Online courses directory (10358)
Math 101: College Algebra is designed to be used to prepare you to earn real college credit by passing the College Algebra CLEP Exam . This course covers topics that are included on the exam, including linear equations, functions, graphing, matrices and more. Use it to help you learn what you need to know about algebra topics so you can succeed on the exam.
The algebra instructors are experienced and knowledgeable educators who have put together comprehensive video lessons in categories ranging from absolute value problems to exponentials to the classification of numbers. Each category is broken down into smaller chapters that will cover topics more in-depth. These video lessons make learning fun and interesting. You get the aid of self-graded quizzes and practice tests to allow you to gauge how much you have learned.
Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.
Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.
Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.
Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.
A math course for life science majors covering elementary probability, probability distributions, random variables, and
Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.
In this course you will learn to use some mathematical tools that can help predict and analyze sporting performances and outcomes. This course will help coaches, players, and enthusiasts to make educated decisions about strategy, training, and execution. We will discuss topics such as the myth of the Hot Hand and the curse of the Sports Illustrated cover; how understanding data can improve athletic performance; and how best to pick your Fantasy Football team. We will also see how elementary Calculus provides insight into the biomechanics of sports and how game theory can help improve an athlete’s strategy on the field.
In this course you will learn:
- How a basic understanding of probability and statistics can be used to analyze sports and other real life situations.
- How to model physical systems, such as a golf swing or a high jump, using basic equations of motion.
- How to best pick your Fantasy Football, March Madness, and World Cup winners by using ranking theory to help you determine athletic and team performance.
By the end of the course, you will have a better understanding of math, how math is used in the sports we love, and in our everyday lives.
Computer fonts, Angry Birds, March Madness, and Google - sound like fun? Indeed, math influences the world around us.
This course provides a self-paced, individualized environment for anyone looking to refresh math skills. The content focuses primarily on algebra and arithmetic, and aligns with many standard exams, such as college math placement exams.
This course is designed for students who will be starting or restarting college within the next year, and for current students who have not completed their general education math requirement. It will provide math refresher materials covering a wide range of mathematical concepts together with information about success in college. Incoming college students are typically placed in college math courses based on placement exam scores. Students often take these placement exams with minimal preparation or after a long break since their last math class. The study materials in the course will help students prepare for placement exams, and higher scores mean fewer required math courses in college. Students who have already taken a placement exam (such as the ACT) can also use these materials to study and then retest, hopefully scoring higher. College students who have started, but not finished their math courses, can also retake a placement exam and possibly skip a math class. The course will also be valuable for anyone who just wants to refresh their math skills. The provided study materials are individualized based on a student’s current knowledge. Each student will be provided a customized learning path that maximizes efficiency so that study time is spent where it’s needed most. Beyond math content, the course will also provide college success material such as test-taking strategies, new student orientation, and study techniques. All of this material can be accessed separately from the math content so even if a student is already placed highly in math, or has tested out of it completely, the course will provide valuable information to help the student orient to college and to get the most out of the college experience.
Methodisch ausgefeilter Doppel-MOOC mit Geometrie und Arithmetik. Du möchtest mathematisch denken lernen? Sei Kiebitz, Anpacker oder Formalisierer: Du hast die Wahl!
This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
This course provides techniques of effective presentation of mathematical material. Each section of this course is associated with a regular mathematics subject, and uses the material of that subject as a basis for written and oral presentations. The section presented here is on chaotic dynamical systems.
We present a course developed by the team of Tomsk State University of Control Systems and Radioelectronics.
This course offers basic knowledge in mathematical logic.
The goals of mathematical logic are:
- To provide a formal language for mathematical statements that is easily translatable into the natural language and that allows compact and convenient notation.
- To offer clear and unambiguous interpretation of such statements that is at the same time simple and close to the natural mathematical concepts.
We made sure to make this course informative and interesting for everyone!
What will I learn?
Upon completion of the course, students will have acquired fundamental knowledge that is valuable in itself and will serve as the foundation for other studies. For example, software engineers strongly rely on logic-mathematical theories in their work.
• Natural languages possess a number of flaws - inaccuracy, polysemy, complexity.
• Knowledge of the simple yet powerful methods of mathematical statement transformations made possible by the language of logic is just as vital as is the knowledge of elementary algebra. No need to reinvent the wheel.
• Invented almost a century ago to address the needs of mathematics, mathematical logic has found application in theoretical and practical programming.
• When dealing with applied problems, a researcher has to switch between the descriptive language, mathematical language, the language of numerical methods and algorithms, and specific programming languages. The language of mathematical logic offers a great opportunity to practice this translation between languages and is used as a powerful formalised tool for transmission of information between distant languages.
What do I need to know?
Most of the course content will be understandable for students with only a high school level of education. Some minor sections of the course will require knowledge of imperative programming and elements of mathematical analysis.
Course Structure
The course consists of 7 chapters:
Chapter 1 - Mission of mathematical logic:
Goals, objectives, methods.
Relation between mathematics and mathematical logic.
Examples of logical errors, sophisms and paradoxes.
Brief history of mathematical logic, discussing how problems mathematical logic faced and solved in its development, and how mathematical logic integrates further and further into programming.
Chapter 2 - Foundations of the set theory:
Set theory is the basis for development of languages.
Chapter 3 - Propositional logic:
Propositional logic studies the simplest yet the most important formal language.
Chapter 4 - First-order languages:
The language of propositional logic has limited tools, so we talk about more complex languages based on predicate logic. The language of predicate logic offers tools for full and exact description of any formal notions and statements.
Chapter 5 - Axiomatic method:
The axiomatic method makes it possible to solve many logical problems, errors and paradoxes. It is widely used in today's mathematics and the knowledge of it is vital for anyone using functional and logical programming languages.
Chapter 6 - Mathematical proof:
Discussion of the types of mathematical proof and how proof can be aided with a computer.
Chapter 7 - Algorithm theory:
To learn about the possibilities of the algorithmic approach and the limitations of calculations, one must know the rigorous definition of algorithms and computability. The module offers these definitions and defines algorithmically unsolvable problems. The module introduces the concept of algorithm complexity, which is an important factor when selecting algorithms to solve problems. The module also compares problems by complexity - this knowledge makes it possible to use any search algorithm to solve problem instead of search for the good algorithm.
This graduate-level course is a continuation of Mathematical Methods for Engineers I (18.085). Topics include numerical methods; initial-value problems; network flows; and optimization.
Mathematical Methods for Quantitative Finance covers topics from calculus and linear algebra that are fundamental for the study of mathematical finance. Students successfully completing this course will be mathematically well prepared to study quantitative finance at the graduate level.
Find out what solid-state physics has brought to Electromagnetism in the last 20 years. This course surveys the physics and mathematics of nanophotonics—electromagnetic waves in media structured on the scale of the wavelength.
Topics include computational methods combined with high-level algebraic techniques borrowed from solid-state quantum mechanics: linear algebra and eigensystems, group theory, Bloch's theorem and conservation laws, perturbation methods, and coupled-mode theories, to understand surprising optical phenomena from band gaps to slow light to nonlinear filters.
Note: An earlier version of this course was published on OCW as 18.325 Topics in Applied Mathematics: Mathematical Methods in Nanophotonics, Fall 2005.
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