## The Challenge

A fundamental Machine Learning challenge can develop learners in several ways:

- Career Opportunities: Machine Learning is a rapidly growing field, and there is a high demand for professionals with expertise in this area. By acquiring knowledge in fundamental Machine Learning concepts, learners can open up new career opportunities and enhance their employability. Knowing that there is a demand for their skills can be a strong motivating factor for individuals considering learning Machine Learning.
- Practical Application: Machine Learning has numerous real-world applications across various industries such as healthcare, finance, marketing, and more. Learning the fundamentals of Machine Learning can help learners understand how it can be applied to solve complex problems and make predictions. This practical aspect can be highly motivating for individuals who are interested in using technology to create impactful solutions.
- Innovations and Advancements: Machine Learning is at the forefront of technological advancements and innovations. By studying the fundamentals, learners can gain insights into cutting-edge research and developments in the field. This exposure to exciting advancements and breakthroughs can inspire and motivate learners to explore Machine Learning further.
- Problem-Solving and Critical Thinking: Machine Learning involves analyzing data, identifying patterns, and creating models to make predictions or decisions. The process of learning Machine Learning requires learners to develop problem-solving and critical thinking skills. Engaging in challenging problem-solving exercises and seeing the results of their efforts can be highly motivating for learners.

CV (Curriculum Vitae) is a document that summarizes your educational and professional history. It must provide a detailed overview of your academic and work experience, skills, achievements, and qualifications.

Transcript of Records is an official document issued by your home university. It specifies the name of the institution, the academic programme you are enrolled in, the list of courses taken up until the current period, the exams or tests you passed, the grades and the credits you earned. 

Transcript of Records

Motivation letter is a personal statement and it might include a brief introduction of yourself, explanation why are you interested in the learning opportunity you are applying to, any relevant experience or skills that you have, your goals and how this opportunity will help you achieve them, This document should not be more than 400 words.

Motivation Letter

Dublin City University

Machine Learning

An overview of the tools, techniques and purpose of machine learning.

Circular economy

Entrepreneurship, technology and innovation

Critical and innovative thinking

Inter-personal skills

Media and information literacy

**Climate Change and Sustainability**  

The reality of climate change is imperative for societies to innovate and action solutions that can advance the world to a more sustainable future. Bringing digital technologies and sustainability goals together is logical, and necessary, and today Digital Twins are already having a radical impact on sustainability. By its nature, digital technologies are adaptable and responsive to innovation – but technology providers do not have a monopoly on ideas. This challenge seeks new ideas, and original thinking, to apply Digital Twin technologies to sustainability goals.  

**Digital Twins**  

Digital twins are virtual counterparts of tangible assets, providing real-time data, optimisation, predictive analytics, and alerts. The significance of DT isn't confined to engineers or facility managers, it's equally valuable for end-users and property owners. A pivotal area where digital twin technology shows promise is in real-time sustainability monitoring.  

Digital Twins can significantly improve the design, construction, and operation of assets of all types. It can improve efficiency by monitoring performance in real time, including carbon outputs. It is envisaged that Digital Twins should simulate entire systems or interlinked assets to simulate future effects of climate or citizen actions. They should enable society to do more with less, to utilise resources better, longer, and to recycle where replacement has been the norm, to align engineering data with reality, geospatial, IOT and other operational data. By means of IoT data, Digital Twins should allow AI and machine learning to better analyse performance and improve efficiency.  

If the above is true – what are the opportunities yet unseen, what has not been envisaged, and where are the next true innovations? Recognising that there is often doubt and scepticism when innovation challenges long-held thinking, submissions should consider how societies can facilitate those who would otherwise be sceptical to be part of that change as data proliferation increasingly becomes more widespread and more important to the goals of optimal sustainability.

Member universities may require additional information from applicants. Please read the application information section carefully and include any extra required information in this section.

Member university

Dublin City University

Member university

Dublin City University

Learning opportunities of Dublin City University