Online courses directory (29)

In this course you will learn how to conduct research using empirical methods, which rely on observation and experimentation. This course is appropriate for those interested in using empirical research methods in their field, particularly students in the social and behavioral sciences. Topics include the formulation of the question to be investigated and the of resulting hypotheses, the collection of data and the analysis of the data collected, and the interpretation and study of analysis results. We assume that learners entering Empirical Research Methods (ERM) have taken at least a semester or year-long course in statistics and, through this or some other experience, have been exposed to the following concepts: Random Variables Population and Samples Data Tables (rows=sample units and columns=variables) Summary Statistics: Mean, Median, Variance, Covariance, Correlation Graphs: Boxplots, Barcharts, Histograms, Scatterplots Inference: standard errors, confidence intervals, hypothesis tests, etc. Models: Bivariate Regression, perhaps ANOVA If learners have not had such exposure, they can follow the appropriate links into the OLI introductory statistics course to review the required concepts.

Programming is a way of organizing a task so that it is replicable by something elsea computer. If you have ever given someone directions, or written down a recipe, you have some experience with programming. Learning more about programming will help you develop the skills of thinking systematically about a task and breaking it down into manageable pieces, which can be applied in many disciplines. This class contextualizes the task of programming by focusing on media, such as images, audio, and interactive systems. By doing so, we hope to put programming in a relevant context. For example, iteration is a programming concept that is essential to creating negative and grayscale images. You will learn algorithms for blending two images together and how to hierarchical relationships are used to organize elements of a user interface. This introductory course has no particular prerequisites and is primarily designed for non-computer science students.

In this course, students learn to analyze and produce effective printed documents, such as technical reports, proposals, and software documentation. To guide their learning, students are introduced to the basics of visual communication design and typography through a series of audio-visual explanations that describe and illustrate key concepts and vocabulary, self-assessments that verify the understanding, and hands-on exercises with individualized feedback that provide opportunities to try out what they learned. Learning Objectives Concepts and vocabularyStudents will be able to use the basic concepts and vocabulary of visual communication design to describe the design of documents. AnalysisStudents will be able to recognize and articulate good and problematic aspects of documents. ProductionStudents will be able to use typographic variables appropriately to create effective documents Who should use this OLI course Students who are interested in improving their visual design skills for creating effective documents may find it helpful to use this OLI course. Instructors of a course that require students to create visual communication materials may find it helpful to integrate this OLI course into their existing courses as a supplemental learning tool. Estimated Time to Complete The entire course can be completed in about 2 to 3 hours.

This course will introduce students to the basic concepts and skills of evidence-based practice. The course is directly relevant to students who would like to improve the quality and outcome of their decision-making. Managers and consultants are required to take action based on their decisions, and such decisions may have profound impacts on employees, customers and clients, the organization and society more widely. But how good are such decisions? How can we ensure that managers and consultants get hold of, accurately interpret and make use of the best available evidence in their decision-making? This course will help students develop the practical skills managers and consultants need to bring evidence-based approaches to their organization. In the process of developing these skills you will also find out a lot about management research.

Created through a collaboration with the OPEN Platform+ program, The National STEM Consortium academic certificate in Cyber Technology is built on a 30-semester-credit model with learning outcomes mapped to the National Cybersecurity Workforce Framework [1]. Graduates are prepared for entry-level Cyber positions in across industry and in government, and have an opportunity to sit for nationally recognized certifications from Cisco and CompTIA. The National STEM Consortium (NSC) [2] is a collaborative of ten colleges in nine states, funded by a U.S. Department of Labor grant [3] to develop one-year, 30-credit certificate programs in five Science, Technology, Engineering, and Mathematics (STEM) fields: Composites Technology, Cyber Technology, Electric Vehicle Technology, Environmental Technology, and Mechatronics Technology. [ENTER PROGRAM] [4] [1] http://csrc.nist.gov/nice/framework/ [2] http://www.nationalstem.org [3] http://www.doleta.gov/taaccct/ [4] http://myeducationpath.com/HTTP://COMMUNITY.OLI.CMU.EDU/JCOURSE/WEBUI/GUEST/JOIN.DO?SECTION=CYBERTECH

This course provides an introduction to Python and elementary principles of computing, including iteration, recursion, and binary representation of data. Additional topics on cellular automata, encryption, and the limits of computation are also introduced. The goal of this course is to introduce some of the techniques used in computer science to solve complex problems, with or without a computer. The Python modules are used to introduce and illustrate conditionals and iteration; additional topics are provided without using a specific programming language and can be incorporated into classes that do not use Python.

This course provides an introduction to causal and statistical reasoning. After taking this course, students will be better prepared to make rational decisions about their own lives and about matters of social policy. They will be able to assess criticallyeven if informallyclaims that they encounter during discussions or when considering a news article or report. A variety of materials are presented, including Case Studies where students are given the opportunity to examine a causal claim, and the Causality Lab, a virtual environment to simulate the science of causal discovery. Students have frequent opportunities to check their understanding and practice their skills. This course is meant to serve students in several situations. One, it is meant for students who will only take one such research methods course, and are interested in gaining basic skills that will help them to think critically about claims they come across in their daily lives, such as through a news article. Two, it is meant for students who will take a few statistics courses in service of a related field of study. Three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks.

This course presents material in discrete mathematics and computation theory with a strong emphasis on practical algorithms and experiential learning. Discrete mathematics, also called finite mathematics or decision mathematics, is the study of mathematical structures that are fundamentally discrete in the sense of not supporting or requiring the notion of continuity. Objects studied in finite mathematics are largely countable sets such as integers, finite graphs, and formal languages. Concepts and notations from discrete mathematics are useful to study or describe objects or problems in computer algorithms and programming languages. The CDM course is currently under development and we are making the course available while it is under development. Only one of the planned fifteen modules is currently available. The module on Groups that is currently available would appear mid-way through the complete course.

This course offers an overview of healthcare, health information technology, and health information management systems. The focus is on the role and responsibilities of entry-level health IT specialists in each phase of the health information management systems lifecycle. The curriculum is aligned to the new Certified Associate in Healthcare Information and Management Systems (CAHIMS) [1] certification administered by the Healthcare Information and Management Systems Society. This certificate is designed for students who have previous experience in IT or healthcare and it is designed to serve as a pathway into health IT careers. This course is a collaborative effort of TAACCCT grantees, in particular Bellevue Colleges and MoHealthWINs. The collaborative partners supporting the development of this course are Open Learning Initiative (OLI) at Stanford University and Carnegie Mellon University, Center for Applied Science and Technology (CAST), and Creative Commons (CC)- all funded through the Gates foundation OPEN Grant. The core development team includes content experts, learning scientists, software developers, instructional designers, universal design for learning experts and instructional technologists. [1] http://www.himss.org/health-it-certification/cahims?navItemNumber=13646