Imperial College London is a public research university located in London, United Kingdom. Its founder, Prince Albert, envisioned an area composed of the Royal Albert Hall, Natural History Museum, Victoria and Albert Museum, Science Museum and the Imperial Institute.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis specialisation aims to expose students to, and engage them in, all-encompassing thinking of ‘health systems’ and the importance of a horizontal approach to health system investment to achieve better health outcomes. The specialisation also aims to provide insight into a range of disciplines including organisational behaviour, health policy, information systems and human resources in order to strengthen students’ capacities to think as effective health leaders.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis specialisation reflects on global health challenges and the role of innovative solutions in addressing them. It is intended for public health professionals, budding entrepreneurs and innovators, as well as those interested in understanding the role innovation plays in the health industry.The specialisation begins by providing learners with the ‘nuts and bolts’ of technology and innovation management, including key definitions and terminologies. You'll then examine ethical dimensions of innovation and explore how innovations can be supported through effective financing, protection and other incentives to support entrepreneurship. The specialisation will include in-depth examination of a variety of innovation case studies, using a variety of theoretical and practical frameworks, to understand what makes an innovation more likely to be adopted. You will also explore entrepreneurship and the skills necessary to take an idea through to invention and then innovation - and how to galvanise support for it.By the end of the specialisation, you will be able to consider, in detail, and using appropriate terminology and frameworks, a particular innovation, explaining its added value in a particular context and in a persuasive manner.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis course introduces the field of digital health and the key concepts and definitions in this emerging field. The key topics include Learning Health Systems and Electronic Health Records and various types of digital health technologies to include mobile applications, wearable technologies, health information systems, telehealth, telemedicine, machine learning, artificial intelligence and big data. These technologies are assessed in terms of the key opportunities and challenges to their use and the evidence of their effectiveness in the field of digital health in relation to public health and healthcare globally. The use and application of digital health for COVID-19 forms a case study demonstrating the use of different types of digital health technologies to address key aspects of the response to the virus globally.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis Specialization is intended for learners with basic knowledge in Android app development seeking to develop knowledge in computer graphics and virtual reality in Android. Through the 4 courses, you will learn basic computer graphics theories and practical implementations of 3D graphics, OpenGL ES, and Virtual Reality on Android which will prepare you to design and develop immersive 3D and virtual reality Android app.
Sustainability is one of the key issuesfacing today’s society. This is underlined by the increasing attention on sustainability issues by governments, media, academics and industry. In the context of sustainable development, businesses that are often referredto as part of the problem can be part of the solution. As a consequence, policymakers, industry leaders, society and academics are trying to understand how sustainability affects traditional ways of doing business, and also, how traditional businesses are affected by sustainability. How to develop a sustainable competitive advantage is a key challenge inthe agendas of today’s global executives. This MBA Primer introduces the topic of sustainability from three perspectives: corporate sustainability (core of the module); business ethics and social innovation. The virtual class will be involved in an engaging debatediscussing the different economic, environmental and social perspectives on the topics discussed. At the end of this module, participants will have a comprehensive understanding of sustainability issues, the relevance for policymakers, the role of corporations and the implications for decision-making.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis course focuses on participatory approaches in research, known as 'public involvement' in the UK. You'll specifically, consider why citizens and patients would be involved in research and explore participatory approaches across and within the research cycle in more detail, diving into questions such as:- what kinds of participation can be undertaken at each of the 7 stages of the cycle? - how can you utilise participation in research? - what examples of using participatory approaches exist in research?While this course, as with the rest of the specialisation, focuses on public health and ways of involving citizens and patients across and within the research cycle, these concepts apply to other disciplines and kinds of research too. So, you don't have to be a public health specialist or work in healthcare to gain insight from this course. If you would like to learn more about the theories and core principles of participation within a public health context, we suggest taking Introduction to Participatory Approaches in Public Health. If you're planning a research project and want to include participatory approaches, explore our course Applying Participatory Approaches in Public Health Settings.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeWelcome to this course on Customising your models with TensorFlow 2!In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow. You will also expand your knowledge of the TensorFlow APIs to include sequence models.You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills.At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop a custom neural translation model from scratch.TensorFlow is an open source machine library, and is one of the most widely used frameworks for deep learning. The release of TensorFlow 2 marks a step change in the product development, with a central focus on ease of use for all users, from beginner to advanced level. This course follows on directly from the previous course Getting Started with TensorFlow 2. The additional prerequisite knowledge required in order to be successful in this course is proficiency in the python programming language, (this course uses python 3), knowledge of general machine learning concepts (such as overfitting/underfitting, supervised learning tasks, validation, regularisation and model selection), and a working knowledge of the field of deep learning, including typical model architectures (MLP, CNN, RNN, ResNet), and concepts such as transfer learning, data augmentation and word embeddings.
This interactive course will introduce you to coaching skills for learner-centred conversations. As well as learning about and practicing these skills, you will have the opportunity to reflect on how you can use and integrate these skills into your own educational contexts. The modules will cover:Key principles of coaching approaches in educationCreating the conditions needed for an effective learning relationshipApplying coaching approaches to conversations with learnersUsing coaching approaches in feedback conversations
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeEpidemiological studies can provide valuable insights about the frequency of a disease, its potential causes and the effectiveness of available treatments. Selecting an appropriate study design can take you a long way when trying to answer such a question. However, this is by no means enough. A study can yield biased results for many different reasons. This course offers an introduction to some of these factors and provides guidance on how to deal with bias in epidemiological research. In this course you will learn about the main types of bias and what effect they might have on your study findings. You will then focus on the concept of confounding and you will explore various methods to identify and control for confounding in different study designs. In the last module of this course we will discuss the phenomenon of effect modification, which is key to understanding and interpreting study results. We will finish the course with a broader discussion of causality in epidemiology and we will highlight how you can utilise all the tools that you have learnt to decide whether your findings indicate a true association and if this can be considered causal.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeStatistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health.In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around.This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019.The specialisation can be taken independently of the GMPH and will assume no knowledge of statistics or R software. You just need an interest in medical matters and quantitative data.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeWelcome to this course on Getting started with TensorFlow 2!In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills.At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop an image classifier deep learning model from scratch.Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning. The release of Tensorflow 2 marks a step change in the product development, with a central focus on ease of use for all users, from beginner to advanced level. This course is intended for both users who are completely new to Tensorflow, as well as users with experience in Tensorflow 1.x.The prerequisite knowledge required in order to be successful in this course is proficiency in the python programming language, (this course uses python 3), knowledge of general machine learning concepts (such as overfitting/underfitting, supervised learning tasks, validation, regularisation and model selection), and a working knowledge of the field of deep learning, including typical model architectures (MLP/feedforward and convolutional neural networks), activation functions, output layers, and optimisation.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeWelcome to Logistic Regression in R for Public Health! Why logistic regression for public health rather than just logistic regression? Well, there are some particular considerations for every data set, and public health data sets have particular features that need special attention. In a word, they're messy. Like the others in the series, this is a hands-on course, giving you plenty of practice with R on real-life, messy data, with predicting who has diabetes from a set of patient characteristics as the worked example for this course. Additionally, the interpretation of the outputs from the regression model can differ depending on the perspective that you take, and public health doesn’t just take the perspective of an individual patient but must also consider the population angle. That said, much of what is covered in this course is true for logistic regression when applied to any data set, so you will be able to apply the principles of this course to logistic regression more broadly too. By the end of this course, you will be able to: Explain when it is valid to use logistic regression Define odds and odds ratios Run simple and multiple logistic regression analysis in R and interpret the output Evaluate the model assumptions for multiple logistic regression in R Describe and compare some common ways to choose a multiple regression model This course builds on skills such as hypothesis testing, p values, and how to use R, which are covered in the first two courses of the Statistics for Public Health specialisation. If you are unfamiliar with these skills, we suggest you review Statistical Thinking for Public Health and Linear Regression for Public Health before beginning this course. If you are already familiar with these skills, we are confident that you will enjoy furthering your knowledge and skills in Statistics for Public Health: Logistic Regression for Public Health. We hope you enjoy the course!
Do you want to know more about how a warming planet is changing the landscape for investing? Geared towards professionals working in financial markets, this course provides a solid introduction to the financial risks and opportunities arising from man-made climate change. Our aim is to help you answer a simple question: Does climate risk matter to investors? We do this by defining the financial risks related to climate change and follow with the investment policies and risk management strategies that are taking shape. This course is also a starting point for risk and strategy managers anticipating the impacts from the Financial Stability Board’s Task Force on Climate-Related Financial Disclosures (TCFD) asking firms to disclose the climate risks they face. In short, the course is a primer on how global capital markets are responding the world’s greatest environmental risk. Participants will be exposed to the latest thinking from senior leaders in financial services and multinational firms. The course is led by business school faculty and The Centre for Climate Finance and Investment at Imperial College London; designed by investment practitioners for finance professionals and those aspiring to enter the field. Climate-KIC is supported by EIT, a body of the European Union.
Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeChoosing an appropriate study design is a critical decision that can largely determine whether your study will successfully answer your research question. A quick look at the contents page of a biomedical journal or even at the health news section of a news website is enough to tell you that there are many different ways to conduct epidemiological research. In this course, you will learn about the main epidemiological study designs, including cross-sectional and ecological studies, case-control and cohort studies, as well as the more complex nested case-control and case-cohort designs. The final module is dedicated to randomised controlled trials, which is often considered the optimal study design, especially in clinical research. You will also develop the skills to identify strengths and limitations of the various study designs. By the end of this course, you will be able to choose the most suitable study design considering the research question, the available time, and resources.
Want to study for an MBA but are unsure of basic financial concepts? This business and management course prepares you for studying finance in an MBA program and in business generally.You will learn key financial topics such as present value, Internal Rate of Return (IRR), capital budgeting, equity, bonds, diversification, portfolio choice and the Capital Asset Pricing Model (CAPM), all of which are often discussed and explored in great detail in MBA programs across the globe as well as everyday business operations.A completely online course, you can work wherever and whenever you choose: at home, in the workplace, at a library, coffee shop or even while travelling (with the appropriate network access).This course employs a ‘supported learning’ model. To help you achieve the optimum learning outcomes from this module, Imperial College Business School provides access to an expert online tutor who will support you through the learning materials and associated activities.No previous financial knowledge is needed. Join us as you start your journey into the world of finance for management.