Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based on mathematics, computer science, linguistics, psychology, and more.
Universities and colleges in Ireland are offering Artificial Intelligence courses in the following subject areas:
There are many Artificial Intelligence courses that take place over 1 year to 4 years depending on the course and modules selected. There are also part-time courses and night courses available so you can be sure to fit in your studies no matter what your schedule is like.
Courses will cover theory work through lectures, assignments, tutorials and taught modules. Assessments will take place on a continuous basis with written examinations and practical assignments combined in order to achieve a qualification. You could also consider work experience or placement during your studies which will give you an advantage. However, taking the initiative to learn the required coding and programming skills on a personal level will also be helpful to your application.
Work Experience will not only give you the opportunity to obtain a deeper knowledge and understanding of the industry, it will also give you a chance to do some essential networking with other industry professionals and gain valuable contacts for the future
After completing a course in Artificial Intelligence you will be able to get started in a career that uses specific knowledge of Artificial Intelligence, software engineering and data analysis.
There are almost limitless possibilities with this technology, so employment opportunities are possible in many fields. For example, you could be working for a large technology company, in the medical profession, an engineering company or within internet security. The main players are the big organisations with well-developed IT systems, landing large contracts. They will often run their own graduate schemes.
There may be some cross-over with other disciplines, including computational statistics, mathematical optimisation, data mining, exploratory data analysis and predictive analytics.
Progressing to a senior level often involves managing a team. Large multinational technology companies may offer the best prospects for career progression and the highest salaries. Freelance and remote opportunities are available, and since there are currently low levels of competition, some graduates go on to form their own companies.
Ensuring your Artificial Intelligence engineering skills are excellent is the best way to stand out and succeed in this career. Working hours will depend on whether you are employed by a company with set business hours, if you are contracted to various facilities or companies or if you work for yourself and freelance. The hours are usually full time, Monday to Friday. You may need to work extra hours or at weekends depending on the project you're working on.
After completing a course in Artificial Intelligence you may choose to pursue further study in a specialist field to increase your knowledge base and skillset. Postgraduate study can also be used as a means to change career focus or to gain professional qualifications required to practise in certain career areas such as Computer Science, Information Technology, Mathematics and Statistics, Finance and Economics.
What are the different applications of Artificial Intelligence?
The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and different treatments in patients, and for surgical procedures in the operating room. Artificial Intelligence can be broken down into 4 types:
Machine learning: Giving a computer system the ability “to learn” using statistical data to become more reliable and efficient.
Natural language processing: Building a machinery system that can understand and interpret natural human languages.
Knowledge management: Receiving an organization’s intangible information and converting it into tangible assets.
Pattern recognition: Training a machine to recognize an image exactly like a human based on a particular pattern.
Explore your options here
