intelligence approaches to given business scenarios
- Understanding the business problem and requirements
- Understanding the main AI approaches and typical applications
- Selecting the right application for the given business scenario
- Case Studies to provide opportunity to practice
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
100 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Machine Learning Lab | Practical | Practical Evaluation | 25 % | Week 6 | 2,3 |
| 2 | AI & Machine Learning Discussion Topics | Coursework Assessment | Practical Evaluation | 25 % | OnGoing | 1,4 |
| 3 | Machine Learning Business Application Project | Project | Project | 50 % | Week 13 | 2,3 |
Full Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Lecture Theatre | Lecture | 1 | Weekly | 1.00 |
| Practical / Laboratory | Computer Laboratory | AI Lab | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Individual Research | 4 | Weekly | 4.00 |
Total Full Time Average Weekly Learner Contact Time 3.00 Hours
Required & Recommended Book List
Required Reading
2017-11-29 The Executive Guide to Artificial Intelligence Palgrave Macmillan
ISBN 331963819X ISBN-13 9783319638195
2017-11-29 The Executive Guide to Artificial Intelligence Palgrave Macmillan
ISBN 331963819X ISBN-13 9783319638195
This book takes a pragmatic and hypefree approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in nontechnical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using reallife examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver stepchange benefits to organisations and enables forwardthinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of robot overlords. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes facetoface with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.
Required Reading
2019-06-05 Artificial Intelligence in Practice John Wiley & Sons
ISBN 9781119548218 ISBN-13 1119548217
2019-06-05 Artificial Intelligence in Practice John Wiley & Sons
ISBN 9781119548218 ISBN-13 1119548217
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.