Menu
close
Apply Now
Contact
Parent Programme
BSc in Computing Science Level 7 NFQ
NFQ Level & Reference
Level 7 / Ref M1.12
Duration
12 Weeks X 3 Hours per week
MODULE TITLE
Artificial Intelligence
STAGE
1
Module Credit Units
ECTS: 5

Artificial Intelligence Basics

Introduction to AI

This Artificial Intelligence course aims to provide learners with a solid foundation in the field of Artificial Intelligence (AI), enabling them to grasp key concepts, methodologies, and applications. It focuses on demystifying AI for a diverse audience, fostering a deeper understanding of its principles and implications.

  • It will cultivate an awareness of AI's potential societal and economic implications, including its role in shaping the future job market.
  • Enhance problem-solving abilities by applying AI techniques to address practical challenges.
  • Prepare participants for further exploration in specialized AI domains through a solid understanding of foundational principles.

Indicative Syllabus Content

History of AI: (10%)

  • What is AI and what it is not. Rationality
  • AI origins. Turing, McCulloch & Pitts, Minsky & McCarthy etc
  • AI major milestones.

Main Pillars of AI - theory & practice (75%)

  • Expert Systems
  • Machine Learning (Supervised, unsupervised, reinforcement learning)
  • Natural Language Processing (Classification, machine translation)
  • Perception: Computer Vision (image recognition and machine vision)
  • Speech (text to speech and speech to text)
  • Planning
  • Robotics
  • Multi-agent systems

Ethical Considerations in AI (15%)

  • Hone critical thinking skills to evaluate the strengths and limitations of AI applications.
  • Encourage a well-rounded perspective on the societal and technological implications of AI.
  • Delve into the ethical implications of AI, examining issues such as bias, privacy, and responsible AI development.

Minimum Intended Learning Outcomes (MIMLOs)

Upon successful completion of this module, the learner should be able to:
MIMLO1
Know the history of AI, key influences and evolutions that have brought us to where we are today.
MIMLO2
Discuss the established approaches in AI.
MIMLO3
AI in practice, applying the theories learned in real world situations.
MIMLO4
Ethical Considerations in AI.

Assessment

MIMLOs
Assessment
Percentage
1, 2, 3, 4
CA1: 3, 5, 7 & 9 - Written Assignment
Total 100%
1, 2, 3, 4
CA2: 4, 6, 8 & 10 - Practical Assignment
All assessments
Assessments Every fortnight

Reassessment Opportunity

Where the combined marks of the assessment and examination do not reach the pass mark the learner will be required to repeat the element of assessment that they failed. Reassessment materials will be published on Moodle after the Examination Board and will be aligned to the MIMLOs and learners will be capped at 40% unless there are personal mitigating circumstances.

Aims & Objectives

It will equip learners with the knowledge and skills necessary to navigate the rapidly evolving landscape of AI, empowering them to contribute meaningfully to discussions, projects, and developments in this dynamic field. This course offers a comprehensive overview of AI's historical development and current applications, with a focus on ethical considerations and real-world impact across industries. Students will engage in hands-on exercises to implement AI algorithms and analyze case studies. Additionally, the course covers key mathematical concepts like integrals, vectors, and linear maps, along with practical knowledge of AI tools and programming languages.

[TheChamp-Sharing]
APPLY NOW
Top