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{% extends '@uol-template-course'%}
{% block page_content %}
{% render '@uol-article-content', { article: article } %}
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"content": "\n <h2>Course details</h2>\n\n <p>Our Artificial Intelligence Masters will begin with a two-week online induction designed to prepare you for online learning at the University of Leeds. It will introduce the study skills you will need to successfully complete your degree.</p>\n\n <p>Delivered online, the course offers a flexible schedule of modules which are structured to be accessible to working professionals. There are nine individual 15-credit taught modules and you will typically spend eight weeks studying each module, plus a 45-credit project module over 24 weeks.</p>\n\n <p>The modules cover a variety of subject areas such as algorithms, robotics and machine learning to teach you the technical elements of AI, including robot navigation and manipulation. The Artificial Intelligence project enables you to apply your academic study, techniques and knowledge acquired from the course to develop AI solutions to the real world in your current role to address a work-related challenge, encouraging you to explore, analyse, and innovate upon existing critical theory and practice.</p>\n\n <p>You can take the course at your own pace and adapt your studies to fit around your work and life commitments. To give you flexibility, it is possible to pause your studies and take them up again at a later point. This means you can choose to complete the Artificial Intelligence Masters in a minimum of two years or up to a maximum of four years.</p>\n\n <p>Please note: You might have to take a study break to complete the course depending on when the selected module is next running.</p>\n\n <h3>Course structure</h3>\n\n <p>The list shown below represents typical modules/components studied and may change from time to time. Read more in our <a href=\"#\">Terms and conditions</a>.</p>\n\n <p>For more information and a full list of typical modules available on this course, please read Artificial Intelligence MSc in the <a href=\"#\">course catalogue</a>.</p>\n\n <h4>Year 1 compulsary modules</h4>\n <table><thead>\n <tr>\n <th>Module Id</th>\n <th>Module Name</th>\n <th>Credits</th>\n </tr>\n </thead><tbody>\n <tr>\n <td><a href=\"#\">GEOG100</a></td>\n <td>Programming for Data Science</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1400</a></td>\n <td>Data Science</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1450</a></td>\n <td>Algorithms\t</td>\n <td>15</td>\n </tr>\n </tbody></table>\n\n <h4>Year 1 optional modules</h4>\n <table><thead>\n <tr>\n <th>Module Id</th>\n <th>Module Name</th>\n <th>Credits</th>\n </tr>\n </thead><tbody>\n <tr>\n <td><a href=\"#\">GEOG1300</a></td>\n <td>Machine learning</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1498</a></td>\n <td>Knowledge Representation and Reasoning</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1452</a></td>\n <td>Deep learning</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1750</a></td>\n <td>Data Mining and Text Analytics</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1467</a></td>\n <td>Robotics</td>\n <td>15</td>\n </tr>\n </tbody></table>\n\n <h4>Year 2 compulsary modules</h4>\n <table><thead>\n <tr>\n <th>Module Id</th>\n <th>Module Name</th>\n <th>Credits</th>\n </tr>\n </thead><tbody>\n <tr>\n <td><a href=\"#\">GEOG100</a></td>\n <td>Artificial Intelligence Project (TBC)</td>\n <td>45</td>\n </tr>\n </tbody></table>\n\n <h4>Year 2 optional modules (selection of typical options shown below)</h4>\n <table><thead>\n <tr>\n <th>Module Id</th>\n <th>Module Name</th>\n <th>Credits</th>\n </tr>\n </thead><tbody>\n <tr>\n <td><a href=\"#\">GEOG1300</a></td>\n <td>Machine learning</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1498</a></td>\n <td>Knowledge Representation and Reasoning </td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1452</a></td>\n <td>Deep learning\t</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1750</a></td>\n <td>Data Mining and Text Analytics</td>\n <td>15</td>\n </tr>\n <tr>\n <td><a href=\"#\">GEOG1467</a></td>\n <td>Robotics</td>\n <td>15</td>\n </tr>\n </tbody></table>\n\n\n\n <h2>Learning and teaching</h2>\n\n <h3>Join our powerful learning network</h3>\n\n <p>Our learning will be delivered online via our virtual learning environment, Minerva. Each week you will study through live face-to-face sessions with our world-class academics.</p>\n\n <p>We recognise that professionals have busy lives, so with a 100% online delivery mode, students can manage their learning around their busy personal and full-time employment, without the need to disrupt their life. You will also be given access to premium-quality study videos, library resources and the industry's top electronic journals for independent study.</p>\n\n <p>Our distance learning course is designed to ensure professionals living and working across the world together can share experiences and knowledge with each other. Collaborate and learn from like-minded professionals during regular interactive activities, including live seminars, virtual discussions, and group projects. This allows you to develop a range of transferable skills and grow confidence and strength in character studying within a growing community of virtual learners.</p>\n\n <h3>Introducing Minerva</h3>\n\n <p>Social learning is at the heart of your learning experience, with interactive and collaborative activities embedded into every module of this course. It's what brings your online learning experience to life through:</p>\n\n <ul>\n <li>synchronous and asynchronous video lessons</li>\n <li>interactive surveys, tests, polls and exercises</li>\n <li>weekly live tutorials with classmates and academics</li>\n <li>group projects and discussion boards</li>\n <li>individual access to reading and study resources</li>\n <li>flexible study sessions to allow you to join at any time that suits you</li>\n </ul>\n\n <p>Minerva can be accessed from anywhere with an internet connection and is mobile friendly, so you can study on the go around your existing work and life commitments. You can also benefit from downloadable PDFs on course content for offline reading when required.</p>\n\n <p>We recommend a high-speed broadband internet connection with a minimum speed of 1.5 Mbps. You will need regular access to a desktop computer, tablet or laptop, with a webcam. You will also need the ability to view PDF documents and work in Microsoft Office (software provided).</p>\n\n <p>On this course you'll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.</p>\n\n <h2>Assessment</h2>\n\n <p>Assessment methods will emphasise not just knowledge, but essential skills development too. They will typically include:</p>\n\n <ul>\n <li>mini project reports</li>\n <li>group discussions and assignments</li>\n <li>live and/or pre-recorded presentations</li>\n <li>practical exercises based on real-world scenarios</li>\n <li>essays</li>\n <li>literature reviews</li>\n <li>multiple choice exams for formative learning feedback (no more than 5% of assessment)</li>\n </ul>\n "
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