Courses tagged with "Structural engineering" (124)

This course covers the physics, concepts, theories, and models underlying the discipline of aerodynamics. A general theme is the technique of velocity field representation and modeling via source and vorticity fields, and via their sheet, filament, or point-singularity idealizations.

The intent is to instill an intuitive feel for aerodynamic flowfield behavior, and to provide the basis of aerodynamic force analysis, drag decomposition, flow interference estimation, and many other important applications. A few computational methods are covered, primarily to give additional insight into flow behavior, and to identify the primary aerodynamic forces on maneuvering aircraft. A short overview of flight dynamics is also presented.

Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.

FAQ

Is there a required textbook?
You do not need to buy a textbook. All material is included in the edX course and is viewable online. This includes a full textbook in PDF form. If you would like to buy a print copy of the textbook, a mail-order service will be provided.

Can I still register after the start date?
You can register at any time, but you will not get credit for any assignments that are past due.

How are grades assigned?
Grades are made out of four parts: simple, multiple-choice "Concept Questions " completed during lectures; weekly homework assignments; and two exams, one at the midpoint and one at the end of the course.

How does this course use video? Do I need to watch the lectures live?
Video lectures as well as worked problems will be available and you can watch these at your leisure. Homework assignments and exams, however, will have due dates.

Will the text of the lectures be available?
Yes, transcripts of the course will be made available.

Will the material be made available to anyone registered for this course?
Yes, all the material will be made available to all students.

What are the prerequisites?
The student is expected to be well-versed in basic mechanics, vector calculus, and basic differential equations. Good familiarity with basic fluid mechanics concepts (pressure, density, velocity, stress, etc.) is expected, similar to the content in 16.101x (however, 16.101x is not a requirement). If you do not know these subjects beforehand, following the class material will be extremely difficult. We do not check students for prerequisites, so you are certainly allowed to try.

Who can register for this course?
Unfortunately, learners from Iran, Sudan, Cuba and the Crimea region of Ukraine will not be able to register for this course at the present time. While edX has received a license from the U.S. Office of Foreign Assets Control (OFAC) to offer courses to learners from Iran and Sudan our license does not cover this course. Separately, EdX has applied for a license to offer courses to learners in the Crimea region of Ukraine, but we are awaiting a determination from OFAC on that application. We are deeply sorry the U.S. government has determined that we have to block these learners, and we are working diligently to rectify this situation as soon as possible.

In this first part of a two part course, we’ll walk through the basics of statistical thinking – starting with an interesting question. Then, we’ll learn the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

This course will consist of:

• Instructional videos for statistical concepts broken down into manageable topics
• Guided questions to help your understanding of the topic
• Weekly tutorial videos for using R Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets
• Weekly wrap-up questions challenging both topic and application knowledge

We will cover basic Descriptive Statistics – learning about visualizing and summarizing data, followed by a “Modeling” investigation where we’ll learn about linear, exponential, and logistic functions. We will learn how to interpret and use those functions with basic Pre-Calculus. These two “units” will set the learner up nicely for the second part of the course: Inferential Statistics with a multiple regression cap.

Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).

With these new skills, learners will leave the course with the ability to use basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). Learners from all walks of life can use this course to better understand their data, to make valuable informed decisions.

Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?

In the second part of a two part statistics course, we’ll learn how to take data and use it to make reasonable and useful conclusions. You’ll learn the basics of statistical thinking – starting with an interesting question and some data. Then, we’ll apply the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

We will cover basic Inferential Statistics – integrating ideas of Part 1. If you have a basic knowledge of Descriptive Statistics, this course is for you. We will learn how to sample data, examine both quantitative and categorical data with statistical techniques such as t-tests, chi-square, ANOVA, and Regression.

Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).

This course will consist of:

• Instructional videos for statistical concepts broken down into manageable topics
• Guided questions to help your understanding of the topic
• Weekly tutorial videos for using R
• Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets
• Weekly wrap-up questions challenging both topic and application knowledge

With these new skills, learners will leave the course with the ability to use basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). Learners from all walks of life can use this course to better understand their data, to make valuable informed decisions.

Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?

Prime numbers are one of the most important subjects in mathematics. Many mathematicians from ancient times to the 21st century have studied prime numbers.

In this math course, you will learn the definition and basic properties of prime numbers, and how they obey mysterious laws. Some prime numbers were discovered several hundred years ago whereas others have only been proven recently. Even today, many mathematicians are trying to discover new laws of prime numbers.

Calculating by a pen and paper, you will explore the mysterious world of prime numbers. Join us as we tackle math problems, and work together to discover new laws on prime numbers. Let's study and have fun!

Quantitative Methods in Clinical and Public Health Research is the online adaptation of material from the Harvard T.H. Chan School of Public Health's classes in epidemiology and biostatistics. Principled investigations to monitor and thus improve the health of individuals are firmly based on a sound understanding of modern quantitative methods. This involves the ability to discover patterns and extract knowledge from health data on a sample of individuals and then to infer, with measured uncertainty, the unobserved population characteristics. This course will address this need by covering the principles of biostatistics and epidemiology used for public health and clinical research. These include outcomes measurement, measures of associations between outcomes and their determinants, study design options, bias and confounding, probability and diagnostic tests, confidence intervals and hypothesis testing, power and sample size determinations, life tables and survival methods, regression methods (both, linear and logistic), and sample survey techniques. Students will analyze sample data sets to acquire knowledge of appropriate computer software. By the end of the course the successful student should have attained a sound understanding of these methods and a solid foundation for further study.
 

FAQ

How much does it cost to take the course?
Nothing! The course is free.

When will assignments be due?
The course is organized into weeks, and each week will have its own set of assignments. Students will be expected to complete their homework each week.

Do I need any other materials to take the course?
Nope, as long as you’ve got a Mac or PC, you’ll be ready to take the course.

Will the course use any textbooks or software?
Yes! We'll have free access to the book "Principles of Biostatistics" written by Marcello Pagano (one of the Professors) and Kimberlee Gauvreau.

In addition to the textbook, we'll use Stata (a piece of software for doing statistical analysis).

Thanks to our friends at Statacorp, we'll have free copies of Stata available for all students to use for the duration of the course (Mac and PC only).

Do I need to watch the lectures live?
No. You can watch the lectures at your leisure.

Will certificates be awarded?
Yes. Online learners who achieve a passing grade in a course can earn a certificate of achievement. These certificates will indicate you have successfully completed the course, but will not include a specific grade. Certificates will be issued by edX under the name of either HarvardX, MITx or BerkeleyX, designating the institution from which the course originated. For the courses in Fall 2012, honor code certificates will be free.

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code : https://www.edx.org/edx-terms-service. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement : http://harvardx.harvard.edu/research-statement to learn more.

Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form : https://www.edx.org/contact-us.

Are you thinking about teaching high school math? Learning how to implement effective teaching strategies is essential to creating a successful environment for both you and your students. In this education and teacher training course, you will learn, from experts at Teach for America, how to teach introductory fundamental geometry concepts and empower students to explore math on their own.

You will have the opportunity to engage in creative teaching practices and learn new ways to imagine and visualize approaches for teaching geometry. You will also learn best practices to better support student learning in a math classroom. If you are preparing for or considering teaching geometry, this course will be ideal for you as you explore effective classroom instructional strategies, operations and better understand the foundational content you will teach in a high school geometry class across diverse student communities.

This course includes a weekly module that covers teaching strategies while also introducing commonly taught high school geometry content including:

• segment/angle addition
• basic and parallel/transversal line angle
• angle relationships
• perpendicular and parallel linear equations

You can jump between lessons to quickly review geometry content and classroom strategies relevant to your learning interests. This course covers geometry curriculum typically covered in high school classroom and Common Core State Standards (CCSS) alignment is indicated where applicable. No prerequisite knowledge is required, however, basic algebra skills will be useful (as well as a strong desire to make an engaging and inclusive geometry class)!

Want to be the programmer hot tech companies are looking for?

Take your programming skills to the next level and prove your excellence by learning how to succeed in programming competitions.

Besides improving your knowledge of algorithms and programming languages, you’ll gain unique experience in problem solving, thinking outside the box and meeting tough deadlines – all essential for boosting your value as a programmer and securing a coveted job in Silicon Valley (should you want one).

This computer science course is an introduction to competitive programming developed by ITMO University, the leading expert in IT and the only 6-time world champion of the Association for Computing Machinery - International Collegiate Programming Contest (ACM ICPC), the world's most prestigious programming contest.

You will learn all you need to know about the variety of programming competitions that exist, as well as basic algorithms and data structures necessary to succeed in the most popular of them.

When you meet a new person, it is hard to know what to expect.  You may not be able to read the person or understand what they mean. Even if you want to have a good relationship with them, this lack of understanding can make interactions tense, unpredictable and scary! The same is true for a lot of people as they encounter statistics and mathematical ways of working with data.  Statistics can be confusing and opaque.  Symbols, Greek letters, very large and very small numbers, and how to interpret all of this can leave to feeling cold and disengaged—even fearful and resentful.

But in the modern information age, having a healthy relationship with statistics can make life a whole lot easier. We are constantly faced with an onslaught of data and claims about it—from news articles, to Facebook and blog posts, casual and professional conversations, reports at our workplace, advertising, and claims from politicians and public officials. How can we process that information, make sense of it, evaluate truth claims, and put ourselves in a position to act on the information?  One of the most important ways is by befriending statistics and consistently using statistical ways of thinking.
 
The purpose of this course, then is to help you develop a functional, satisfying, and useful life-long relationship with statistics. To achieve that goal, we will take a non-technical approach—you will learn how statistics work and why they are so helpful in evaluating the world of information that is around us. You will learn about the logic of statistical thinking and the concepts (rather than the mathematical details and probability theory) that guide statistical inferences and conclusions.
 
You do not need to be a math whiz to take this course. If you can add, subtract, multiply, and divide (or just be able to use a calculator to do that!), you will be more than able to handle what will happen as this relationship develops.

By the end of the course you will be able to:

• Identify the most important features of a data set
• Select a statistical test based on the features of the data
• Think like a statistical detective
• Understand the relationship between two different characteristics or variables
• Perform some simple statistical calculations and draw some conclusions from real data
• Hopefully, love stats! 

We’ll do all of this using entertaining examples related to real-life situations we all encounter in everyday life.

Comment étudier l'Univers dans lequel nous vivons en utilisant la seule information qu'il nous envoie: la lumière ? Ce cours donne un aperçu des phénomènes physiques qui se cachent derrière les objets astronomiques qui nous entourent, des planètes et des étoiles jusqu'aux filaments cosmiques, en passant par les galaxies comme notre Voie Lactée et les amas de galaxies. Le cours met l'accent sur le lien entre les prédictions théoriques et les observations et constitue la base indispensable des cours d'astrophysique avancés.

Actuary is rated the best job of 2015 by CareerCast.com because it pays well and offers abundant opportunities for advancement. 

You may have heard of actuarial science, or you might even know an actuary, but do you know what an actuary does? During the course you’ll hear from a wide variety of actuaries about their careers.

And don’t be scared that the course will be “just a whole lot of mathematics”. Together, we will go beyond the math to learn how actuaries approach problems relating to risk, using examples from:

• Finance
• Investments
• Banking
• Insurance

You will learn how actuarial science applies mathematical and statistical methods to assess risk in these industries and other professions.

You’ll experience “hands-on” learning using Excel (or an equivalent spreadsheet tool) to project and investigate the financial condition of a company choosing appropriate strategies for the company through the use of simulations.

The course has been carefully designed for students from a wide variety of backgrounds, with secondary/high school level being the only assumption of mathematical background. Even if you don’t have any background in, for example, calculus, the course has been designed so you can skip over these sections without affecting your understanding of the rest of the course. You also do not need to have any Excel or other spreadsheet background to take the course.

For those with stronger mathematical backgrounds, extension questions are provided to test you further. You’ll learn a huge amount about actuarial science no matter what your background is!

Join us today. To connect with the course community before and during the course, join our Facebook group, and tweet us with #actuarialedX.

"Great introduction to this specialized field; every day there are new challenges where as a student you are put in a situation to learn and apply the lessons with practical exercises. Great structure of the course, with main concepts to review at the end of a lesson. I would recommend to anyone who would like to learn more about actuarial science." - Previous student

We live in a world of numbers. You see them every day: on clocks, in the stock market, in sports, and all over the news. Algebra is all about figuring out the numbers you don't see. You might know how fast you can throw a ball, but can you use this number to determine how far you can throw it? You might keep track of stock prices, but how can you figure out how much money you've made (or lost) in the market? And you may already know how to tell time, but can you calculate at what times a clock's hour and minute hands are exactly aligned? With algebra, you can answer all of these questions, using the numbers you already know to solve for the unknown. Algebra is an essential tool for all of high school and college-level math, science, and engineering. So if you're starting out in one of these fields and you haven't yet mastered algebra, then this is the course for you!
 
In this course, you'll be able to choose your own path within each lesson, and you can jump between lessons to quickly review earlier material. AlgebraX covers a standard curriculum in high school Algebra I, and CCSS (common core) alignment is indicated where applicable.

Learn more about our High School and AP* Exam Preparation Courses

Have you wondered about the design strategies behind temperature controllers, quad-copters, or self-balancing scooters? Are you interested in robotics, and have heard of, or tried, “line-following" or “PID control” and want to understand more?

Feedback control is a remarkably pervasive engineering principle. Feedback control uses sensor data (e.g. brightness, temperature, or velocity) to adjust or correct actuation (e.g. steering angle, motor acceleration, or heater output), and you use it all the time, like when you steer a bicycle, catch a ball, or stand upright. But even though applications of feedback are very common, the subject is an uncommonly compelling example of mathematical theory guiding practical design. In this engineering course we will introduce you to the theory and practice of feedback control and provide a glimpse into this rich and beautiful subject.

Each week we will begin with a mathematical description of a fundamental feedback concept, combined with on-line exercises to test your understanding, and will finish with you designing, implementing, measuring, and analyzing a hardware system, that you build, for controlling a propeller-levitated-arm feedback system.

You will not need a background in calculus or software engineering to succeed in this class but you should be familiar with algebra and mechanical forces, have some exposure to complex numbers, and be comfortable with modifying mathematical formulas in short computer programs.

This is a lab course, and in order to complete the weekly assignments, you will need to purchase/acquire a list of parts. To make sure you receive your parts before the class begins, you should register promptly, so that you can access the lists of parts and international vendors.

Phenomena as diverse as the motion of the planets, the spread of a disease, and the oscillations of a suspension bridge are governed by differential equations.MATH226x is an introduction to the mathematical theory of ordinary differential equations. This course follows a modern dynamical systems approach to the subject. In particular, equations are analyzed using qualitative, numerical, and if possible, symbolic techniques.

MATH226 is essentially the edX equivalent of MA226, a one-semester course in ordinary differential equations taken by more than 500 students per year at Boston University. It is divided into three parts. MATH226.1 is the first of these three parts.

In MATH226.1, we will discuss biological and physical models that can be expressed as differential equations with one or two dependent variables. We will discuss geometric/qualitative and numerical techniques that apply to all differential equations. When possible, we will study some of the standard symbolic solution techniques such as separation of variables and the use of integrating factors. We will also study the theory of existence and uniqueness of solutions, the phase line and bifurcations for first-order autonomous systems, and the phase plane for two-dimensional autonomous systems. The techniques that we develop will be used to analyze models throughout the course.

For additional information on obtaining credit through the ACE Alternative Credit Project, please visit here.

How do you design:

• A boat that doesn’t tip over as it bobs in the water?
• The suspension system of a car for a smooth ride?
• Circuits that tune to the correct frequencies in a cell phone?

How do you model:

• The growth of antibiotic resistant bacteria?
• Gene expression?
• Online purchasing trends?

The answer: Differential Equations.

Differential equations are the language of the models we use to describe the world around us. In this mathematics course, we will explore temperature, spring systems, circuits, population growth, and biological cell motion to illustrate how differential equations can be used to model nearly everything in the world around us.

We will develop the mathematical tools needed to solve linear differential equations. In the case of nonlinear differential equations, we will employ graphical methods and approximation to understand solutions.

Photo by user: bizoo_n. Copyright © 2016 Adobe Systems Incorporated. Used with permission.

The goal of this course is to provide high school students and college freshman a broad outline of engineering and help them decide on a career in engineering. The course explores the different disciplines of engineering and providing participants with a broad background in different areas of engineering.

Do you want to learn how race-cars are built? How robots are able to work independently? How is energy harvested? How is energy stored? How are organs built? How is the body imaged? How do you design an aircraft? How do electrons travel in micro and nanoelectronics? How are drugs delivered in the body? How do you build on soils that are unstable? How do robots see? How is light used in devices? How is data stored and managed? How is pollution mitigated? How are electrical signals processed? How are strong and tough materials designed and built? How is thermal energy managed? How is data transmitted? How are systems integrated? How do you make sure goods and services reach their destination? These are all things that engineers are dealing with on a daily basis and will form the basis of the first part of the course.

The goal of this mathematics course is to provide high school students and college freshmen an introduction to basic mathematics and especially show how mathematics is applied to solve fundamental engineering problems. The aim of the course is to show the students why mathematics is important in an engineering career by demonstrating how simple engineering problems can be mathematically described and methodically analyzed to find a solution.

A number of applied examples from various engineering disciplines will be introduced, analyzed and solved.

More than 2000 years ago, long before rockets were launched into orbit or explorers sailed around the globe, a Greek mathematician measured the size of the Earth using nothing more than a few facts about lines, angles, and circles. This course will start at the very beginnings of geometry, answering questions like "How big is an angle?" and "What are parallel lines?" and proceed up through advanced theorems and proofs about 2D and 3D shapes. Along the way, you'll learn a few different ways to find the area of a triangle, you'll discover a shortcut for counting the number of stones in the Great Pyramid of Giza, and you'll even come up with your own estimate for the size of the Earth.
 
In this course, you'll be able to choose your own path within each lesson, and you can jump between lessons to quickly review earlier material. GeometryX covers a standard curriculum in high school geometry, and CCSS (common core) alignment is indicated where applicable.

Learn more about our High School and AP* Exam Preparation Courses

This course was funded in part by the Wertheimer Fund.

This course is an introduction to mechanics and follows a standard first-semester university physics course. You will learn fundamental mechanics concepts and mathematical problem solving required for all STEM fields.

The course begins with kinematics, where you will learn to use equations and graphs to describe the position, velocity, and acceleration of an object, and how those quantities are related through calculus. You will then learn how forces affect motion through Newton’s Laws, and how to understand and calculate several different forces, including gravitational, normal force, drag force, and friction force. The concept of energy will be covered, including kinetic energy, potential energy, and how they are affected by work. You will learn how to use the conservation of energy to solve motion problems. Finally, momentum, another “quantity of motion” will be described. You will learn how to calculate momentum, about its relationship to Newton’s laws, and how to use it to solve motion problems, including collisions.

This course is valuable preparation for the equivalent on-campus course, or as supplementary material.

The world is full of uncertainty: accidents, storms, unruly financial markets, and noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical inference are the keys to analyzing data and making scientifically sound predictions.

This is Part 1 of a 2-part sequence on the basic tools of probabilistic modeling. Part 1 introduces the general framework of probability models, multiple discrete or continuous random variables, expectations, conditional distributions, and various powerful tools of general applicability. Part 2 will then continue into further topics that include laws of large numbers, the main tools of Bayesian inference methods, and an introduction to random processes (Poisson processes and Markov chains).

The contents of the two parts of the course are essentially the same as those of the corresponding MIT class, which has been offered and continuously refined over more than 50 years. It is a challenging class, but will enable you to apply the tools of probability theory to real-world applications or your research.

Probabilistic models use the language of mathematics. But instead of relying on the traditional "theorem - proof" format, we develop the material in an intuitive -- but still rigorous and mathematically precise -- manner. Furthermore, while the applications are multiple and evident, we emphasize the basic concepts and methodologies that are universally applicable.

Photo by User: Pablo Ruiz Múzquiz on Flickr. (CC BY-NC-SA 2.0)

We are surrounded by information, much of it numerical, and it is important to know how to make sense of it. Stat2x is an introduction to the fundamental concepts and methods of statistics, the science of drawing conclusions from data.

The course is the online equivalent of Statistics 2, a 15-week introductory course taken in Berkeley by about 1,000 students each year. Stat2x is divided into three 5-week components. Stat2.1x is the first of the three.

The focus of Stat2.1x is on descriptive statistics. The goal of descriptive statistics is to summarize and present numerical information in a manner that is illuminating and useful. The course will cover graphical as well as numerical summaries of data, starting with a single variable and progressing to the relation between two variables. Methods will be illustrated with data from a variety of areas in the sciences and humanities.

There will be no mindless memorization of formulas and methods. Throughout Stat2.1x, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

FAQ

• What is the format of the class?
  • Instruction will be consist of brief lectures and exercises to check comprehension. Grades (Pass or Not Pass) will be decided based on a combination of scores on short assignments, quizzes, and a final exam.
• How much does it cost to take the course?
  • Nothing! The course is free.
• Will the text of the lectures be available?
  • Yes. All of our lectures will have transcripts synced to the videos.
• Do I need to watch the lectures live?
  • No. You can watch the lectures at your leisure.
• Can I contact the Instructor or Teaching Assistants?
  • Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.
• Do I need any other materials to take the course?
  • If you have any questions about edX generally, please see the edX FAQ.