This course introduces three main types of partial differential equations: diffusion, elliptic, and hyperbolic. It includes mathematical tools, real-world examples and applications.

Developed by the NYCDOE CS education team, the Introduction to Physical Computing course is a 54-hour long introductory computer science course that guides students to explore fundamental CS concepts through tinkering with the micro:bit, a simple programmable computer device. Each unit of the course guides students through the learning process with three practices: analyzing computer applications around them based on a given issue; prototyping a project that reflects the result of the analysis plus their interest; and communicating about their projects, including the functionality of a project, a project development process, influence from other projects and their contribution to a project when working in a group. The curriculum and support sessions assist educators in discovering the most effective way of facilitating this course for their own classroom, while helping them to become comfortable with the main tool, the micro:bit.

This course is an introduction to software engineering, using the Java™ programming language. It covers concepts useful to 6.005. Students will learn the fundamentals of Java. The focus is on developing high quality, working software that solves real problems.

Comprehensive coverage of core concepts grounded in both classic studies and current and emerging research, including coverage of the DSM-5 in discussions of psychological disorders. Incorporates discussions that reflect the diversity within the discipline, as well as the diversity of cultures and communities across the globe.

The goal of this course is to give an undergraduate-level introduction to representation theory (of groups, Lie algebras, and associative algebras). Representation theory is an area of mathematics which, roughly speaking, studies symmetry in linear spaces.

Introduction to Solid State Chemistry is a first-year single-semester college course on the principles of chemistry. This unique and popular course satisfies MIT's general chemistry degree requirement, with an emphasis on solid-state materials and their application to engineering systems.

This course is a self-contained introduction to statistics with economic applications. Elements of probability theory, sampling theory, statistical estimation, regression analysis, and hypothesis testing. It uses elementary econometrics and other applications of statistical tools to economic data. It also provides a solid foundation in probability and statistics for economists and other social scientists.

This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed for further study of econometrics and provide basic preparation for 14.32. Topics include elements of probability theory, sampling theory, statistical estimation, and hypothesis testing.

This course covers descriptive statistics, the foundation of statistics, probability and random distributions, and the relationships between various characteristics of data. Upon successful completion of the course, the student will be able to: Define the meaning of descriptive statistics and statistical inference; Distinguish between a population and a sample; Explain the purpose of measures of location, variability, and skewness; Calculate probabilities; Explain the difference between how probabilities are computed for discrete and continuous random variables; Recognize and understand discrete probability distribution functions, in general; Identify confidence intervals for means and proportions; Explain how the central limit theorem applies in inference; Calculate and interpret confidence intervals for one population average and one population proportion; Differentiate between Type I and Type II errors; Conduct and interpret hypothesis tests; Compute regression equations for data; Use regression equations to make predictions; Conduct and interpret ANOVA (Analysis of Variance). (Mathematics 121; See also: Biology 104, Computer Science 106, Economics 104, Psychology 201)

The main goal of the course is to highlight the general assumptions and methods that underlie all statistical analysis. The purpose is to get a good understanding of the scope, and the limitations of these methods. We also want to learn as much as possible about the assumptions behind the most common methods, in order to evaluate if they apply with reasonable accuracy to a given situation. Our goal is not so much learning bread and butter techniques: these are pre-programmed in widely available and used software, so much so that a mechanical acquisition of these techniques could be quickly done "on the job". What is more challenging is the evaluation of what the results of a statistical procedure really mean, how reliable they are in given circumstances, and what their limitations are.Login: guest_oclPassword: ocl

Introduces topology, covering topics fundamental to modern analysis and geometry. Topological spaces and continuous functions, connectedness, compactness, separation axioms, and selected further topics such as function spaces, metrization theorems, embedding theorems, the Tychonoff theorem.

A 14 week Introduction to Computer Science course.
This course is targeted to middle school grades 6-8 (ages 11-14 years). It is also written for teachers who may not have a Computer Science background, or who may be teaching an “Intro to Computer Science” course for the first time.

This course takes approximately 14 weeks to complete, spending about 1 week on each of the first 11 lessons, and 3 weeks for students to complete the final project at the end. Of course, teachers should feel free to customize the curriculum to meet individual school or district resources and timeframe.

SFUSD's creative computing curriculum introduces computer science as a creative, collaborative, and engaging discipline to children in kindergarten through second grade.

Across 4 units and 15-20 lessons, students will learn about algorithms and programming, computing systems, the Internet, and impacts of computing, while developing strong practices and dispositions. Lessons are designed to be implemented in 45 to 60-minute periods approximately once per week.

This review course includes 600+ practice questions, plus instructional articles and videos covering the topics of computers, the Internet, programming, algorithms, and data analysis.

A student manual developed by the Utah State Board of Education, in cooperation with the Unified Police of Greater Salt Lake

LEGO® robotics uses LEGO®s as a fun tool to explore robotics, mechanical systems, electronics, and programming. This seminar is primarily a lab experience which provides students with resources to design, build, and program functional robots constructed from LEGO®s and a few other parts such as motors and sensors.

In this lesson, students will learn three different photo shooting skills: Silhouette, Shadows abd Reflection. At the same time, students will be taught how to use Chinese to describe a place they like. Then students needs to use one of photogtaphy skills to take a picture of  one place they went and they like, and describe the picture they took by using target language. All thumbnail iamges in this lesson plan are  images myself.