Online courses directory (19947)

Lecture Series on Mathematics - III by Prof.P.N.Agarwal, Department of Mathematics, IIT Roorkee.

Lecture Series on Probability and Random Variables by Prof. M. Chakraborty, Department of Electronics and Electrical Com

Lecture Series on Digital Image Processing by Prof. P.K. Biswas , Department of Electronics & Electrical Communicati

Lecture Series on Robotics by Prof. C. Amarnath, Prof. B. Seth, Prof. K. Kurien Issac, Prof. P. S. Gandhi, Prof. P. Sesh

In this course you will learn about the  different experiences patients go through in a medical context. The patient journey explores the interaction between the patient and the healthcare providers in all stages of the disease; coping with treatment and dealing with expectations, and interaction with and between different stakeholders.

This course will give designers and specialists in healthcare the knowledge, insights and tools to be able to analyze and improve patient experience. You will learn how to map complex healthcare scenarios, pinpoint opportunities and create hands-on solutions aimed at improving the patient experience.  

This course is an introduction to patient journey mapping; developed at the Delft University of Technology and applied in improvement of care pathway. Step-by-step, the course visualizes the different stakeholders, phases and actions involved in patient treatment. You will be challenged to pursue new insights and given unique opportunities to learn, observe and question patients and medical professionals, with the opportunity to attend a live broadcasted, interactive surgery.

No previous knowledge about health care innovation, design or journey mapping is necessary.

LICENSE

The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.

This course is designed to provide future STEM faculty, graduate students and post-doctoral fellows with an introduction to effective teaching strategies and the research that supports them.

The goal of the eight-week course is to equip the next generation of STEM faculty to be effective teachers, thus improving the learning experience for the thousands of students they will teach.

The course draws on the expertise of experienced STEM faculty, educational researchers, and staff from university teaching centers, many of them affiliated with the Center for the Integration of Research, Teaching, and Learning (CIRTL), a network of research universities collaborating in the preparation of STEM graduate students and post-docs as future faculty members.

Our capacity to collect and store data has exponentially increased, but deriving information from data from a scientific perspective requires a foundational knowledge of probability.

Are you interested in a career in the emerging data science field, or as an actuarial scientist? Or want better to understand statistical theory and mathematical modeling?

In this statistics and data analysis course, we will provide an introduction to mathematical probability to help meet your career goals in the exciting new areas becoming known as information science.

In this course, we will first introduce basic probability concepts and rules, including Bayes theorem, probability mass functions and CDFs, joint distributions and expected values.

Then we will discuss a few important probability distribution models with discrete random variables, including Bernoulli and Binomial distributions, Geometric distribution, Negative Binomial distribution, Poisson distribution, Hypergeometric distribution and discrete uniform distribution.

To continue learning about probability, enroll in Probability: Distribution Models & Continuous Random Variables, which covers continuous distribution models, central limit theorem and more.

 
The Center for Science of Information, a National Science Foundation Center, supports learners by offering free educational resources in information science.

The course, ME 599: Nanomanufacturing taught by Professor John Hart at the University of Michigan, discusses the propert

Chemical Engineering (E20) is an introductory course offered by the Stanford University Engineering Department. It provi

Bioengineering at MIT is represented by the diverse curricula offered by most Departments in the School of Engineering.

Lectures on Satellite Communications, Satellite Technology, Satellite Components and Satellite Systems

Course on Basics of Nuclear Power Generation, Nuclear Fission, Nuclear Power Plants and Nuclear Thermodynamics Principle

Lecture Series on Transportation Engineering - II by Dr.Rajat Rastogi, Department of Civil Engineering, IIT Roorkee.

In this statistics and data analysis course, you will learn about continuous random variables and some of the most frequently used probability distribution models including, exponential distribution, Gamma distribution, Beta distribution, and most importantly, normal distribution.

You will learn how these distributions can be connected with the Normal distribution by Central limit theorem (CLT). We will discuss Markov and Chebyshev inequalities, order statistics, moment generating functions and transformation of random variables.

This course along with the recommended pre-requisite, Probability: Basic Concepts & Discrete Random Variables, will you give the skills and knowledge to progress towards an exciting career in information and data science.

 
The Center for Science of Information, a National Science Foundation Center, supports learners by offering free educational resources in information science.

In order to be competitive in the computer science field, it’s imperative to understand the basic building blocks of a modern computer and how they directly impact the speed and efficiency of a program. Whether you work with embedded systems, mobile computer-based systems, or cloud systems, performance and energy efficiency are key drivers of usability and competitiveness of computerized products.

In this course, you will learn how to design modern multicore-based computers, and how the design choices you make affect performance and energy consumption. You will explore design principles governing modern microprocessors, such as pipelining and cache memories, as well as methods for determining the impact of your design on execution time and energy efficiency.

These skills can make a difference for practicing engineers for the purpose of building highly competitive products. Take, for instance, a smartphone with limited battery capacity. By adding value to end users through new or improved functionality, this can lead to significantly shorter operation time between battery charges, thus utilizing the already limited resources of a smartphone far more efficiently.

With this skillset, you can become an expert in computer system performance and energy efficiency - knowledge that is in high demand when designing computerized embedded products. With trends towards IoT (Internet of Things), autonomous systems and mobile computers, such a skillset will be critical in a career in systems engineering.

This course is derived from a Chalmers senior undergraduate course in computer system design. It assumes basic knowledge in computer organization.

Comment l’eau de pluie s'infiltre-t-elle dans le sol (et quelle partie ruisselle) ? Quelle est la recharge d’une nappe ? Quelle quantité d’eau un sol peut-il retenir ? Quelle sont les directions des flux de polluants dans un sol ?

Ce cours vous donnera les clés pour comprendre, modéliser et mesurer les processus de transferts de l’eau dans le sol.

Il s’adresse aux ingénieurs, techniciens et étudiants désireux d'accroître ou de rafraîchir leurs connaissances dans le domaine de l’hydrodynamique des sols, pour des applications aussi diverses que l’agronomie, l’environnement, l’irrigation ou la mécanique des sols.

Ce cours sera donné par des experts de différents domaines liés à cette thématique. Il vous permettra d’acquérir les bases nécessaires à l’utilisation d’outils de modélisation hydrologique, d’irrigation, ou de pollution diffuse.

En collaboration avec

Lecture Series on Performance of Marine Vehicles At Sea by Prof.S. C. Misra and Prof.D.Sen, Department of Ocean Engineer

Lecture Series on Analog ICs by Prof. K.Radhakrishna Rao , Department of Electrical Engineering,I.I.T.Madras.

Lectures by Prof. K. N. BhatrnDepartment of Electrical EngineeringrnIIT Madras

Lecture Series on Materials Science by Prof.SK. Gupta, Department of Applied Mechanics ,IIT Delhi.