I loved this subject as actually enthralling and highly hands-on in its approach whilst balancing between theory, content, and programming and explaining really awesome technical concepts regarding AI, machine learning, deep learning, and even Gen AI! Plus thanks to the subject seminar lecturers and Peter Kitchener himself I found that the overlap between cognitive biology, neuroscience, and computers extraordinarily thought-provoking. What I know is helpful to my learning is the technicality of machine learning and that data, encoding problems, representing data, and forwarding that to machines to learn, problem-solve on their own, and calculate is both beautiful and fascinating and probably would have stunned geniuses of the past such as Alan Turing and Charles Babbage as to how technologically sophisticated we've become as a humanity! Hearing from my peers and mentors on this subject, I know that machine learning and AI--whilst up-to-date and new--are not at all easy to invent and conjure up let alone explain to a cohort of students, so I genuinely appreciate the effort and pure brain-power and thinking it has been done to create and generate a practical and hands-on subject to Neural Networks. Some may argue otherwise, but I still remain optimistic that this subject is really crucial to navigating the next generation of AI movement in this world with a technical expertise in problem-solving, collaboration during discussions and teamwork, and systems and machines improvement designs, which are all and even more invaluable tools, gifts, and practical skills that have been sought to be honed in during all live classes by peers and mentors, but especially encouraged and prompted by the lecturers and tutors! The individual practical report of designing a lexicon system is actually really iconic and sophisticated because I learnt from Peter that symbols have their own defined importance to societies and civilisations as to convey a certain idea, representation of something important, or to carry out abstract computational thinking or develop a notation for patterns that help supersede our ancestors on numerical and complex mathematical thought and their own thinking! This is actually really really cool and inspires me to shoot for the stars with not only biological content-strong subjects like Complex Functions in Neuroscience, but to complement such with a civil and ethical technological approach to AI and cognition. I always endeavoured to learn to the best of my ability in all seminars and tutorials whilst being mindful of the fact that what I'm learning and what everyone enrolled in this subject is learning about is actually breath-taking and powerful tools for developing sophisticated AI tools, to understand and synthesise data when human natural capabilities may be too slow to do so but a computer can outsize any computation at a much faster rate than any human, granted, as I've noted down, with the right cognition granted to it or sometimes recipe given to the machine. This subject is super fun because it opens so many doors to so many profound technologies and applications in making machines a little more like us but better in some qualities and helpful in all that we genuinely need help for. Plus, explaining a lot of profound math-based ideas and how AI works behind the scenes is not an easy task or even doable by just anyone, so I highly appreciate Peter and the learning staff for all their efforts involved! This, being a neuroscience elective is actually under the guise of a machine learning or IT-related subject but I can see why. Neuroscience research and more can benefit from neural networks so this really is an amazing time to be alive when we have real (actual) neural networks in our brain working to solve artificial neural networks to solve biology's toughest challenges where neuroscientists go back to looking at a real set of neural networks in the lab haha!I think adding on a historical component for a brief introductory seminar as to how humans have come from basic evolutionary origins to training, creating, making, and purposing highly technical apparatus in the version of neural networks, machines, and AI or really computers that have something akin to a mind of their own would have really encouraged me much so more in thinking, "hey, these cool details that I'm learning makes me feel a wonder that I'm born to a generation where the coolest technologies are becoming ever more vivid and alive in their own right, there is so much to do, learn, create, and craft that I can progress and strive towards and with the right amount of effort and effortful thinking that comes along with having an awesome and amazing education!" But otherwise, this subject is really deep and meaningful in its core and I highly endeavour to see future installments in the continuation of this subject with the rise and growth of IT and AI and what can be added or maybe subtracted to deliver even MORE sophisticated models of computation and calculations! But alas, that's up to the future to decide who we'll become!

Grade: 90. Legendary subject, super engaging and light workload, should be pretty easy to do well. Everyone I know got H1.

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An exciting cross between neuroscience and artificial intelligence. The computational side can be tough without a strong maths background, but the content is cutting-edge. Extremely engaging and Peter is very passionate about the subject. I found the course content fun to do and it's a nice breakaway from the standard x3 lectures a week format.

Peter is a great lecturer and super helpful in this course! You don't need to know any coding going into it, but it is fast paced and you have to learn quite a bit solo. The quizzes were all super easy and marked fairly, and if you had questions about the quiz (they were open for a week and you could talk with others), you could ask him for help. The MST was also quite fair and marked easily, though you can't ask for help with that one. The final assignment was super fun and you could do whatever you wanted, and if you were lost you could also ask for help at any time (there were QandA sessions every Thurs too), which really helped! I think overall everyone in the course did well, and everyone I know got a H1 overall as well:)

I absolutely loved this subject - the favourite of my course. The seminars are the most interesting lectures I've had and it was nice to be able to enjoy them fully without taking notes as you aren't directly assessed on the content. This subject also really allows you to be creative with your choice of project and take it wherever you like. We haven't got the marks back for the final project, but the rest of the assessments were marked fairly and generously. It would be difficult without any programming background, but not impossible if you put a bit of extra time in (and I'd say it's worth it!)