Eligibility Requirements for Dublin Business School Master of Science in Artificial Intelligence

Entry Requirements


Minimum 55% or above in bachelor's from a recognized third level institution. Cognate subjects include computer science, technology, networking, information systems, engineering, general science, statistics, data analytics or related discipline.

2.5/4

Bachelor's GPA Requirement

3 years degree

UG Requirement

About Dublin Business School

Dublin Business School (DBS) is one of the largest independent colleges in Ireland, offering a range of undergraduate and postgraduate programs in business, law, arts, media, psychology, and IT. DBS has a diverse student body, with students from over 70 countries, and provides a student-centered learning environment with small class sizes and individual attention from experienced faculty members. The college has a strong focus on employability, with many programs offering work placements and internships, and a career-focused curriculum designed to prepare graduates for success in their chosen fields. DBS is located in the heart of Dublin, a vibrant and multicultural city with excellent career opportunities.

Dublin Business School Master of Science in Artificial Intelligence Program Description

The MSc in Artificial Intelligence at Dublin Business School aims to develop learners within the Artificial Intelligence (AI) discipline involving skills in technology, programming, Data Science, and information processing to respond to the ever-growing demand across industries for AI specialists. The program also recognises the interdisciplinary nature of AI, combined with analytics and large data volumes, creating an environment for AI to emerge as a key technology for the future. AI is a set of technologies that use machine learning, speech analytics, natural language processing, machine vision and analytics to process the data to make informed decisions or recommendations.

The Master of Science (MSc) in Artificial Intelligence aims are to

  • Enable learners to develop mastery of current and developing computer technologies, especially skills related to the development and use of Artificial Intelligence.
  • Provide learners with a deep and systematic knowledge of the management of Artificial Intelligence in organisational contexts.
  • Facilitate the development of applied skills that are directly complementary and relevant to the workplace.
  • Identify and develop autonomous learning skills for the learners.
  • Develop a deep and systematic understanding of current issues of research and analysis.
  • Enable the learners to identify, develop, and apply detailed analytical, creative, problem-solving, and research skills. 
  • Respond ethically and informatively to address unseen situations that may arise due to the emerging needs of the industry.
  • Provide the learner with a comprehensive platform for career development, innovation and further study.

Program URL:https://www.dbs.ie/course/postgraduate/master-of-science-(msc.)-in-artificial-intelligence

Dublin Business School Master of Science in Artificial Intelligence Program Curriculum

1.Deep Learning: This elective course may cover advanced topics in deep learning, including neural networks, convolutional neural networks, and recurrent neural networks.

2.Computer Vision: This elective course may focus on the application of AI techniques to visual data, including image and video analysis, object recognition, and facial recognition.

3.Natural Language Processing: This elective course may cover techniques for processing and analyzing natural language data, including sentiment analysis, topic modeling, and speech recognition.

4.Robotics: This elective course may explore the application of AI techniques to robotics, including robot perception, control, and navigation.

5.Reinforcement Learning: This elective course may cover the principles and techniques of reinforcement learning, including Markov decision processes, Q-learning, and policy gradient methods.

Electives

1.Deep Learning: This elective course may cover advanced topics in deep learning, including neural networks, convolutional neural networks, and recurrent neural networks.

2.Computer Vision: This elective course may focus on the application of AI techniques to visual data, including image and video analysis, object recognition, and facial recognition.

3.Natural Language Processing: This elective course may cover techniques for processing and analyzing natural language data, including sentiment analysis, topic modeling, and speech recognition.

4.Robotics: This elective course may explore the application of AI techniques to robotics, including robot perception, control, and navigation.

5.Reinforcement Learning: This elective course may cover the principles and techniques of reinforcement learning, including Markov decision processes, Q-learning, and policy gradient methods.

1.Machine Learning: This core course may cover the principles and techniques of supervised and unsupervised machine learning, including regression, classification, clustering, and dimensionality reduction.

2.Natural Language Processing: This core course may introduce students to the challenges and techniques involved in processing and analyzing natural language data, including syntax, semantics, and pragmatics.

3.Computer Vision: This core course may cover the principles and techniques of computer vision, including image processing, feature extraction, and object recognition.

4.Robotics: This core course may explore the principles and techniques of robotics, including kinematics, dynamics, and control.

5.Data Analytics: This core course may provide students with an introduction to the principles and techniques of data analytics, including data preprocessing, visualization, and statistical analysis.

1.Machine Learning: This specialization may focus on advanced topics in machine learning, such as deep learning, reinforcement learning, and generative models.

2.Natural Language Processing: This specialization may focus on the application of AI techniques to natural language data, such as sentiment analysis, text summarization, and question answering.

3.Computer Vision: This specialization may focus on the application of AI techniques to visual data, such as image and video analysis, object recognition, and image captioning.

4.Robotics: This specialization may focus on the application of AI techniques to robotics, such as robot perception, motion planning, and control.

5.Big Data Analytics: This specialization may focus on the application of AI techniques to large-scale data, such as distributed computing, data mining, and data visualization.

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Dublin Business School Master of Science in Artificial Intelligence Employment

Companies Recruiting Dublin Business School Master of Science in Artificial Intelligence Graduates

1.Technology Companies: Large technology companies such as Google, Amazon, Microsoft, and IBM are some of the biggest recruiters of AI professionals. They often have dedicated AI research divisions and utilize AI technologies in various products and services.

2.Financial Services: The financial services industry, including banks, investment firms, and insurance companies, are increasingly utilizing AI technologies for fraud detection, risk management, and customer service.

3.Healthcare: The healthcare industry is also leveraging AI technologies for applications such as medical imaging analysis, drug discovery, and patient monitoring.

4.Manufacturing: The manufacturing industry is utilizing AI technologies for predictive maintenance, supply chain optimization, and quality control.

5.Government Agencies: Government agencies are utilizing AI technologies for a variety of applications such as national security, law enforcement, and public health.

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