About the Course
The Professional Diploma in Artificial Intelligence will allow you to explore the concepts, opportunities, and challenges presented by this technology which is integrated into many of the services we use daily.
In this course, you will learn what Artificial Intelligence is in practical terms, and what the implications are for businesses, employees, and society. You will learn about different technologies and applications across diverse industries, geographies, and functions. You will learn how to manage the people-process-technology balance to maximise the value of Artificial Intelligence in your organisation.
This course is designed for those who wish to learn how to communicate the opportunities and challenges presented by Artificial Intelligence in an informed and effective way. It is suitable for those who wish to take on a leadership role driving implementation, or even just to understand how this technology will transform the nature of their work. It will guide you in understanding both the theory and the real practical capabilities and implications of this technology.
Entry Requirements
There are no specific entry requirements or pre-qualifications. A general understanding of how organisations operate would be useful. The technical aspects of Artificial Intelligence and its concepts will be taught with the assumption of no prior knowledge. Learners should be curious about Artificial Intelligence and the opportunities and challenges the technology presents. The course is suitable for professionals working at all levels of an organisation, across all industries, geographies and functions.
Prospective students for whom English is not a native language are welcome to undertake the course. It is the responsibility of the student to ensure that their proficiency in English is at IELTS level 6.5 or higher in order to participate and complete assignments successfully.
Learning Outcomes
On completion of this course, students will be able to:
Explain the core concepts, terminology and role of Artificial Intelligence in Digital Transformation
Examine the capabilities of the 3 most common types of Artificial Intelligence and how they can be used to drive greater organisational efficiency and effectiveness
Analyse how to link the business and technical capabilities of an organisation to influence strategy and build competitive advantage
Evaluate the People-Process-Technology balance implications in leveraging Artificial Intelligence
Assess the ethical, social, legal and governance considerations of Artificial Intelligence along with the trends that will influence and shape future workforces
Course Structure
36 hours: Live online sessions, 3 hours per week, 6.30pm – 9.30pm over 12 weeks
Course Breakdown
1. Introduction to Artificial Intelligence
Course introduction
Outline of AI history
Identification of AI myths and capabilities
Explore AI commoditisation
Review key terminology
2. Digital Transformation
Review the 4 domains of digital transformation – Technology; Data; Process; Change Management
Investigate how organisations leverage digital transformation for streamlining processes
3. Process Automation Technology
Explore the elements and capabilities of AI-powered process automation systems
Illustrate the application of RPA across industries, geographies and functions
Investigate opportunities for leveraging RPA to decrease costs and increase profitability
Analyse the industry hype and concerns for RPA implications
Evaluate the strategic implications, such as continuous improvement, business process re-engineering and creating boundaries for business/governance capability
4. Cognitive Insight Technology
Review the elements and capabilities of machine learning systems
Illustrate how machine learning is used in different industries, geographies and functions
Investigate the policy considerations of machine learning
Evaluate the strategic threats, opportunities and applications of machine learning
Decide if and how machine learning should be used in organisations
5. Cognitive Engagement Technology
Review the elements and capabilities of natural language processing (NLP) systems
Illustrate how NLP is implemented across different industries, geographies and functions
Investigate and evaluate the strategic threats, opportunities, implications and policy considerations of NLP
Decide if and how NLP should be used in organisations and the implications of industry convergence
6. Business Capability Strategy
Use situational analysis techniques to develop a strategically focused vision-led approach
Evaluate how business architecture can enable AI
Investigate opportunities for scaling business processes and building compliance by design
Evaluate risk to human and knowledge capabilities within organisations
Analyse governance implications for alignment, control, and enablement of AI
Assess change management concerns
7. Technical Capability Strategy
Analyse the change management and technical/human capital implications
Assess the People-Process-Technology balance for organisations
Evaluate organisational capability in areas such as technical skills, technology know-how, integration with existing cloud projects, employee/vendor decisions, and project management responsibilities
Link business and technical capabilities to influence strategy and build competitive advantage
8. Social, Ethical, and Legal Implications of Artificial Intelligence
Assess the social, ethical, and legal implications of AI
Analyse data protection implications, particularly in relation to GDPR
Evaluate the importance of strong governance processes that identify ethical, legal, and discriminatory consequences –
9. Trends in AI – The Workforce of the Future
Analyse how AI will influence human capital development in future workforces
Explore the learners’ own organisational challenges and opportunities
Teaching and Learning
The weekly lectures, delivered live online, will introduce theory and concepts that will be illustrated with a focus on practical examples. Sessions will follow a cycle through lecturer input, group work, discussion, sharing of examples, comments and feedback. A community of practice will be supported, where learners are encouraged to learn from one another, apply ideas to their own context and practice and share their unique perspective.
Assessment
There are two assessable components in the course; a case study and a final business report.
Assessed Component / Weighting / Date for submission:
1. Case Study: A case study exploring how AI is transforming an industry to achieve high performance (1,500 words) / 40% / Week 8
2. Business report: A report exploring and appraising the opportunities, challenges, and implications of potentially introducing or expanding the use of Artificial Intelligence in the learner’s organisation or organisation of choice (3,000 words) / 60% / 2 Weeks after course completion
The case study will build upon lessons learned in class activities, in particular, studying AI implementation in organisations, by focusing on an industry as a whole. This will demonstrate a broader understanding of the benefits of the different types of AI and the drivers of change in the industry.
The final assessment will bring together all the concepts and insights that learners have amassed and developed to apply to their own professional context. This will demonstrate the depth of understanding of the opportunities, challenges and wider implications of Artificial Intelligence and how they can influence its implementation within an organisation.
Resource requirements and recommended capacity
Students must have a computer, broadband connection, and audio capable of running Zoom sessions.
Click here for Programme Dates
Training Provider: UCD Professional Academy
Programme Cost: €1,500
Programme Cost to South West Gnó members: €525.00
Bookings
Bookings are closed for this event.
