Science Courses and Tutorials
Science education websites including university courses online, massive open online courses, and tutorials. No commercial sites.
344 listings
Submitted Dec 21, 2016 to Science Courses and Tutorials This tutorial shows how to acquire earthquake waveforms from data centers. The data centers are used to provide SEED volumes for regional moment tensor inversion.
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Submitted Dec 21, 2016 to Science Courses and Tutorials Data science companies are increasingly looking at portfolios when making hiring decisions. One of the reasons for this is that a portfolio is the best way to judge someone’s real-world skills. The good news for you is that a portfolio is entirely within your control. If you put some work in, you can make a great portfolio that companies are impressed by.
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Submitted Dec 21, 2016 to Science Courses and Tutorials Fast.ai's 7 week course, "Practical Deep Learning For Coders, Part 1" is taught by Jeremy Howard (Kaggle's #1 competitor 2 years running, and founder of Enlitic). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free!
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Submitted Dec 10, 2016 to Science Courses and Tutorials This course provides an elementary introduction to probability and statistics with applications. Topics include: basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.
The Spring 2014 version of this subject employed the residential MITx system, which enables on-campus subjects to provide MIT students with learning and assessment tools such as online problem sets, lecture videos, reading questions, pre-lecture questions, problem set assistance, tutorial videos, exam review content, and even online exams. |
Submitted Dec 10, 2016 (Edited Dec 30, 2016) to Science Courses and Tutorials We all had dreams of what we wanted to be when we were younger. But how many of us grow up to achieve what the childhood versions of ourselves set out to be? Millions of people want to go to space, but only thousands have ever been. Scientists and doctors are never far from the list of what people want to be when they grow up, but only a small percent ever get there. So what advice would you give to a young teenager, at the start of their life, who wants to become an astronaut or an astrophysicist? We get our chance on today's Ask Ethan.
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Submitted Dec 08, 2016 to Science Courses and Tutorials Taught by Neil Gershenfeld of the MIT Media Lab.
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Submitted Dec 05, 2016 (Edited Dec 05, 2016) to Science Courses and Tutorials A Columbia University Lede Program presented in Summer 2015.
Consideration of both the scientific and social implications of counting, of turning the world into bits. Through the process of gaining fluency in the use of Python, students will spend some time thinking through representations of core "data types" like time, location, text, image, sound and relationships (or networks), and the computational "affordances" associated with each. Students will study several common metaphors for organizing and storing data – from structureless key-value stores, to document collections like MongoDB, to a single table or spreadsheet, to the "multiple tables" of a relational database. We will also discuss ideas behind publishing or sharing data, moving from HTML documents and Web 1.0 to data services and APIs in Web 2.0, to semantics in Web 3.0. These efforts will be project-driven, with students using and building modern data services with a scripting language. Their projects will underscore the reality that data are plentiful and circulate and interact in a kind of informational ecosystem. As researchers, our students will be called on both to access and to publish data products. |
Submitted Dec 04, 2016 to Science Courses and Tutorials OCW makes JHSPH course materials used in the teaching of actual courses freely and openly available on the Web. You may share and adapt the materials on OCW under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.
JHSPH sees OCW as an important component of the School’s mission (Protecting Health, Saving Lives - Millions at a Time). OCW is true to JHSPH's values of excellence, innovation and leadership. JHSPH OCW contributes to the "shared intellectual commons" in academia, which fosters collaboration across JHSPH and among other scholars across disciplines and around the world. |
Submitted Dec 04, 2016 to Science Courses and Tutorials Have you ever wondered how:
atoms tell time? antennas form beams? metamaterials cloak? errors depend on power? information is measured? semiconductors switch? magnets levitate? spins are imaged? quantum states are teleported? computers can operate reversibly? adiabatically? stochastically? MAS.862 will provide answers to these and many other questions, through a survey of the theoretical foundations and device mechanisms used in information technologies. |
Submitted Dec 04, 2016 to Science Courses and Tutorials This course attempts to explain the role and the importance of the financial system in the global economy. Rather than separating off the financial world from the rest of the economy, financial equilibrium is studied as an extension of economic equilibrium. The course also gives a picture of the kind of thinking and analysis done by hedge funds.
This Yale College course, taught on campus twice per week for 75 minutes, was recorded for Open Yale Courses in Fall 2009. |
Submitted Dec 04, 2016 to Science Courses and Tutorials This is a course in Java programming for beginners. It covers the fundamentals of programming, roughly the same material that is covered in a beginning programming course in a university or in a high school AP Computer Science course.
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Submitted Dec 04, 2016 to Science Courses and Tutorials Course content for CPSC 314, Introduction to Computer Graphics, University of British Columbia. Taught in Winter 2015-2016 by Tamara Munzer. Includes animation, digital geometry, and visualization.
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Submitted Dec 04, 2016 to Science Courses and Tutorials Videos, course notes, and code from a one-day workshop taught by Gene Kogan at ITP-NYU in Spring 2016. Sections cover neural networks, convolutional and recurrent neural networks, game AI and deep reinforcement learning, transfer learning, and more.
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Submitted Dec 02, 2016 to Science Courses and Tutorials <img src="http://www.elementlist.com/images/astro162.gif" alt="astronomy" width="132" height="84" align="right" border="0">In our first semester of astronomy we were concerned primarily with our own Solar System. In this semester we broaden our perspective and consider the entire Universe. Much of the material for this semester is already on the Web at the Violence in the Cosmos site, but it is arranged in a different order than it will be when the following sequence is completed.
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Submitted Dec 02, 2016 to Science Courses and Tutorials World Wide Web, blogging platforms, instant messaging and Facebook can be characterized by the interplay between rich information content, the millions of individuals and organizations who create and use it, and the technology that supports it.
The course will cover recent research on the structure and analysis of such large social and information networks and on models and algorithms that abstract their basic properties. Class will explore how to practically analyze large scale network data and how to reason about it through models for network structure and evolution. Topics include methods for link analysis and network community detection, diffusion and information propagation on the web, virus outbreak detection in networks, and connections with work in the social sciences and economics. |
Submitted Dec 02, 2016 to Science Courses and Tutorials An advanced, 10-session course on reinforcement learning taught by David Silver.
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Submitted Dec 02, 2016 to Science Courses and Tutorials Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc. There are a large variety of underlying tasks and machine learning models powering NLP applications. Recently, deep learning approaches have obtained very high performance across many different NLP tasks. These models can often be trained with a single end-to-end model and do not require traditional, task-specific feature engineering. In this spring quarter course students will learn to implement, train, debug, visualize and invent their own neural network models. The course provides a deep excursion into cutting-edge research in deep learning applied to NLP. The final project will involve training a complex recurrent neural network and applying it to a large scale NLP problem. On the model side we will cover word vector representations, window-based neural networks, recurrent neural networks, long-short-term-memory models, recursive neural networks, convolutional neural networks as well as some very novel models involving a memory component. Through lectures and programming assignments students will learn the necessary engineering tricks for making neural networks work on practical problems.
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Submitted Jun 28, 2010 to Science Courses and Tutorials ![]() |
Submitted Dec 13, 2009 to Science Courses and Tutorials This online edition of a 1955 pamphlet by Seville Chapman covers many of the essential elements of what is needed to study and be successful at university-level physics, including how to take good notes, how to work problems, and how to study for exams.
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Submitted Dec 12, 2009 to Science Courses and Tutorials This website is for people involved in applied social research and evaluation. You'll find lots of resources and links to other locations on the Web that deal in applied social research methods. This site includes an online textbook of social research methods, including statistics, research design, and data analysis.
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