Courses tagged with "Nutrition" (6413)

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.

This course deals with advanced design theories and textual analysis. Emphasis is placed on script analysis in general, as well as the investigation of design principles from a designer's perspective. Students also refine technical skills in rendering and presentation, historical research, and analysis. Class sessions include interaction with student/faculty directors and other staff designers. The goal of this course is for students to approach text with a fresh vision and translate that vision into design for performance.

In this UX course, we will survey theories and findings from the social sciences (especially psychology); with special attention to how these concepts influence the way we design for human interaction. We will cover how people perceive and process information, motor capabilities and limitations, decision-making and problem solving, and how emotion and social factors impact user experience. We will also cover best practices for designing systems to align with how people work.

This course is part of the User Experience (UX) Research and Design MicroMasters Program offered by MichiganX.

The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451 Principles of Digital Communication II, is offered in the spring.

Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication.

This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm.

More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms; the BCJR algorithm; turbo codes, LDPC codes and RA codes; and performance of LDPC codes with iterative decoding. Finally, the course addresses coding for the bandwidth-limited regime, including lattice codes, trellis-coded modulation, multilevel coding and shaping. If time permits, it covers equalization of linear Gaussian channels.

This course is an introduction to discrete applied mathematics. Topics include probability, counting, linear programming, number-theoretic algorithms, sorting, data compression, and error-correcting codes. This is a Communication Intensive in the Major (CI-M) course, and thus includes a writing component.

Quantitative and model-based introduction to basic ideas in economics, and applications to a wide range of real world problems.

This course provides a quantitative and model-based introduction to basic economic principles, and teaches how to apply them to make sense of a wide range of real world problems. Examples of applications include predicting the impact of technological changes in market prices, calculating the optimal gasoline tax, and measuring the value of new products. This is a real Caltech class. It will be taught concurrently to Caltech and on-line students. This has two implications. On the costs side: the class is challenging, makes extensive use of calculus, and will demand significant effort. On the benefit side: successful completion of the class will provide you with an in-depth understanding of basic economics, and will permanently change the way you see the world.

This course provides a quantitative and model-based introduction to basic economic principles, and teaches how to apply them to make sense of a wide range of real world problems. Examples of applications include predicting the impact of technological changes in market prices, calculating the optimal gasoline tax, and measuring the value of new products. This is a real Caltech class. It will be taught concurrently to Caltech and on-line students. This has two implications. On the costs side: the class is challenging, makes extensive use of calculus, and will demand significant effort. On the benefit side: successful completion of the class will provide you with an in-depth understanding of basic economics, and will permanently change the way you see the world.

Principles of Electric Circuits (20220214x) is one of the kernel courses in the broad EECS subjects. Almost all the required courses in EECS are based on the concepts learned in this course, so it’s the gateway to a qualified EECS engineer.

The main content of this course contains linear and nonlinear resistive circuits, time domain analysis of the dynamic circuits, and the steady state analysis of the dynamic circuits with sinusoidal excitations. Important concepts, e.g. filters, resonance, quiescent point, etc., cutting-edge elements, e.g. MOSFETs and Op Amps, etc., systematic analyzing tools, e.g. node method and phasor method, etc., and real-world engineering applications, e.g. square wave generator and pulse power supply for railgun, etc., will be discussed in depth.

In order to facilitate the learning for students with middle school level, we prepare the necessary knowledge for calculus and linear algebra in week 0. With your effort, we can show you the fantastic view of electricity.

电路原理课程是电类各专业最重要的一门学科基础课，后续各专业基础课和专业课都建立在这门课程的知识体系之上，因此是电类专业本科生的“看家 课”之一。电路原理课程的主要内容包括：线性电阻电路分析、非线性电阻电路分析、动态电路的时域分析和正弦激励下动态电路的稳态分析4大部分。清华大学电 路原理课程的教学包括电路分析基本方法、当代电路元器件、电路原理的实际工程应用等，为学生提供了扎实的基础和丰富的应用。

为方便至只有中学知识的学生学习，电路原理MOOC专门利用第0周准备必要的微积分、线性代数和大学物理电学的基础。我们有信心：你能领悟电世界的奇妙。    

This electronics course will focus on the physics of biomolecule detection in terms of three elementary concepts: response time, sensitivity, and selectivity. We will use potentiometric, amperometric, and cantilever-based mass sensors to illustrate the application of these concepts to specific sensor technologies. Learners in this course will be able to decide what sensors to make, appreciate their design principles, interpret measured results, and spot emerging research trends.

This electronics course is the latest in a science and engineering series offered by the nanoHUB-U project, which is jointly funded by Purdue University and the National Science Foundation. 

This class introduces students to the interdisciplinary nature of 21st-century engineering projects with three threads of learning: a technical toolkit, a social science toolkit, and a methodology for problem-based learning. Students encounter the social, political, economic, and technological challenges of engineering practice by participating in real engineering projects with faculty and industry; this semester's major project focuses on the engineering and economics of solar cells. Student teams will create prototypes and mixed media reports with exercises in project planning, analysis, design, optimization, demonstration, reporting and team building.

This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data.

This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”

This course covers current understanding of, and modern approaches to human disease, emphasizing the molecular and cellular basis of both genetic disease and cancer. Topics include: The Genetics of Simple and Complex Traits; Karyotypic Analysis and Positional Cloning; Genetic Diagnosis; The Roles of Oncogenes and Tumor Suppressors in Tumor Initiation, Progression, and Treatment; The Interaction between Genetics and Environment; Animal Models of Human Disease; Cancer; and Conventional and Gene Therapy Treatment Strategies.

This course provides a systematic presentation of the chemical applications of group theory with emphasis on the formal development of the subject and its applications to the physical methods of inorganic chemical compounds. Against the backdrop of electronic structure, the electronic, vibrational, and magnetic properties of transition metal complexes are presented and their investigation by the appropriate spectroscopy described.

This course covers the principles of main group (s and p block) element chemistry with an emphasis on synthesis, structure, bonding, and reaction mechanisms.

This course is part of the Microsoft Professional Program Certificate in Data Science.

Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, Python, and Azure Machine Learning.

This course provides an overview of macroeconomic issues: the determination of output, employment, unemployment, interest rates, and inflation. Monetary and fiscal policies are discussed. Important policy debates such as, the sub-prime crisis, social security, the public debt, and international economic issues are critically explored. The course introduces basic models of macroeconomics and illustrates principles with the experience of the U.S. and foreign economies.