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Students
Tuition Fee
EUR 17,500
Per course
Start Date
Medium of studying
On campus
Duration
1 years
Program Facts
Program Details
Degree
Masters
Major
Business Management | Artificial Intelligence | Data Analysis
Area of study
Business and Administration | Information and Communication Technologies
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
EUR 17,500
About Program

Program Overview


Artificial Intelligence for Business – MSc

Course Overview

This programme’s aim is to develop graduates with skills in artificial intelligence, with a focus on business use cases of this technology. Recognising the increasing value of artificially intelligent models to organisations, graduates of this programme will be versed in the technologies, processes, and socio-ethical considerations of artificial intelligence as applied in business contexts. In the third and final semester during the summer, students will complete a substantive project and dissertation document.


Entry Requirements

  • Students are expected to have a minimum of a Merit Higher Diploma (Level 8) or 2.2 Honours Bachelor Degree (Level 8) in Computing/Business Computing, Electronics, Computer Science, Software Engineering, Data/Business Analytics, Physics, Statistics or equivalent.
  • Non-native English speakers are required to have an IELTS level of 6.5 or higher, or a CEFR English level of at least B2 or equivalent.
  • Please note, students are expected to have a numerate background with prior exposure to computer programming.

Modules Overview

Trimester 1

  • Mathematics for Artificial Intelligence
    • Credits: 5
    • The aim of this module is to introduce students to the mathematical topics relevant to artificial intelligence, covering linear algebra, probability and statistics. Students will gain knowledge of vectors, matrices, eigenvectors, eigenvalues and matrix factorisation. In the probability and statistics section, students will develop skills to effectively analyse, visualise and interpret data to discover important insights. They will learn about tools to manage uncertainty, quantify relationships and make data-driven business decisions.
  • Business Artificial Intelligence Case Studies
    • Credits: 5
    • The purpose of this module is to expand the student’s understanding of techniques employed in AI by exposing them to real-world case studies. These case studies may be of approaches that organisations have taken to implement solutions to real problems in the field or based on scenarios which have no prior solutions to allow the students to create their own approach and compare it with other students. One of the main goals of this module will be to expose students to the varied uses of AI in different industries and critique various case studies using different applications of AI.
  • Fundamentals of Machine Learning
    • Credits: 10
    • This module will introduce students to the classical machine learning algorithms that are used for classification, regression and pattern detection. Students will learn about the core data handling skills necessary to complete the different phases of machine learning implementation. Firstly, students will develop knowledge and skills related to data pre-processing and manipulation, Secondly, students will learn about different machine learning algorithms and the scenarios in which each is appropriate to use. Students will develop the skills to build models and assess their predictive performance. Finally, students will interpret and communicate the results achieved. A goal of this module is to expand the student’s knowledge of classical predictive techniques employed in business contexts by exposing them to case studies of approaches that organisations have taken to implement solutions to problems in the field.
  • Data Mining and Business Intelligence
    • Credits: 10
    • This module introduces data mining and business intelligence concepts. Association rule mining, clustering, recommender systems, and timeseries forecasting are the basic concepts covered in this course. These techniques can provide insight into product and customer similarities, provide product & content recommendations, and facilitate price and sales forecasting efforts. Where possible, code for the approaches employed will be generated using large language models, with students receiving demonstrations on this.

Trimester 2

  • Data Engineering
    • Credits: 10
    • Much of the data produced today is unstructured, such as social media posts, text documents, images and video. Extracting values from unstructured data requires additional tools and techniques, compared with those required to analyse structured datasets. This module explores the theory and practice of managing data, including identifying and extracting data, data pre-processing, transforming and loading data for analysis. A variety of analytics tools and techniques needed to gain value from unstructured data will be employed, with a particular focus on the practical analysis of textual data.
  • Deep Learning
    • Credits: 10
    • This module will build on the foundations laid by the Fundamentals of Machine Learning module and give students a broad overview of the key conceptual ideas and practical skills (Python) necessary to work effectively with deep learning and modern generative AI technologies.
  • Legal, Social and Ethical Implications of AI
    • Credits: 5
    • This module will provide students with an insight into the legal, ethical and social implications of Artificial Intelligence.
  • Research Methods
    • Credits: 5
    • This module aims to introduce students to the key concepts involved in research and to develop their understanding of the uses and relevance of the major methodologies employed. The material covered in this module will form the basis for the Applied Research Project element of the MSc programme, with one of the key outcomes of this module being a valid and robust proposal for an applied research project.

Trimester 3

  • Applied Research Project
    • Credits: 30
    • The project builds on the Research Methods module, where the research proposal will have been developed and submitted. The dissertation will consist of 20,000 words, excluding bibliography and appendices, providing students with an opportunity to develop and demonstrate programming and artificial intelligence model use for business along with written communication skills. As the capstone component of the programme, this element will help integrate the curriculum content and deliver a significant body of work that can contribute to the body of knowledge in artificial intelligence for business. The dissertation will draw on analytical and evaluative competences based upon knowledge and skills developed during the programme. The exercise also provides an opportunity for students to develop their interests in a particular area of artificial intelligence, while demonstrating an ability to undertake independent research in an ethical and methodologically sound manner. As with any project of significant complexity, students will have opportunities to hone time management, problem-solving, and planning skills throughout the course of the project.

What can you do after this programme?

Further Study

  • Upon completion, graduates will be eligible to apply to a relevant Level 10 programme.

Career Opportunities

  • Graduates from this programme will be in a very strong position to move into an AI role in any organisation, especially considering their original qualifications and, in some cases, work experience. This programme will equip graduates with the key skills required to work in a business world where artificial intelligence is becoming ever more present. Roles that graduates could fill after completing the programme include:
    • Data Analyst
    • Data Scientist
    • Data/AI Sales Strategist
    • Sales Engineer
    • Product Owner
    • Data Engineer

Fees

  • Domestic/EU fees are €7,000; Non-EU fees: €17,500

Location

  • Athlone

Duration

  • 1 year

Level

  • Level 9

Course Type

  • Postgraduate

Study Mode

  • Full Time

Department

  • Accounting and Business Computing

Class Contact Hours

  • 13 (average for first and second trimesters), 1 hour contact for third and final summer trimester
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About University
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Technological University of the Shannon (TUS)


Overview:

Technological University of the Shannon (TUS) is a multi-campus university in Ireland, offering a wide range of undergraduate and postgraduate programs across various disciplines. It is known for its focus on applied learning and innovation, fostering strong industry ties and providing excellent employment opportunities for its graduates.


Services Offered:

TUS provides a comprehensive range of services to its students, including:

    Admissions & Support:

    Admissions guidance, international student support, open days, student finance information, induction programs, and student support services.

    Campus Life:

    Accommodation options, career and employability services, chaplaincy and pastoral care, disability supports, learning support, student counselling, student health services, sports facilities, student union, clubs and societies.

    Faculty Areas:

    Business, Hospitality & Humanities, Engineering, Built Environment & Informatics, Sciences, Health & Technology, and Limerick School of Art & Design.

Student Life and Campus Experience:

TUS prioritizes a student-first approach, offering small class sizes and personalized attention. Students can expect a vibrant campus life with a range of clubs, societies, and sports activities. The university also provides comprehensive support services to ensure a positive and enriching student experience.


Key Reasons to Study There:

    Applied Learning & Innovation:

    TUS emphasizes practical skills and real-world application, preparing students for successful careers.

    Strong Industry Ties:

    The university has strong connections with industry partners, providing students with valuable internship and employment opportunities.

    Excellent Employment Opportunities:

    TUS graduates are highly sought after by employers, with a strong track record of successful career outcomes.

    Vibrant Campus Life:

    Students can enjoy a diverse and engaging campus experience with a range of clubs, societies, and sports activities.

    Comprehensive Support Services:

    TUS provides a wide range of support services to ensure students' academic and personal success.

Academic Programs:

TUS offers a wide range of academic programs, including:

    Undergraduate:

    Programs in various disciplines, including business, engineering, science, technology, art, and design.

    Postgraduate:

    Master's and PhD programs in specialized fields.

    Apprenticeships:

    Programs in various trades and technical fields.

    Flexible & Professional Learning:

    Programs designed for working professionals.

Other:

TUS is a QS 5 Star Rated University, recognized for its high-quality education and research. The university is also actively involved in research and development, with a focus on areas of national and global importance.

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410
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