Courses tagged with "Evaluation" (733)

In this computer science course, you will learn how to deploy an ASP.NET MVC application, which is a web application framework developed by Microsoft, which implements the model–view–controller (MVC) pattern, to the Microsoft Azure platform. We will expand on the application by learning about Microsoft Azure’s capabilities and then adding functionality to make your application a more robust and highly available cloud-based solution.

As a data pro, you know that some scenarios—particularly those involving real-time analytics, site personalization, IoT, and mobile apps—are better addressed with NoSQL storage and compute solutions than they are with relational databases. Microsoft Azure has several NoSQL (or “Not Only SQL”) non-relational data storage options to choose from. NoSQL databases are generally built to be distributed and partitioned across many servers. And they’re built to scale out for high availability and to be flexible enough to handle semi-structured and unstructured data. If you have a data model that is constantly evolving and you want to move fast, that’s what these databases are about.

In this practical course, complete with labs, assessments, and a final exam, join the experts to learn how NoSQL has evolved over time. Explore non-relational data storage options in Azure, and see how to use them in your applications. Find out how to create, store, manage, and access data in these different storage options. Get an in-depth look at Azure Table Storage, DocumentDB, MongoDB, and more. Learn about the “three Vs”—variety (schemas or scenarios that evolve quickly), volume (scale in terms of data storage), and velocity (throughput needs to support a large user base). Take this opportunity to get hands-on with NoSQL options in Azure.

Database development is more than just creating a table with rows and columns. This computer science course introduces features and technologies for implementing a database. Topics include:

• Logical table design
• Ensuring Data Integrity
• Indexes
• Views

This courses focuses on the creation of database objects including views, stored procedures, columnstore indexes, and more.

Students considering this course should be familiar with fundamental database concepts.

This course is part of the Microsoft SQL Database Development XSeries.

Take your first step in using C# and XAML to develop Windows 10 Universal Windows Platform apps. In part one of this three-part programming series (three x 4-week courses) you develop a responsive UI that automatically adapts as the app window changes size.

You will also learn to implement XAML data binding and basic application lifecycle management. Put your existing C# and XAML skills to work creating apps for the new Windows app store.

*IMPORTANT:
This course will NOT teach C#, XAML or programming basics.
Prior experience programming in C# and XAML is required.

Use C# and XAML to develop Windows 10 Universal Windows Platform apps that look great on any Windows 10 device. In part two of this three-part programming series (three x 4-week courses) you develop an MVVM app with an adaptive UI that looks great running on phones, tablets, and PCs. You will also learn to develop Windows 10 navigation and menu structures, integrate Cortana into your app, and manage the built-in camera of mobile device. Put your existing C#/XAML skills to work creating apps for the new Windows app store.

*IMPORTANT: This course will NOT teach C#, XAML or programming basics.

Prior experience programming in C# and XAML is required.

Use C# and XAML to develop Windows 10 Universal Windows Platform apps that you will be proud to publish to the new Windows store. In part three of this three-part programming series (three x 4-week courses) you develop an app that connects to the cloud for data and services, implements notifications, geofencing, and live tiles, and includes advanced features such as speech-to-text and inking. Put your existing C#/XAML skills to work creating apps for the new Windows app store.

*IMPORTANT: This course will NOT teach C#, XAML or programming basics. Prior experience programming in C# and XAML is required.

Using a variety of learning tools and methodologies, this course will help you understand the role that the internet plays in economic development, and in the lives of people and businesses in general.

Traditional development challenges are preventing the digital revolution from fulfilling its transformative potential: the opportunity to bring broader development gains in the form of faster growth, more jobs and better services to economies.

In this course, you’ll explore answers to the following key questions: What are the challenges that prevent digital dividends from spreading more rapidly? What are the most important returns to digital investments? What should be done to fully benefit from the digital revolution?

The course will benefit a broad variety of audiences, ranging from student to policymaker, and from entrepreneur to civic actor.

Every business today depends on connectivity, and now there is increasing demand for engineers who can design, develop and manage data networks – and keep them secure as well.

This applied computer science MOOC will give you the hands-on know-how to master the network technologies used every day to communicate and access information via the web and phones.

You’ll learn the vocabulary, concepts and mechanisms common to all digital networks, and explore the TCP, UDP and IP protocols that support all online communications.

You’ll also see how a global network is organized and how its components work together, and understand the importance of standards and protocols. This course is designed for students or professionals with a background in science or computing.

Practical coursework is carried out in a Unix virtual environment that can be installed on any modern computer.

Sign up now and sharpen up your network knowledge!

Learn the fundamentals of digital signal processing theory and discover the myriad ways DSP makes everyday life more productive and fun.

We will present the state of the art energy minimization algorithms that are used to perform inference in modern artificial vision models: that is, efficient methods for obtaining the most likely interpretation of a given visual input. We will also cover the popular max-margin framework for estimating the model parameters using inference.

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming.

Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?

Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).

Part 1 of this course analyzes signals and systems in the time domain. Part 2 covers frequency domain analysis.

Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). Part 1 is a prerequisite for Part 2. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.

Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?

Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).

Part 1 of this course analyzes signals and systems in the time domain. Part 2 covers frequency domain analysis.

Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). Part 1 is a prerequisite for Part 2. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.

6.341x is designed to provide both an in-depth and an intuitive understanding of the theory behind modern discrete-time signal processing systems and applications. The course begins with a review and extension of the basics of signal processing including a discussion of group delay and minimum-phase systems, and the use of discrete-time (DT) systems for processing of continuous-time (CT) signals. The course develops flow-graph and block diagram structures including lattice filters for implementing DT systems, and techniques for the design of DT filters. Parametric signal modeling and the efficient implementation of DT multirate and sampling rate conversion systems are discussed and developed. An in-depth development of the DFT and its computation as well as its use for spectral analysis and for filtering is presented. This component of the course includes a careful and insightful development of the relationship between the time-dependent Fourier transform and the use of filter banks for both spectral analysis and signal coding.

6.341x is organized around eleven units each typically consisting of a set of two to four topics. The source material for learning each topic includes suggested reading in the course text, clarifying notes, other related reading, and video excerpts and will include an interactive on-line discussion forum. The course text is the widely used text by Oppenheim and Schafer (third edition). The video segments are adapted from live video recordings of the MIT residential course. 

Each topic includes a set of automatically-graded exercises for self-assessment and to help in digesting and understanding the basics of the topic, and in some cases to preview topics. A typical unit in the course concludes with a set of more extensive problems to help in integrating the topics and developing a deeper understanding. Automatic grading of your answers to these problems as well as solutions will be provided.

6.341x and this freely-available version were developed through the support and encouragement of the MIT Department of Electrical Engineering and Computer Science, the MIT Office of Digital Learning, and the MIT Research Laboratory of Electronics.

This course can be cited as: Alan V. Oppenheim and Thomas A. Baran, 6.341x Discrete-Time Signal Processing, on edX, Summer 2016. https://www.edx.org/course/discrete-time-signal-processing-mitx-6-341x-1

Hoy en día prácticamente cualquiera con algo de responsabilidad en una organización tiene que hacer en algún momento una presentación eficaz con la que comunicar sus ideas o los resultados de su trabajo. Con este curso introductorio aprenderás las bases para hacer una presentación eficaz que llegue a tu público, conocerás qué imágenes y otros recursos de Internet podrás usar para ello sin infringir ninguna propiedad intelectual y aprenderás a utilizar las funciones básicas del programa Microsoft Powerpoint para realizar esta presentación

Unidades 

• Diseñando presentaciones eficaces
• Introducción a Powerpoint
• Añadiendo contenido a nuestra presentación​

Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability and optimization. Learning algorithms enable a wide range of applications, from everyday tasks such as product recommendations and spam filtering to bleeding edge applications like self-driving cars and personalized medicine. In the age of ‘big data’, with datasets rapidly growing in size and complexity and cloud computing becoming more pervasive, machine learning techniques are fast becoming a core component of large-scale data processing pipelines.

This statistics and data analysis course introduces the underlying statistical and algorithmic principles required to develop scalable real-world machine learning pipelines. We present an integrated view of data processing by highlighting the various components of these pipelines, including exploratory data analysis, feature extraction, supervised learning, and model evaluation. You will gain hands-on experience applying these principles using Spark, a cluster computing system well-suited for large-scale machine learning tasks, and its packages spark.ml and spark.mllib. You will implement distributed algorithms for fundamental statistical models (linear regression, logistic regression, principal component analysis) while tackling key problems from domains such as online advertising and cognitive neuroscience.

Gene sequences and the rest of the genome play an important role in determining how an organism functions normally and reacts when situations change. DNA sequences can also be used to determine relationships between organisms and form the underpinnings of the Tree of Life.

Since DNA sequences play such an important role in any organism it should not be surprising that any changes to a sequence could lead to alterations in behavior or response. For example, a small number of specific changes in DNA sequence have been shown to lead to tumor development in mammals or the production of enzymes with altered properties.

One of the jobs of a bioinformatician is to help determine where these changes are in a DNA sequence and sort out in that context what effects may result, which is usually done by aligning the sequences in question.

In this course, part of the Bioinformatics MicroMasters program, you will learn about the theory and algorithms behind DNA alignments, practice doing alignments manually, and then perform more complicated alignments using web and software based approaches.

With a significant increase in high-profile data breaches and cybersecurity threats in the last couple years, it is critical for businesses to learn about the costs and investment decisions around securing their online systems. If you make decisions around IT investments in your job or are interested in learning more about securing your business, this course is for you.

While many businesses think of cybersecurity as a technical problem, this course broadens that view and shows that security failures are caused as often by bad business decisions and incentive systems as by bad technical design.

This course provides an introduction to the field of the economics behind cybersecurity, delivered by four leading research teams from distinguished universities around the world, including:

• Michel van Eeten of Delft University of Technology in The Netherlands
• Ross Anderson of Cambridge University in the United Kingdom
• Rainer Boehme of University of Münster in Germany
• Carlos H.Gañán of Delft University of Technology in The Netherlands
• Tyler Moore of Southern Methodist University in the USA

It will provide you with the economic concepts, measurement approaches and data analytics to make better security decisions, while helping you to understand the forces that shape the security decisions of other businesses, products and services.

This course will:

1. Teach you to make choices on investing in your company’s cybersecurity. We discuss and apply different economic models that help determine the costs and benefits of security investments.
2. Arm you with research to make strategic business decisions. We review empirical research into security decisions and incentives of actors. We analyze data on firms in different markets, and apply economic concepts to explain the strategies of attackers.
3. Review policy and regulations. We discuss available economic tools to better align the incentives for cybersecurity, including better security metrics, cyber insurance/risk transfer, information sharing, and liability assignment.

This course offers a broad view of the field through lectures and exercises that can apply to both early career professionals as well as senior technical managers.

After finishing this course you will be able to apply economic analysis and data analytics. You will understand the role played by incentives on the adoption and effectiveness of security mechanisms, and on the design of technical, market-based, and regulatory solutions to different security threats.
 
After successfully completing this course, you will:

• Position yourself as a vital subject matter expert regarding the economic drivers that influence cybersecurity and position your company to move forward and stay competitive.
• Engage confidently with management on opportunities and cybersecurity challenges faced by your industry; analyze emerging security threats and how these threats can be mitigated by effectively addressing real economic problems.
• Learn and assess the issues of investment in cybersecurity, making your company more productive, while saving time and money.

Upon successful completion of this course, learners will be awarded a DelftX Professional Education Certificate. The TU Delft Extension School offers Continuing Education Units for this course. Participants of EconSec101x who successfully complete the course requirements will earn a Certificate of Completion and are eligible to receive 2.0 Continuing Education Units (2.0 CEUs).

Enrollment for this course will close on January 29, 2015.

PDF of the Syllabus

FAQs

What is DelftX Professional Education?

DelftX online courses with TU Delft’s standard of educational excellence combined with the flexibility and convenience of online learning that today’s professionals require.

What background is required to participate in this course?

Though some previous knowledge in either computer science or economics is recommended, there is no formal prerequisite as all the concepts will be introduced properly. No advance reading is required.

How will this professional education benefit me?

Economics of cybersecurity is designed to be valuable to both individuals and companies because it provides a platform for discussion from various technical perspectives. The concepts delivered through this course can spark idea generation, and the knowledge gained can be applied to any company’s approach to cybersecurity issues. Specific key benefits are:

• Position yourself as a vital subject matter expert regarding the economic drivers that influence cybersecurity and position your company to propel forward and stay competitive

• Engage confidently with management on opportunities and cybersecurity challenges faced by your industry; analyze emerging security threats and how these threats can be mitigated by effectively addressing real economic problems

• Learn and assess the issues of investment in cybersecurity, making your company more productive while saving time and money.

Does this course offer any special value or exclusive experiences to participants?

EconSec101x offers a unique opportunity to gain insights into the economics of cybersecurity guided by the most active researchers in the field. Students will obtain an understanding of professional, ethical, legal, security and social issues and responsibilities

Can I still enroll if the course has started?

Yes, you can enroll until one week after the course start date and still have the opportunity to obtain a certificate.

What types of certificates does DelftX offer?

Upon successful completion of this course, learners will be awarded a DelftX Professional Education Certificate.

Can I receive Continuing Education Units?

The TU Delft Extension School offers Continuing Education Units for this course. Participants of EconSec101x who successfully complete the course requirements will earn a Certificate of Completion and are eligible to receive 2.0 Continuing Education Units (2.0 CEUs)

How do I receive my certificate and CEUs?

Upon successful completion of the course, your certificate can be printed from your dashboard. The CEUs are awarded separately by the TU Delft Extension School.

Can I take this course without going through the ID-verification procedure?

Yes, you can. Please contact student support and indicate that you want to take EconSec101x by paying the fee but without going through ID-verification.

EECS149.1x introduces students to the design and analysis of computational systems that are integrated with physical processes.

KIeHealthX will introduce students to the field of eHealth and its opportunities and challenges. During the course you will get to know the different concepts that are used in the field and learn how it developed historically. This basic knowledge will help you to understand the opportunities and challenges of the field. You will meet different stakeholders from various countries and get to know their views on the opportunities and challenges of eHealth. We will introduce you to eHealth strategies and frameworks for developing and analyzing them. You will get to know methods for eHealth service development and discuss basic requirements that are necessary to achieve sustainable eHealth applications for both clinical professionals and patients.

You will see examples of eHealth applications in different contexts and for different users. We will discuss questions such as:

• What is it that is so unique about the health sector?
• What factors are important - to avoid failures when implementing eHealth?
• What are usable tools for care professionals?
• How can patients best organize and use their own health data to improve their condition?

eHealth is a global issue but successful eHealth implementation is very dependent on the local context. At the end of the course you will have a basic understanding what eHealth is and how to set up eHealth strategies and discuss them in your specific context. You will also get to know success factors and pitfalls for the development of sustainable eHealth services and their implementation. 

This course is offered in collaboration with EIT Health.