Financial derivatives are ubiquitous in global capital markets. Students will obtain a sophisticated understanding of valuation methods; tools for quantifying, hedging, and speculating on risk; and a basic familiarity with major markets and instruments. Financial derivatives are ubiquitous in global...

This free 5-module online introductory course gives you the essential concepts, techniques and skills to effectively work with data and produce compelling data stories under tight deadlines. Comprising of video lectures, tutorials, assignments, readings and discussion forums, this course is open to...

The exercises we cover today will have you working directly with the Spark specific components of the AMPLab’s open-source software stack, called the Berkeley Data Analytics Stack (BDAS).

This three-week course provides a foundation for marketers and analysts seeking to understand the core principles of digital analytics and to improve business performance through better digital measurement. Course highlights include: * An overview of today’s digital measurement landscape * Guidance...

In this course, we study neural networks of various types. Topics include: neural network architectures, perceptrons, the backpropagation algorithm, neuro-probabilistic language models, convolutional nets for digit recognition, mini-batch gradient descent, the momentum method, recursive neural networks...

Introductory course in machine learning by world leading expert Geoffrey Hinton. Topics include: linear regression and classification, neural networks, clustering, decision trees, gaussian processes, deep belief nets and more

A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms (Cambridge University Press, 2003)" which can be bought at Amazon, and is available free online. A subset of these lectures used to constitute a Part III Physics course at the University...

Advanced course in machine learning by world leading expert Geoffrey Hinton. Topics include: graphical models, Restricted Boltzmann machines, Object Recognition in Deep Neural Nets, Recurrent neural networks, Non-linear Dimensionality Reduction and more.

The course is an interdisciplinary course, focused on the emerging science of complex networks and their applications. The material includes the mathematics of networks, their applications to biology, sociology, technology and other fields, and their use in the research of real complex systems in nature...

Learn how to use Azure Data Lake technologies to store and process big data in the cloud. Want to store and process data at scale? This data analysis course teaches you how to apply the power of the Azure cloud to big data using Azure Data Lake technologies. Learn how to manage data in Azure Data Lake...

Discover and acquire the quantitative data analysis skills that you will typically need to succeed on an MBA program. This course will cover the fundamentals of collecting, presenting, describing and making inferences from sets of data. Want to study for an MBA but unsure of the basic data analysis still...

Learn how to use Microsoft Azure Data Factory to orchestrate big data workflows in the cloud. Need to schedule and manage big data workflows? This data analysis course teaches you how to use Azure Data Factory to coordinate data movement and transformation using technologies such as Hadoop, SQL, and...

Learn the methods and strategies for using large-scale educational data to improve education and make discoveries about learning. Online and software-based learning tools have been used increasingly in education. This movement has resulted in an explosion of data, which can now be used to improve educational...

Learn to create a novel mobile application in this MIT course - from research to design, usability, implementation and field evaluation. How do you design a mobile app that truly changes people's lives? How can you understand how a new service is being used, both quantitatively and qualitatively? How...

Learn to apply formal methods to systematically develop correct, loop-based programs, an essential skill for computer programmers. Is my program correct? Will it give the right output for all possible permitted inputs? Computers are now essential in everyday life. Incorrect programs lead to frustration...

Geometry and Quantum Field Theory, designed for mathematicians, is a rigorous introduction to perturbative quantum field theory, using the language of functional integrals. It covers the basics of classical field theory, free quantum theories and Feynman diagrams. The goal is to discuss, using mathematical...

Learn basic data visualization principles and how to apply them using ggplot2. As part of our Professional Certificate Program in Data Science, this course covers the basics of data visualization and exploratory data analysis. We will use three motivating examples and ggplot2, a data visualization package...

Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform. In data science, data is called "big" if it cannot fit into the memory of a single standard laptop or workstation. The analysis of big datasets requires using a cluster of tens, hundreds or thousands of computers...

Learn best approaches and practices for marketing measurement, including how to use metrics to measure success. Begin your journey in a new career in marketing analytics. Learn about powerful strategies and methodology, starting with identifying market trends and metrics used to measure marketing success...

Learn about manufacturing systems and ways to analyze them in terms of material flow and storage, information flow, capacities, and times and durations of events, especially random events. In this course, part of the Principles of Manufacturing MicroMasters program, you will learn how to analyze manufacturing...