Online courses directory (29)

This course covers specialized and somewhat advanced topics in the fields of cellular biology, molecular biology, biochemistry, and genetics. It does not cover organismal biology or taxonomy. The course is carefully planned to provide the background that biology students will need for advanced biology classes. Non-biology majors will also find this course useful as it explains many of the concepts and techniques currently discussed in the popular press. This course is built around six key concepts that provide unifying explanations for how and why structures are formed and processes occur throughout your study of biology. Because it is not possible to cover the breadth of modern molecular biology in one semester, an understanding of these key concepts will provide a basis for extension of your knowledge to biological systems beyond the specifics covered in this course. One of the major goals of the course therefore is for you to not only learn the definitions of the concepts but also learn to recognize when they are operating the process being studied.

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 teaches the core principles of economics using a collection of experiments and workbooks. In the experiments, students become traders in a market and attempt to make profitable deals with one another. At the conclusion of the experiment, the data are used to form a customized, online workbook. Each workbook guides the student through the analysis of the experiment’s outcome, while simultaneously presenting the key ideas and core principles in economics needed to gain a deeper understanding of both the experiment and economic life. In these experiments the student is both a participant and an observer. As a participant, the student experiences first hand the issues that all economic agents must confront; as an observer, the student sees how modern economic theory can explain the complex interactions that occur in both the experiments, and the economic world at large. Students often report that they learn nearly as much about economic principles from their experience as a participant as they do from their analysis of the experiment as an observer. Students learning on their own or in small classes (generally fewer than 10 students) can still use the workbooks, but will be given synthetic data. Small numbers of students participating in experiments does not yield enough data for the workbooks.

This course introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. In addition, the course helps students gain an appreciation for the diverse applications of statistics and its relevance to their lives and fields of study. The course does not assume any prior knowledge in statistics and its only prerequisite is basic algebra. We offer two versions of statistics, each with a different emphasis: Probability and Statistics and Statistical Reasoning. Each course includes all expository text, simulations, case studies, comprehension tests, interactive learning exercises, and the StatTutor labs. Each course contains all of the instructions for the four statistics packages options we support. To do the activities, you will need your own copy of Microsoft Excel, Minitab, the open source R software, TI calculator, or StatCrunch. One of the main differences between the courses is the path through probability. Probability and Statistics includes the classical treatment of probability as it is in the earlier versions of the OLI Statistics course.

This course is designed to help students (primarily incoming college freshmen) develop the foundational computing and information literacy skills that they will need to succeed in other courses. The course is available for use in academic settings.

An ongoing development effort in collaboration with the Software Engineering Institute’s CERT [1], this course focuses on common security issues in C and C++ development. With security expert Robert Seacord serving as lead content author, the course addresses a key need in professional education for software developers. Topics to be covered include the secure and insecure use of integers, arrays, strings, dynamic memory, formatted input/output functions, and file I/O. Continued development is being funded by partnerships with industry. [1] http://www.cert.org/

Statistical Reasoning introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. In addition, the course helps students gain an appreciation for the diverse applications of statistics and its relevance to their lives and fields of study. The course does not assume any prior knowledge in statistics and its only prerequisite is basic algebra. We offer two versions of statistics, each with a different emphasis: Probability and Statistics and Statistical Reasoning. Each course includes all expository text, simulations, case studies, comprehension tests, interactive learning exercises, and the StatTutor labs. Each course contains all of the instructions for the four statistics packages options we support. To do the activities, you will need your own copy of Microsoft Excel, Minitab, the open source R software, TI calculator, or StatCrunch. One of the main differences between the courses is the path through probability; Statistical Reasoning places less emphasis on probability than does the Probability and Statistics course and takes an empirical approach.

The STEM Readiness course provides a refresher of core skills related to STEM careers. The core skills covered are Mathematics from arithmetic to beginning algebra, Workplace Communications and Professionalism. The topics of the course are presented through workplace scenarios to show learners how these skills apply to their potential careers. In reviewing these core skills students will be better prepared to be successful in post-secondary STEM related technical programs and ultimately in STEM related careers.