Courses tagged with "Evaluation" (733)

In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?

This course, part of the Data Science MicroMasters program, will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you’ll learn how to use:

• python
• jupyter notebooks
• pandas
• numpy
• matplotlib
• git
• and many other tools.

You will learn these tools all within the context of solving compelling data science problems.

After completing this course, you’ll be able to find answers within large datasets by using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports. 

By learning these skills, you’ll also become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings. Last but not least, this course will provide you with the foundation you need to succeed in later courses in the Data Science MicroMasters program.

This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.

How can you tell a secret when everyone is able to listen in? In this course, you will learn how to use quantum effects, such as quantum entanglement and uncertainty, to implement cryptographic tasks with levels of security that are impossible to achieve classically.

This interdisciplinary course is an introduction to the exciting field of quantum cryptography, developed in collaboration between QuTech at Delft University of Technology and the California Institute of Technology.

By the end of the course you will

• Be armed with a fundamental toolbox for understanding, designing and analyzing quantum protocols.
• Understand quantum key distribution protocols.
• Understand how untrusted quantum devices can be tested.
• Be familiar with modern quantum cryptography – beyond quantum key distribution.

This course assumes a solid knowledge of linear algebra and probability at the level of an advanced undergraduate. Basic knowledge of elementary quantum information (qubits and simple measurements) is also assumed, but if you are completely new to quantum information additional videos are provided for you to fill in any gaps.

Already know something about quantum mechanics, quantum bits and quantum logic gates, but want to design new quantum algorithms, and explore multi-party quantum protocols? This is the course for you!

In this advanced graduate physics course on quantum computation and quantum information, we will cover:

• The formalism of quantum errors (density matrices, operator sum representations)
• Quantum error correction codes (stabilizers, graph states)
• Fault-tolerant quantum computation (normalizers, Clifford group operations, the Gottesman-Knill Theorem)
• Models of quantum computation (teleportation, cluster, measurement-based)
• Quantum Fourier transform-based algorithms (factoring, simulation)
• Quantum communication (noiseless and noisy coding)
• Quantum protocols (games, communication complexity)

Research problem ideas are presented along the journey.

Learner Testimonial

“This course is hard!” 
-- Anonymous MIT graduate student

This is an introduction to quantum computation, a cutting edge field that tries to exploit the exponential power of computers based on quantum mechanics. The course does not assume any prior background in quantum mechanics, and can be viewed as a very simple and conceptual introduction to that field.

Quantum computation is a remarkable subject building on the great computational discovery that computers based on quantum mechanics are exponentially powerful. This course aims to make this cutting-edge material broadly accessible to undergraduate students, including computer science majors who do not have any prior exposure to quantum mechanics. The course starts with a simple introduction to the fundamental principles of quantum mechanics using the concepts of qubits (or quantum bits) and quantum gates. This treatment emphasizes the paradoxical nature of the subject, including entanglement, non-local correlations, the no-cloning theorem and quantum teleportation. The course covers the fundamentals of quantum algorithms, including the quantum fourier transform, period finding, Shor's quantum algorithm for factoring integers, as well as the prospects for quantum algorithms for NP-complete problems. It also discusses the basic ideas behind the experimental realization of quantum computers, including the prospects for adiabatic quantum optimization and the D-Wave controversy.

Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.

Do I need a textbook for this class?
No. Notes will be posted each week. If you wish to consult other references, a list of related textbooks and online resources will be provided.

What is the estimated effort for course?
About 5-12 hrs/week.

Why is the work load range so wide?
How long you spend on the course depends upon your background and on the depth to which you wish to understand the material. The topics in this course are quite open ended, and will be presented so you can understand them at a high level or can try to follow it at a sophisticated level with the help of the posted notes.

How much does it cost to take the course?
Nothing! The course is free.

Will the text of the lectures be available?
Yes. All of our lectures will have transcripts synced to the videos.

Do I need to watch the lectures live?
No. You can watch the lectures at your leisure.

This course is part of the Microsoft Professional Program Certificate in Big Data and the Microsoft Professional Program Certificate in Data Science.

Transact-SQL is an essential skill for data professionals and developers working with SQL databases. With this combination of expert instruction, demonstrations, and practical labs, step from your first SELECT statement through to implementing transactional programmatic logic.

Work through multiple modules, each of which explore a key area of the Transact-SQL language, with a focus on querying and modifying data in Microsoft SQL Server or Azure SQL Database. The labs in this course use a sample database that can be deployed easily in Azure SQL Database, so you get hands-on experience with Transact-SQL without installing or configuring a database server.

The increased demand by consumers and businesses for more utility, connectivity and smarter and more efficient electronic technology not only creates a need for more embedded systems but also for engineers in the embedded systems field.

In this lab-based computer science course, explore the complexities of embedded systems and learn how to develop your own real-time operating system (RTOS) by building a personal fitness device with Bluetooth connectivity (BLE). An operating system (OS) is a software system that computers use to manage the resources of a computer. The OS decides which tasks are performed when and decides how resources are utilized. Simple embedded systems, which are a combination of electrical, mechanical, chemical, and computer components designed to perform a dedicated function, originally did not need an OS. However, as embedded systems have evolved, so have their complexities. To manage this, an RTOS is now required.

Embedded systems are often deployed in safety-critical situations such as automotive, military, industrial, and medical applications. In applications such as communications and consumer electronics, response time and processing speed are important. A real-time system not only needs to arrive at the correct answer, but must also get the correct answer at the correct time. A RTOS manages a computer's resources so that tasks are performed in a timely mannner.

In this computer science course, students will learn the design fundamentals of an RTOS from the bottom up and use these fundamentals to build practical real-time applications. We will provide a board support package (BSP), so students will be able to focus on the RTOS and Bluetooth network without needing prior experience in circuits and I/O device driver software. This is a hands-on project-based lab course, where you will incrementally build a personal fitness device with Bluetooth connectivity.

This course is intended for students and professional engineers wishing to improve their skills in the fields of embedded systems, product development, computer architecture, operating systems, and Bluetooth networks.

To complete this course, you will need to purchase a lab kit including a microcontroller board, an I/O board, and a Bluetooth module. Instructions about purchasing the kit and installing required software are at http://edx-org-utaustinx.s3.amazonaws.com/UT601x/RTOS.html .

Is your data protected against disaster? Database administrators, regardless of platform need to be ready, whether working with SQL Server 2016, SQL Server v.Next on Linux, or Azure SQL Databases.

In this course, which is part of the SQL Server Database Administration series, you’ll explore the various recovery models you can set up.

Learn about your choices for system backup, gaining understanding of how to back up and recover SQL Server 2016, SQL Server v.Next on Linux, and Azure SQL Databases. Then you’ll actually do a backup. Plus, get practical tips on how to restore a SQL Server database.

This computer science course introduces features and technologies for recovering data. Topics include: SQL Server Recovery Models, Backup of SQL Server Databases, and Restoring SQL Server Databases. 

This course is the first course in a series of two. Both courses provide a solid foundation in the area of reliable distributed computing, including the main concepts, results, models and algorithms in the field.

Today's global IT infrastructures are distributed systems; from the Internet to the data-centers of cloud computing that fuel the current revolution of global IT services. At the core of these services you find distributed algorithms.

These algorithms run on multiple computers and communicate only by sending and receiving messages. It is crucial for the implemented services to continue to work 24/7 even if some of the computers fail or some of the messages are lost in transit. This is the subject of reliable distributed algorithms in computer science.

ID2203.1x covers models of distributed algorithms based on input/output automata; specifications of fault tolerant abstractions and failure detectors; specific distributed abstractions and fault-tolerant algorithms, including reliable broadcast and causal broadcast; key-value stores and consistency models; single-value consensus and the Paxos algorithm.

To complete the course with a full grade (100%) students are required to answer the graded quizzes provided every week, as well as the programming assignments.

This course is the second course in a series of two. Both courses provide a solid foundation in the area of reliable distributed computing, including the main concepts, results, models and algorithms in the field.

In order to ensure that IT infrastructures - a key engine of operations for any organization - operate at full capacity and efficiency, it is vital to understand its core: distributed algorithms. To achieve this, the infrastructure itself must be reliable and resilient. This course continues on the foundations of distributed algorithms, introduced in ID2203.1x, and builds on these concepts at a higher level of complexity to develop the skills needed to build and maintain reliable and efficient distributed systems.

ID2203.2x covers specific advanced abstractions and algorithms including sequence consensus and multi-Paxos; atomic broadcast and replicated state machines. It also covers dynamic reconfiguration of services; the use of physical clocks in distributed systems; the CAP theorem, and weaker consistency models, including eventual consistency and conflict-free replicated data-types.

Students will experiment and develop a variety of distributed algorithms in an interactive, engaging programming environment using the Scala programming language. They will be guided throughout the programming assignments and provided with intuitive examples to help them get started.

To complete the course with a full grade (100%) students are required to answer the graded quizzes provided every week, as well as the programming assignments.

La complejidad de los problemas emanados de una rápida globalización de la economía así como  los grandes avances en la tecnología de la información (TI) han acelerado la aparición de sucesivas crisis económicas y sociales en las que tanto gobiernos de muchos países como empresas encuentran dificultades para adaptarse a esta nueva situación  y cambiar con agilidad sus modelos de  gobierno y gestión.

Por otro lado la agresión al medio ambiente y el cambio climático  y  la necesidad de atender los requerimientos  de agentes económicos y sociales reclaman su derecho a desempeñar el rol que les corresponde. Emergen tendencias como la Responsabilidad Social Corporativa, vinculada a procesos de reporte estandarizado, como el que marca Global Reporting Initiative (GRI) y a mejoras en los esquemas de Gobernanza Corporativa, necesarias para armonizar los distintos ecosistemas tanto sociales como empresariales y ambientales garantizando la legítima participación de todas las partes interesadas y equiparando la información generada a la financiera a la hora de tomar decisiones.

En este escenario, los activos utilizados tanto por gobiernos como empresas para desarrollar deben ser administrados de manera eficaz y eficiente para incrementar el valor de las organizaciones de manera incremental y continua garantizando principalmente  la sostenibilidad económico financiera de esas organizaciones. Dentro de esos activos, la información y la TI adquieren valor importantísimo para facilitar  las necesidades de transformación de las organizaciones y, especialmente gobernar y gestionar el uso adecuado de la TI tal como señala la norma ISO/IECE 38500.

En cualquier caso, la implantación de éstas  tecnologías requiere un cambio profundo en la cultura de las organizaciones, públicas y privadas y la adopción de principios y políticas internas que impidan posibles perjuicios a todas las partes interesadas en el éxito de dichas organizaciones.

La aplicación de las distintas normas mencionadas así como  renovación del concepto de Gobernanza Corporativa aplicada a los distintos activos y especialmente a la TI (dirección y control en el uso y gestión de los mismos) es uno de los grandes retos a los que se enfrenta hoy el mundo económico financiero así como la generación de conocimiento e inteligencia para resolver los graves problemas de nuestros días y en el futuro. Esta nueva forma de trabajar hará que las empresas sean más responsables, comprometidas, humanas,  productivas, y más eficaces y eficientes en el liderazgo, formación y aptitud personal así como un uso adecuado de la TI por parte de la organización.

La complejidad de los problemas emanados de una rápida globalización de la economía así como  los grandes avances en la tecnología de la información (TI) han acelerado la aparición de sucesivas crisis económicas y sociales en las que tanto gobiernos de muchos países como empresas encuentran dificultades para adaptarse a esta nueva situación  y cambiar con agilidad sus modelos de  gobierno y gestión.

Por otro lado la agresión al medio ambiente y el cambio climático  y  la necesidad de atender los requerimientos  de agentes económicos y sociales reclaman su derecho a desempeñar el rol que les corresponde. Emergen tendencias como la Responsabilidad Social Corporativa, vinculada a procesos de reporte estandarizado, como el que marca Global Reporting Initiative (GRI) y a mejoras en los esquemas de Gobernanza Corporativa, necesarias para armonizar los distintos ecosistemas tanto sociales como empresariales y ambientales garantizando la legítima participación de todas las partes interesadas y equiparando la información generada a la financiera a la hora de tomar decisiones.

En este escenario, los activos utilizados tanto por gobiernos como empresas para desarrollar deben ser administrados de manera eficaz y eficiente para incrementar el valor de las organizaciones de manera incremental y continua garantizando principalmente  la sostenibilidad económico financiera de esas organizaciones. Dentro de esos activos, la información y la TI adquieren valor importantísimo para facilitar  las necesidades de transformación de las organizaciones y, especialmente gobernar y gestionar el uso adecuado de la TI tal como señala la norma ISO/IECE 38500.

En cualquier caso, la implantación de éstas  tecnologías requiere un cambio profundo en la cultura de las organizaciones, públicas y privadas y la adopción de principios y políticas internas que impidan posibles perjuicios a todas las partes interesadas en el éxito de dichas organizaciones.

La aplicación de las distintas normas mencionadas así como  renovación del concepto de Gobernanza Corporativa aplicada a los distintos activos y especialmente a la TI (dirección y control en el uso y gestión de los mismos) es uno de los grandes retos a los que se enfrenta hoy el mundo económico financiero así como la generación de conocimiento e inteligencia para resolver los graves problemas de nuestros días y en el futuro. Esta nueva forma de trabajar hará que las empresas sean más responsables, comprometidas, humanas,  productivas, y más eficaces y eficientes en el liderazgo, formación y aptitud personal así como un uso adecuado de la TI por parte de la organización.

This course is Part II of a two-part mathematical introduction to the mechanics and control of robots that can be modeled as kinematic chains. Topics covered include the concept of a robot’s configuration space and degrees of freedom, static grasp analysis, the description of rigid body motions, kinematics of open and closed chains, and the basics of robot control. The emphasis is not on the latest research trends and technological innovations in robotics, but on learning the fundamental concepts and core principles that underlie robotics as a scientific discipline. The intent is to help students acquire a unified set of analytical tools for the modeling and control of robots, together with a reliable physical intuition that recognizes the unique and interdisciplinary nature of robotics—in short, content that will serve as a reliable foundation for whatever trends may appear later, and remain relevant to both the practitioner and researcher. NOTE: Part II will cover screw motions and the product of exponentials kinematics formula, inverse kinematics of open chains, velocity kinematics and statics, closed chain kinematics, and basics of robot control.

We think of Robotics as the science of building devices that physically interact with their environment. The most useful robots do it precisely, powerfully, repeatedly, tirelessly, fast, or some combinations of these. The most interesting robots maybe even do it intelligently. This course will cover the fundamentals of robotics, focusing on both the mind and the body.

We will learn about two core robot classes: kinematic chains (robot arms) and mobile bases. For both robot types, we will introduce methods to reason about 3-dimensional space and relationships between coordinate frames. For robot arms, we will use these to model the task of delivering a payload to a specified location. For mobile robots, we will introduce concepts for autonomous navigation in the presence of obstacles.

Class projects will make use of ROS - the open-source Robot Operating System (www.ros.org) widely used in both research and industry. Computer requirements for working on the projects will include a computer set up with Ubuntu Linux and high bandwidth internet access for downloading and installing ROS packages.

Flying drones or robot manipulators accomplish heavy-duty tasks that deal with considerable forces and torques not covered by a purely robot kinematics framework. Learn how to formulate dynamics problems and design appropriate control laws.

In this course, part of the Robotics MicroMasters program, you will learn how to develop dynamic models of robot manipulators, mobile robots, and drones (quadrotors), and how to design intelligent controls for robotic systems that can grasp and manipulate objects.

We will cover robot dynamics, trajectory generation, motion planning, and nonlinear control, and develop real-time planning and control software modules for robotic systems. This course will give you the basic theoretical tools and enable you to design control algorithms.

Using MATLAB, you will apply what you have learned through a series of projects involving real-world robotic systems.

How do you create robots that operate well in the real world? Learn the key math concepts and tools used to design robots that excel in navigating our complex, unstructured world in environments such as aerospace, automotive, manufacturing and healthcare.

In this course, part of the Robotics MicroMasters program, you will learn how to apply concepts from linear algebra, geometry and group theory and the tools to configure and control the motion of manipulators and mobile robots.

You will also learn how to use MATLAB, the standard robotics programming environment and learn step by step how to use this mathematical tool to write functions, calculate vectors and produce visualizations. You will get hands on experience applying your knowledge to projects using various simulations in MATLAB.

How do robots climb stairs, traverse shifting sand and navigate through hilly and rocky terrain?

This course, part of the Robotics MicroMasters program, will teach you how to think about complex mobility challenges that arise when robots are deployed in unstructured human and natural environments.

You will learn  how to design and program the sequence of energetic interactions that must occur between sensors and mechanical actuators in order to ensure stable mobility. We will expose you to underlying and still actively developing concepts, while providing you with practical examples and projects. 

How do robots “see”, respond to and learn from their interactions with the world around them? This is the fascinating field of visual intelligence and machine learning. Visual intelligence allows a robot to “sense” and “recognize” the surrounding environment. It also enables a robot to “learn” from the memory of past experiences by extracting patterns in visual signals.

You will understand how Machine Learning extracts statistically meaningful patterns in data that support classification, regression and clustering. Then by studying Computer Vision and Machine Learning together you will be able to build recognition algorithms that can learn from data and adapt to new environments.

By the end of this course, part of the Robotics MicroMasters program, you will be able to program vision capabilities for a robot such as robot localization as well as object recognition using machine learning.

Projects in this course will utilize MATLAB and OpenCV and will include real examples of video stabilization, recognition of 3D objects, coding a classifier for objects, building a perceptron, and designing a convolutional neural network (CNN) using one of the standard CNN frameworks.

Programmeren is steeds belangrijker in onze wereld. En jong geleerd is oud gedaan. Deze MOOC bevat filmpjes en opdrachten waarmee kinderen zelf kunnen leren programmeren.

Iedere week maken we samen een game: een doolhof, een aquarium, een Flappy Bird spel en een soort Super Mario.

Iedere week leer je weer nieuwe programmeerblokken en denken we samen na over hoe je je programma’s het mooiste kunt maken.

Dit materiaal volgt de leerlijn programmeren in het basisonderwijs.

Docent of ouder? Lees hier alvast wat deze MOOC inhoudt en hoe je alles goed instelt voor je kind of leerling."

Wil je met meerdere kinderen mee doen? Maak voor ieder kind of leerling een account aan. Zo krijgen ze hun eigen puzzels en kunnen ze in hun eigen tempo werken. Als ze klaar zijn krijgen ze dan ook een mooi Scratch diploma met hun naam erop.

LICENTIE

Het materiaal van deze cursus is eigendom van de TU Delft en wordt aangeboden onder een Creative Commons licentie CC-BY-NC-SA 4.0 International Licence.