Online courses directory (19947)

El curso “Aprendizaje y enseñanza virtual” responde a las necesidades de aquellos que tienen un interés directo en el aprendizaje y la enseñanza digital en cualquier campo. Es ideal para todos aquellos que desean aprender más sobre el potencial de la tecnología en entornos de enseñanza virtual formal e informal, dándoles lo oportunidad de contar con los elementos necesarios para pasar de la idea a la implementación.

Está diseñado para dar respuesta a las preguntas clave que giran alrededor de cómo diseñar experiencias de enseñanza virtual significativas en entornos digitales que faciliten un abanico de oportunidades de aplicación en la enseñanza y la formación online.

El contenido se desarrolla en una serie de temas entrelazados y dosificados en 6 lecciones, que en conjunto proporcionan a los participantes las bases necesarias para comprender y ampliar sus conocimientos y práctica en el diseño de experiencias de enseñanza –aprendizaje online (e-learning).

Este curso forma parte del programa de MicroMasters “e-Learning: crea actividades y contenidos para la enseñanza virtual” diseñada con el propósito de desarrollar en los participantes  las habilidades y competencias necesarias para la implementación de entornos de aprendizaje innovadores apoyados por las TIC's. Al inscribirte en este programa de MicroMasters te daremos acceso a un área de descarga especial, en la cual encontrarás plantillas (predefinidas) de las principales herramientas presentadas en los cursos, guías de mejores prácticas y vídeos complementarios con entrevistas de reconocidos expertos a nivel internacional, que comparten su experiencia y conocimiento en el campo de la educación apoyada por tecnología, el diseño y producción de recursos multimedia.

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies.

Major perspectives covered include:

• probabilistic versus non-probabilistic modeling
• supervised versus unsupervised learning

Topics include: classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection.

Methods include: linear and logistic regression, support vector machines, tree classifiers, boosting, maximum likelihood and MAP inference, EM algorithm, hidden Markov models, Kalman filters, k-means, Gaussian mixture models, among others.

In the first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization. Our approach will be more practically motivated, meaning we will fully develop a mathematical understanding of the respective algorithms, but we will only briefly touch on abstract learning theory.

In the second half of the course we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.

Lectures by Prof.S.N.SinghrnDepartment of Electrical EngineeringrnIIT Kanpur

Lectures by Prof. harishankar RamachandranrnDepartment of Electrical EngineeringrnIIT Madras

Lecture Series on Heat and Mass Transfer by Prof. S.P.Sukhatme and Prof. U.N.Gaitonde, Department of Mechanical Engineer

Lecture Series on Strength of Materials by Dr.S.P.Harsha, Department of Mechanical & Industrial Engineering, IIT Roo

Lecture Series on Control Engineering by Prof. S. D. Agashe, Department of Electrical Engineering,IIT Bombay.

El curso “Tecnologías web emergentes para la enseñanza virtual” está orientado a que conozcas las tecnologías web emergentes que están revolucionando la enseñanza virtual, así como las herramientas web 2.0 que se pueden aplicar en el área educativa o de capacitación.

El contenido se desarrolla en una serie de temas entrelazados y dosificados en 6 lecciones, en las que aprenderás a utilizar las diferentes herramientas web de una forma sencilla y dinámica elaborando recursos educativos virtuales. También te brindamos una serie de estrategias y metodologías para la integración de estos recursos de una forma adecuada y eficiente al proceso de enseñanza-aprendizaje en entornos digitales.

Todas las lecciones incluyen materiales audiovisuales, material de apoyo, actividades prácticas y foros de discusión para formar y promover una comunidad activa de aprendizaje.

Este curso forma parte del programa de MicroMasters “e-Learning: crea actividades y contenidos para la enseñanza virtual” diseñada con el propósito de desarrollar en los participantes  las habilidades y competencias necesarias para la implementación de entornos de aprendizaje innovadores apoyados por las TIC's. Al inscribirte en este programa de MicroMasters te daremos acceso a un área de descarga especial, en la cual encontrarás plantillas (predefinidas) de las principales herramientas presentadas en los cursos, guías de mejores prácticas y vídeos complementarios con entrevistas de reconocidos expertos a nivel internacional, que comparten su experiencia y conocimiento en el campo de la educación apoyada por tecnología, el diseño y producción de recursos multimedia.

Learn the basics of Java programming language and how to develop programs with conditionals and loops, design and implement recursive algorithms, understand basic mechanisms of the Object Oriented Paradigm (OPP), use and interpret the API of some of the most common Java classes and real-world android application development using the Android software development kit (SDK). This course provides the basic skills to ensure a start with Android Studio Editor and use Virtual Device.

This course is part of the GalileoX Android Developer MicroMasters Program that is specifically designed to teach the critical skills needed to be successful in this exciting field and to prepare you to take the Google Associate Android Developer Certification Exam. To qualify for the MicroMasters Credential you will need to earn a Verified Certificate in each of the four courses and the Final Capstone Project.

Learn about project management from a multidisciplinary perspective, as we cover fundamental tools and techniques for managing a broad range of projects.

You will learn about the project management life cycle from initiation to closing. We will address the behavioral and quantitative facets of project management, as well as the use of methods, tools and techniques for the initiation, planning, execution and closing of projects. The course will be divided by the project life cycle phases.

First, we will cover project initiation. We will review projects in organizations, project selection models, the project manager role and project organization structures to better understand how a project is initiated. You will also learn how to create a key project management deliverable, the project charter.

Second, we will cover the project-planning phase. You will learn how to build a comprehensive project management plan covering the key aspects of risk, quality, scope, schedule, cost, time, resource and communications.

Third, we will cover the project execution phase. We will explore the monitoring and control of a project including earned value analysis and project reporting. Case studies and examples will be used to help you understand the correct actions for a project manager to take to keep a project in control.

Finally, we will cover the project closing phase, where we explore the tasks to complete an effective project closure.

This course is part of the RIT Project Management MicroMasters Program that is designed to teach the skills and behaviors necessary to be successful in a project management career. In order to qualify for the MicroMasters Credential, you will need to earn a verified certificate in each of the three courses as well as pass a capstone exam.

Instructors: Prof. Eric Grimson, Prof. John Guttag The goal of this course is to illustrate the spectroscopy of small mo

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.

an introductory course to learn about biotechnological techniques and and its pharmaceutical applications.

Learn the basics you need to have to practice in a hospital settings from medication management to compounding

Projectile motion, mechanics and electricity and magnetism.

Explore how to create a sustainable future by moving away from dependence on fossil resources to biomass resources for the production of food, chemicals and energy-carriers.

We’ll focus on five topics in this course:

1. Introduction to Biobased Sciences

Learn about the products that can be derived from biomass and the processes used to do so, compared to current fossil based products and processes.

2. Biorefinery

Biorefinery deals with the challenge of extracting valuable biomass components and converting them to final products. To achieve this you first need knowledge of the different types of biomass, the molecules present and their chemical characteristics. Biorefinery is all about efficient processing. Aspects of processing include the harvesting, pre-treatments, conversion and separation technologies.

3. Consumer Behaviour

Understand the challenges of moving towards a biobased economy and gaining consumer acceptance. How do consumers evaluate products? And how is their perception influenced by communication strategies?  Understanding the basics of consumer science will help you to implement a consumer view when developing a product. 

4. Biomass production

A biobased economy runs on biomass. It is therefore important to understand which factors play a major role in crop growth, yield formation and quality. In this module you’ll learn to identify design criteria for the production of biobased crops on both a crop and farm level.

5. Achieving Sustainability

Delve into the true meaning of sustainability and how sustainability issues are linked to human activities. Biobased products are not always as sustainable as it seems on first glance. You’ll learn that an understanding of the degree of sustainability requires a thorough analysis of a variety of factors and constituents.

Want to explore ambitious teaching and how collaboration between students and teachers can lead to deeper learning and the development of 21st-century skills?

This course is developed in partnership with Microsoft as part of the Microsoft K-12 Education Leadership initiative, which aims to help K-12 school leaders drive the pursuit of ambitious instruction in classrooms. 

Beyond the straightforward transfer of facts and skills, ambitious instruction has teachers and students making meaning of rich academic content, engaging authentic practical and intellectual puzzles, and creating new knowledge and capabilities in themselves and others. Globally, ambitious instruction sits at the very center of policy-driven educational improvement efforts, with schools and systems pressed to engage students in "deeper learning" and the development of "21st-century skills."

This course is both for individual leaders and for teams of leaders from a school, district/region, or system who aim to improve educational opportunities and outcomes for students, especially those historically underserved by public schools. For these teams, the course will function as a platform both for initiating their joint practice and for collaborating on issues that arise in their joint practice.

Students will explore:

• The meaning and practice of ambitious instruction.
• The use of technology in ambitious instruction.
• Systemic supports for ambitious instruction.
• The practice of leading transformative change.

This course is part of the Leading Educational Innovation and Improvement MicroMasters Program offered by MichiganX.

This business and management course introduces students to an evidence-based management (EBM) framework that shows how maturity across six key domains is linked to improved leadership competency. The key domains are:

• Framing the problem (Ask);
• Gathering evidence (Acquire);
• Evaluating evidence (Appraise);
• Synthesizing findings (Aggregate);
• Implementation (Apply)
• Evaluating the outcomes (Assess).

Graduate business education has come under fire in recent years for not adequately preparing students for the challenge of managing in a complex, information-rich, and rapidly changing commercial environment. This was clearly demonstrated during the global financial crisis which exposed the inability of graduates from leading business schools to adapt what they had learnt to this new reality.

Evidence-based practice in management is a response to this situation. This business course focuses on exposing students to the latest academic thinking, while also equipping students to be critical and analytical thinkers that challenge established beliefs, and utilize the best available evidence to inform ethical decision making. Learn the EBM framework, how to analyze research, use critical thinking and more to make better business decisions.

The knowledge and skills developed in this course will prepare students to confront future business challenges. These business and management capabilities are critical for emerging leaders, established managers, and entrepreneurs.

This course provides the foundation for all other courses in the Evidence-Based Management MicroMasters Program.

The foundations of Algebra from The Khan Academy.