Courses tagged with "Nutrition" (421)
Ever hang your head in shame after your Python program wasn't as fast as your friend's C program? Ever wish you could use objects without having to use Java? Join us for this fun introduction to C and C++! We will take you through a tour that will start with writing simple C programs, go deep into the caves of C memory manipulation, resurface with an introduction to using C++ classes, dive deeper into advanced C++ class use and the C++ Standard Template Libraries. We'll wrap up by teaching you some tricks of the trade that you may need for tech interviews.
We see this as a "C/C++ empowerment" course: we want you to come away understanding
- why you would want to use C over another language (control over memory, probably for performance reasons),
- why you would want to use C++ rather than C (objects), and
- how to be useful in C and C++.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
This is a fast-paced introductory course to the C++ programming language. It is intended for those with little programming background, though prior programming experience will make it easier, and those with previous experience will still learn C++-specific constructs and concepts.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
This course examines signals, systems and inference as unifying themes in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; group delay; state feedback and observers; probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization; least-mean square error estimation; Wiener filtering; hypothesis testing; detection; matched filters.
In this 5-week course we’ll introduce the fundamentals of programming in Processing, an accessible introduction to combining arts and computing. The course will provide the essentials of programming in a visual context, allowing you to visualize, design, and create generative art with Processing.
This course introduces the basic computational methods used to understand the cell on a molecular level. It covers subjects such as the sequence alignment algorithms: dynamic programming, hashing, suffix trees, and Gibbs sampling. Furthermore, it focuses on computational approaches to: genetic and physical mapping; genome sequencing, assembly, and annotation; RNA expression and secondary structure; protein structure and folding; and molecular interactions and dynamics.
6.00.2x will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving . This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. You will spend a considerable amount of time writing programs to implement the concepts covered in the course. For example, you will write a program that will simulate a robot vacuum cleaning a room or will model the population dynamics of viruses replicating and drug treatments in a patient's body.
Topics covered include:
- Advanced programming in Python 3
- Knapsack problem, Graphs and graph optimization
- Dynamic programming
- Plotting with the pylab package
- Random walks
- Probability, Distributions
- Monte Carlo simulations
- Curve fitting
- Statistical fallacies
This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.
This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.
Course Format
This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:
- A complete set of Lecture Videos by Prof. Guttag.
- Resources for each lecture video, such as Handouts, Slides, and Code Files.
- Recitation Videos by course TA's to review content and problem solving techniques.
- Homework problems with sample student solutions.
- Further Study collections of links to supplemental online content.
- Self-Assessment tools, including lecture questions with answers and unit quizzes with solutions, to assess your subject mastery.
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