# Online courses directory (648)

The advent of computers transformed science. Large, complicated datasets that once took researchers years to manually analyze could suddenly be analyzed within a week using computer software. Nowadays, scientists can use computers to produce several hypotheses as to how a particular phenomenon works, create computer models using the parameters of each hypothesis, input data, and see which hypothetical model produces an output that most closely mirrors reality. Computational biology refers to the use of computers to automate data analysis or model hypotheses in the field of biology. With computational biology, researchers apply mathematics to biological phenomena, use computer programming and algorithms to artificially create or model the phenomena, and draw from statistics in order to interpret the findings. In this course, you will learn the basic principles and procedures of computational biology. You will also learn various ways in which you can apply computational biology to molecular and cell…

This course focuses on the interaction of chemical engineering, biochemistry, and microbiology. Mathematical representations of microbial systems are featured among lecture topics. Kinetics of growth, death, and metabolism are also covered. Continuous fermentation, agitation, mass transfer, and scale-up in fermentation systems, and enzyme technology round out the subject material.

This course focuses on the interaction of chemical engineering, biochemistry, and microbiology. Mathematical representations of microbial systems are featured among lecture topics. Kinetics of growth, death, and metabolism are also covered. Continuous fermentation, agitation, mass transfer, and scale-up in fermentation systems, and enzyme technology round out the subject material.

This is an introductory course in biochemistry, designed for both biology and chemical engineering majors. A consistent theme in this course is the development of a quantitative understanding of the interactions of biological molecules from a structural, thermodynamic, and molecular dynamic point of view. A molecular simulation environment provides the opportunity for you to explore the effect of molecular interactions on the biochemical properties of systems. This course assumes that students have taken introductory chemistry, including basic thermodynamics, as well as introductory organic chemistry. An introductory biology course is not a prerequisite for the course, but students would benefit from some prior exposure to biology, even at the high school level. Required mathematical skills include simple algebra and differential calculus.

This subject deals primarily with kinetic and equilibrium mathematical models of biomolecular interactions, as well as the application of these quantitative analyses to biological problems across a wide range of levels of organization, from individual molecular interactions to populations of cells.

Great managers are made, not born. Learn about the qualities and skills of great managers in this Business 101 course. Instructor Sherri Hartzell holds both an MBA and Ed.D., so she's an excellent choice to teach you about principles of management.

Start by learning about the different levels of management in organizations and then dive into how good managers lead to great employees. Students of business, budding entrepreneurs and independent online learners alike can benefit from these short, engaging video lessons and interactive online quizzes. Business 101: Principles of Management can prepare you to earn real, widely transferable college credit by taking the Principles of Management CLEP exam or the Excelsior Principles of Management exam .

This course is about modeling and how computer models can support managerial decision making. A model is a simplified representation of a real situation and modeling is the process of developing, analyzing and interpreting a model in order to help make better decisions. Models can be invaluable tools in managing and understanding the complexity and risk inherent in many business problems. As a result, models have become an increasingly important part of business at all levels from daily operations to strategic decision making.

This course will help learners become intelligent users and consumers of these models. To this end, we will cover the basic elements of modeling – how to formulate a model and how to use and interpret the information a model produces. The course emphasizes “learning by doing” so that students will be expected to formulate, solve, and interpret a number of different optimization and simulation models using Excel spreadsheets. An important theme in the course is to understand the appropriate use of models in business and the potential pitfalls from using models incorrectly or inappropriately.

The course has two distinct parts:

- The first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization. Our approach will be more practically motivated, meaning we will fully develop a mathematical understanding of the respective algorithms, but we will only briefly touch on abstract learning theory.
- In the second half, we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.

Sal working through the 53 problems from the practice test available at http://www.cde.ca.gov/ta/tg/hs/documents/mathpractest.pdf for the CAHSEE (California High School Exit Examination). Clearly useful if you're looking to take that exam. Probably still useful if you want to make sure you have a solid understanding of basic high school math. CAHSEE Practice: Problems 1-3. CAHSEE Practice: Problems 4-9. CAHSEE Practice: Problems 10-12. CAHSEE Practice: Problems 13-14. CAHSEE Practice: Problems 15-16. CAHSEE Practice: Problems 17-19. CAHSEE Practice: Problems 20-22. CAHSEE Practice: Problems 23-27. CAHSEE Practice: Problems 28-31. CAHSEE Practice: Problems 32-34. CAHSEE Practice: Problems 35-37. CAHSEE Practice: Problems 38-42. CAHSEE Practice: Problems 43-46. CAHSEE Practice: Problems 47-51. CAHSEE Practice: Problems 52-53. CAHSEE Practice: Problems 1-3. CAHSEE Practice: Problems 4-9. CAHSEE Practice: Problems 10-12. CAHSEE Practice: Problems 13-14. CAHSEE Practice: Problems 15-16. CAHSEE Practice: Problems 17-19. CAHSEE Practice: Problems 20-22. CAHSEE Practice: Problems 23-27. CAHSEE Practice: Problems 28-31. CAHSEE Practice: Problems 32-34. CAHSEE Practice: Problems 35-37. CAHSEE Practice: Problems 38-42. CAHSEE Practice: Problems 43-46. CAHSEE Practice: Problems 47-51. CAHSEE Practice: Problems 52-53.

Build your earth science vocabulary and learn about cycles of matter and types of sedimentary rocks through the Education Portal course Earth Science 101: Earth Science. Our series of video lessons and accompanying self-assessment quizzes can help you boost your scientific knowledge ahead of the Excelsior Earth Science exam . This course was designed by experienced educators and examines both science basics, like experimental design and systems of measurement, and more advanced topics, such as analysis of rock deformation and theories of continental drift.

How does the final velocity on a zip line change when the starting point is raised or lowered by a matter of centimeters? What is the accuracy of a GPS position measurement? How fast should an airplane travel to minimize fuel consumption? The answers to all of these questions involve the derivative.

But what is the derivative? You will learn its mathematical notation, physical meaning, geometric interpretation, and be able to move fluently between these representations of the derivative. You will discover how to differentiate any function you can think up, and develop a powerful intuition to be able to sketch the graph of many functions. You will make linear and quadratic approximations of functions to simplify computations and gain intuition for system behavior. You will learn to maximize and minimize functions to optimize properties like cost, efficiency, energy, and power.

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

Calculus 1C: Coordinate Systems & Infinite Series

This course was funded in part by the Wertheimer Fund.

**Advanced Placement and AP are registered trademarks of the College Board, which was not involved in the production of, and does not endorse, these offerings.*

In this course, we go beyond the calculus textbook, working with practitioners in social, life and physical sciences to understand how calculus and mathematical models play a role in their work.

Through a series of case studies, you’ll learn:

- How standardized test makers use functions to analyze the difficulty of test questions;
- How economists model interaction of price and demand using rates of change, in a historical case of subway ridership;
- How an x-ray is different from a CT-scan, and what this has to do with integrals;
- How biologists use differential equation models to predict when populations will experience dramatic changes, such as extinction or outbreaks;
- How the Lotka-Volterra predator-prey model was created to answer a biological puzzle;
- How statisticians use functions to model data, like income distributions, and how integrals measure chance;
- How Einstein’s Energy Equation, E=mc
^{2}is an approximation to a more complicated equation.

With real practitioners as your guide, you’ll explore these situations in a hands-on way: looking at data and graphs, writing equations, doing calculus computations, and making educated guesses and predictions.

This course provides a unique supplement to a course in single-variable calculus. Key topics include application of derivatives, integrals and differential equations, mathematical models and parameters.

This course is for anyone who has completed or is currently taking a single-variable calculus course (differential and integral), at the high school (AP or IB) or college/university level. You will need to be familiar with the basics of derivatives, integrals, and differential equations, as well as functions involving polynomials, exponentials, and logarithms.

This is a course to learn applications of calculus to other fields, and NOT a course to learn the basics of calculus. Whether you’re a student who has just finished an introductory Calculus course or a teacher looking for more authentic examples for your classroom, there is something for you to learn here, and we hope you’ll join us!

Using Desmos in this Course This course uses Desmos (https://www.desmos.com/), an online graphing calculator, to illustrate examples. Your use of the Desmos platform or any content hosted by Desmos is subject to the Desmos terms of service at https://www.desmos.com/terms and privacy policy at https://www.desmos.com/privacy.

If you do not wish to use the Desmos platform or view content hosted by Desmos, you may not be able to complete the course. This course does NOT require you to make your own individual user account on Desmos. Desmos is a separate entity and is not directly affiliated with HarvardX or edX.

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. 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.

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Life as an emergent property of networks of chemical reactions involving proteins and nucleic acids. Mathematical theories of metabolism, gene regulation, signal transduction, chemotaxis, excitability, motility, mitosis, development, and immunity. Applications to directed molecular evolution, DNA computing, and metabolic and genetic engineering.

This course covers cells and tissues of the immune system, lymphocyte development, the structure and function of antigen receptors, the cell biology of antigen processing and presentation, including molecular structure and assembly of MHC molecules, the biology of cytokines, leukocyte-endothelial interactions, and the pathogenesis of immunologically mediated diseases. The course is structured as a series of lectures and tutorials in which clinical cases are discussed with faculty tutors.

#### Lecturers

Frederick W. Alt

Marcus Altfeld

Paul Anderson

Jon C. Aster

Hugh Auchincloss

Steven P. Balk

Samuel M. Behar

Richard S. Blumberg

Francisco Bonilla

Bobby Cherayil

Benjamin Davis

David Hafler

Nir Harcohen

Bruce Horwitz

David M. Lee

Andrew Lichtman

Diane Mathis

Richard Mitchell

Hidde Ploegh

Emmett Schmidt

Arlene Sharpe

Megan Sykes

Shannon Turley

Dale T. Umetsu

Ulrich von Andrian

Bruce Walker

Kai Wucherpfennig

Ramnik Xavier

Sarah Henrickson