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DTSTART;VALUE=DATE:20260915
DTEND;VALUE=DATE:20260918
DTSTAMP:20260729T023306
CREATED:20260701T215326Z
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SUMMARY:Introduction to Deep Learning - Online
DESCRIPTION:This is a hands-on introduction to the first steps in Deep Learning\, intended for researchers who are familiar with (non-deep) Machine Learning.  This introduction aims to cover the basics of Deep Learning in a practical and hands-on manner\, so that upon completion\, you will be able to train your first neural network and understand what next steps to take to improve the model. \nThe course covers:  \n\nWhat is deep learning?\nClassification by a neural network using Keras\nMonitor the training progress\nAdvanced layer types\nReal world application\n\nLearning Outcomes: \nIntroduction  \n\nDefine deep learning\nDescribe how a neural network is build up\nExplain the operations performed by a single neuron\nDescribe what a loss function is\nRecall the sort of problems for which deep learning is a useful tool\nList some of the available tools for deep learning\nRecall the steps of a deep learning workflow\nTest that you have correctly installed the Keras\, Seaborn and scikit-learn libraries\nUse the deep learning workflow to structure the notebook\n\nClassification by a neural network using Keras \n\nExplore the dataset using pandas and seaborn\nIdentify the inputs and outputs of a deep neural network.\nUse one-hot encoding to prepare data for classification in Keras\nDescribe a fully connected layer\nImplement a fully connected layer with Keras\nUse Keras to train a small fully connected network on prepared data\nInterpret the loss curve of the training process\nUse a confusion matrix to measure the trained networks’ performance on a test set\n\nMonitor the training process \n\nExplain the importance of keeping your test set clean\, by validating on the validation set instead of the test set\nUse the data splits to plot the training process\nExplain how optimization works\nDesign a neural network for a regression task\nMeasure the performance of your deep neural network\nInterpret the training plots to recognize overfitting\nUse normalization as preparation step for deep learning\nImplement basic strategies to prevent overfitting\n\nAdvanced layer types \n\nUnderstand why convolutional and pooling layers are useful for image data\nImplement a convolutional neural network on an image dataset\nUse a dropout layer to prevent overfitting\nBe able to tune the hyperparameters of a Keras model\n\nTransfer learning \n\nAdapt a state-of-the-art pre-trained network to your own dataset\n\nOutlook \n\nUnderstand that what we learned in this course can be applied to real-world problems\nUse best practices for organising a deep learning project\nIdentify next steps to take after this course\n\nPre-requisites: \nLearners are expected to have the following knowledge: \n\nBasic Python programming skills and familiarity with the Pandas package.\nBasic knowledge on machine learning\, including the following concepts: Data cleaning\, train & test split\, type of problems (regression\, classification)\, overfitting & underfitting\, metrics (accuracy\, recall\, etc.).\n\nSetup Instructions \nPlease follow the setup instructions here: https://carpentries-lab.github.io/deep-learning-intro/index.html#software-setup \nNote that software installation can take some time.  Please set up your python environment at least a day in advance of the workshop. If you encounter problems with the installation procedure\, ask your workshop organizers via email for assistance so you are ready to go as soon as the workshop begins. \nProgramme \n\nWhat is deep learning?\nClassification by a neural network using Keras\nMonitor the training progress\nAdvanced layer types\nReal world application\n\nThis course is taking place on 15-17 September from 09:00 – 17:00. \n\nCost: \nThe fee is: \n• £60 per day for students registered at university\n• £150 per day for staff at academic institutions\, Research Councils researchers\, public sector staff and staff at registered charity organisations and recognised research institutions\n• £350 per day for all other participants. \nIn the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. \nIf it is no longer possible to run a course due to circumstances beyond its control\, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs\, losses or expenses that may be incurred as a result of its cancellation of a course\, including but not limited to any travel or accommodation costs. \nThe University of Southampton’s Online Store T&Cs also continue to apply. \nWebsite and registration: \nRegister for this course
URL:https://www.dementiaresearcher.nihr.ac.uk/event/introduction-to-deep-learning-online/
CATEGORIES:Training
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DTSTART;VALUE=DATE:20261209
DTEND;VALUE=DATE:20261210
DTSTAMP:20260729T023306
CREATED:20260723T101931Z
LAST-MODIFIED:20260723T101931Z
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SUMMARY:Qualitative Methods for Understanding Diverse Lives
DESCRIPTION:In this one-day online training workshop you will be introduced to four qualitative research methods to better understand diverse lives – Photo Go-Alongs\, Collage\, Life History Interviews and Participant Packs. When researching social groups\, researchers may focus on categories such as age\, gender\, sexuality and so on. These categories can turn catch-all terms into catch-all agendas. \nTreating groups of people with one shared characteristic as homogenous risks a cookie-cutter approach which overlooks diverse lives and needs. Given the complexity of what it means to be a person\, a one-size fits all approach to engagement cannot suffice. The methods introduced in this training workshop are beneficial in exploring diverse lives and can be used when researching with any group. \nThe session is aimed at PhD students and academics of all career stages across the UK who want to better understand: \n\nThe specific place-based needs of people\nThe everyday practices of people\nThe world from participants’ perspectives\nHow to work with people in an inclusive and accessible way\n\nThis online training workshop will be structured as follows:   \n\nIntroductions\nOrigins and Approach\nMethods deep dive:\n\nPhoto Go-Alongs\nParticipant packs\nCollage\nLife Histories\nWorkshops\n\n\nLearnings and close\n\nBy the end of the course participants will: \n\nBe able to think critically about how creative\, participatory methods might be incorporated into their research and/ or teaching.\nHave broadened their understanding of research methods from tools of data collection to techniques for capacity building.\nHave workshopped four qualitative methods for creatively engaging with people (Photo Go-Alongs\, Collage\, Life Histories and Participant packs).\n\nThis online training workshop will take place over the course of 1 day on Wednesday 11th March 2026 between 10:00 and 16:00\, with 1 hour for lunch between 12:30 and 13:30. \nCost: \nThe fee per teaching day is: £60 per day for registered students. £150 per day for staff at academic institutions\, Research Councils researchers\, public sector staff\, staff at registered charity organisations and recognised research institutions. £350 per day for all other participants. \nIn the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date. \nIf it is no longer possible to run a course due to circumstances beyond its control\, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs\, losses or expenses that may be incurred as a result of the cancellation of a course. \n\nRegister
URL:https://www.dementiaresearcher.nihr.ac.uk/event/qualitative-methods-for-understanding-diverse-lives-2/
LOCATION:Online\, United Kingdom
CATEGORIES:Training
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