Imperial College London is a community of problem-solvers dedicated to finding innovative solutions to the world's biggest challenges. Located in the heart of London, Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges.
A science-based university with an international reputation for excellence in learning and research, Imperial furthers its commitment to improving education worldwide through its learning and teaching strategy.
Coursera
Dive into the core of Mathematics for Machine Learning with our Linear Algebra course. Learn about vectors, matrices, eigenvalues, eigenvectors, and apply these concepts to exciting tasks like image rotation and understanding algorithms like PageRank.
Coursera
Discover the fundamental principles of multivariate calculus and their application in machine learning with this beginner-friendly course. Gain a solid understanding of gradients, optimization techniques, and more, all crucial for developing sophisticated ML algorithms.
Coursera
Dive into the essential mathematics behind one of the most popular dimensionality reduction techniques in machine learning: Principal Component Analysis (PCA). This comprehensive course is designed for those with an intermediate understanding of statistics and linear algebra, aiming to equip you with the skills needed to apply PCA effectively in your data science projects. By the end of this course, you'll have a solid grasp on how to minimize reconstruction error and extract meaningful patterns from high-dimensional datasets.
Coursera
Discover the art and science of preventing disease through organized efforts in society with our Linear Regression in R for Public Health course. Learn to create statistical models that describe how patient and environmental factors influence illness risk, starting from basic concepts like correlation and linear regression. This course will guide you through data importation, examination, and model fitting using the powerful R programming language.
Coursera
Discover the essential elements of statistical analysis and data interpretation tailored specifically for public health professionals. This course provides a solid foundation in understanding key concepts such as types of variables, common distributions, and hypothesis testing. By the end of this program, you'll be able to analyze new datasets, identify their main characteristics, perform basic analyses, and formulate and test hypotheses based on means and proportions.
Coursera
Dive into 'Logistic Regression in R for Public Health' - a practical course designed for healthcare professionals aiming to harness the power of statistical modeling within their field. This hands-on experience will equip you with essential skills in logistic regression analysis, focusing on real-life public health data sets and using R as your tool. You'll learn how to predict health outcomes accurately, considering the unique complexities of public health data.
Coursera
Dive into the world of Survival Analysis in Public Health with our expert-led online course. Gain a deep understanding of time-to-event analysis using R, learn about unique terms like hazard and censoring, and apply your skills through practical data analysis exercises. Perfect for public health professionals looking to enhance their analytical capabilities.
Coursera
Dive into the world of Probabilistic Deep Learning with this comprehensive course designed for those who have already grasped foundational concepts in deep learning with TensorFlow. This specialization focuses on teaching you how to incorporate probabilistic methods into your models using TensorFlow 2, enabling you to better handle noise and uncertainty in real-world applications such as autonomous driving or medical imaging.
Coursera
Embark on a journey into the future of healthcare with 'Introduction to Digital Health'. This course is designed for those eager to understand how digital technologies are revolutionizing medicine and improving patient care. From learning health systems to electronic health records, delve into the world of mobile applications, wearable devices, telemedicine, AI, and big data analytics. Gain insights into their impact on public health responses, especially in managing COVID-19.