Courses tagged with "Web Design" (101)

In this course, you will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge.  You will learn about how statistics and probability work together.  The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.  Statistics formalizes the process of making decisions, and this course is designed to help you use statistical literacy to make better decisions.  Note that this course has applications for the natural sciences, economics, computer science, finance, psychology, sociology, criminology, and many other fields. We read data in articles and reports every day.  After finishing this course, you should be comfortable evaluating an author's use of data.  You will be able to extract information from articles and display that information effectively.  You will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistic…

Learn about the most effective data analysis methods to solve problems and achieve insight.

The Coursera course, Data Analysis and Statistical Inference has been revised and is now offered as part of Coursera Specialization “Statistics with R”. This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Learn critical concepts and practical methods to support research data planning, collection, storage and dissemination.

Apply the learned algorithms and techniques for data mining from the previous courses in the Data Mining Specialization to solve interesting real-world data mining challenges.

Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation.

Learn about descriptive statistics, and how they are used and misused in the social and behavioral sciences. Learn how to critically evaluate the use of descriptive statistics in published research and how to generate descriptive statistics yourself, using freely available statistical software.

Do you see yourself as a non-creative individual? Do you want to learn to effectively understand design? Do you want to learn how to see the world around you with new eyes and have the ability to create sharper and more successful websites and graphics from the ground up? This course will teach you the basics of design and help get you on the road to creating, designing and implementing solid designs for the web! In this introductory course, basic design thinking, theory and practice will be explored in an easy to absorb, fun and relaxed environment.Students will begin by understanding and implementing the foundations of design: the basic elements and principles of design. These elements and principles are applicable to all design mediums such as architecture, art, graphic design, photography, print and web design. Special emphasis will be given to the application of these principles and elements, along with color and typography, to the medium of web design. For students who have not had formal training in design, this course will bring them up to speed with the fundamentals of design, while learning how to apply these concepts to web and graphic design. For students who have received previous design training, this course will offer new techniques, tips and tricks, and new ways of thinking of design fundamentals while applying these concepts to the electronic mediums of web design and graphics for the web. Applicable Job Roles: web designers, graphic designers, and webmasters.

Learn the basics of creating data products using Shiny, R packages, and interactive graphics. This is the ninth course in the Johns Hopkins Data Science Specialization.

Learn how to make effective decisions about your future career and how to take control of your professional development by honing your critical thinking and employability skills. Suitable for anyone undertaking some form of study, regardless of academic discipline, interests or employment background.

We are constantly using experiments to tweak and find improvements in our personal lives, our communities, and in our work. But are you doing it efficiently? Or are you changing one thing at a time and hoping for the best? In this course, you'll learn how to plan efficient experiments using statistical methods - enabling you to test for many variables that lead to better results.

Learn the essential exploratory techniques for summarizing data. This is the fourth course in the Johns Hopkins Data Science Specialization.

Try your hand at understanding the brain by learning to analyze neural data yourself! Working with real neural data sets from neuroscience research labs, you’ll learn data analysis techniques so you can discover for yourself how the brain works.

This course is an introduction to the theory and practice of financial engineering and risk management. We consider the pricing of derivatives, portfolio optimization and risk management and cast a critical eye on how these are used in practice. We will also feature some interview modules with Emanuel Derman .

This course provides an introduction to various classes of derivative securities and we will learn how to price them using "risk-neutral pricing". In the follow-up to this course (FE & RM Part II) we will consider portfolio optimization, risk management and more advanced examples of derivatives pricing including, for example, real options and energy derivatives.

This course follows on from FE & RM Part I. We will consider portfolio optimization, risk management and some advanced examples of derivatives pricing that draw from structured credit, real options and energy derivatives. We will also cast a critical eye on how financial models are used in practice.

Everyday across the world, thousands of businesses are victimized by fraud. Who commits these bad acts? Why? And, how? In this course we are going to help you answer the questions: who commits fraud, why and how. We’ll also help you develop skills for catching them.

This course introduces concepts, algorithms, programming, theory and design of spatial computing technologies such as global positioning systems (GPS), Google Maps, location-based services and geographic information systems. Learn how to collect, analyze, and visualize your own spatial datasets while avoiding common pitfalls and building better location-aware technologies.

Learn to use the tools that are available from the Galaxy Project. This is the second course in the Genomic Big Data Science Specialization.