Imagen de Anant Agarwal
Anant Agarwal
chief platform officer of 2U, founder of edX, and professor of electrical engineering and computer science at MIT
edX

Anant Agarwal is the chief platform officer of 2U, and founder of edX. Anant taught the first edX course on circuits and electronics from MIT, which drew 155,000 students from 162 countries. He has served as the director of CSAIL, MIT's Computer Science and Artificial Intelligence Laboratory, and is a professor of electrical engineering and computer science at MIT. He is a successful serial entrepreneur, having co-founded several companies including Tilera Corporation, which created the Tile multicore processor, and Virtual Machine Works.

Anant won the Maurice Wilkes prize for computer architecture, and MIT's Smullin and Jamieson prizes for teaching. He is also the 2016 recipient of the Harold W. McGraw, Jr. Prize for Higher Education, which recognized his work in advancing the MOOC movement. Additionally, he is a recipient of the Padma Shri award from the President of India and was named the Yidan Prize for Education Development Laureate in 2018. He held a Guinness World Record for the largest microphone array, and is an author of the textbook "Foundations of Analog and Digital Electronic Circuits."

Scientific American selected his work on organic computing as one of 10 World- Changing Ideas in 2011, and he was named in Forbes' list of top 15 education innovators in 2012. Anant, a pioneer in computer architecture, is a member of the National Academy of Engineering, a fellow of the American Academy of Arts and Sciences, and a fellow of the ACM.

He hacks on WebSim, an online circuits laboratory, in his spare time. Anant holds a Ph.D. from Stanford and a bachelor's from IIT Madras. Anant's twitter handle is @agarwaledu.


Cursos impartidos por Anant Agarwal

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Dynamic Energy Modelling of Buildings: Thermal Simulation

<p>Understand the dynamics of buildings’ thermal behavior and learn how to optimize their design and operation through thermal modeling.</p>

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Dynamic Energy Modelling of Buildings: Thermal Simulation

<p>Understand the dynamics of buildings’ thermal behavior and learn how to optimize their design and operation through thermal modeling.</p>

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Computing for Data Analysis

<p>A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning.</p>

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Introduction to Analytics Modeling

<p>Learn essential analytics models and methods and how to appropriately apply them, using tools such as R, to retrieve desired insights.</p>

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Probability and Statistics I: A Gentle Introduction to Probability

<p>This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems.</p>

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Probability and Statistics II: Random Variables – Great Expectations to Bell Curves

<p>This course discusses properties and applications of random variables. For instance, how many customers are likely to arrive in the next hour? What’s the probability that a lightbulb will last more than a year?</p> <p>When you’re done with this course, you’ll have enough firepower to undertake a wide variety of modeling and analysis problems; and you’ll be well-prepared for the upcoming Statistics courses.</p>

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Probability and Statistics III: A Gentle Introduction to Statistics

<p>This course provides an introduction to basic statistical concepts. We begin by walking through a library of probability distributions – including the normal distribution, which in turn leads to the Central Limit Theorem. We then discuss elementary descriptive statistics and estimation methods.</p>

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Probability and Statistics IV: Confidence Intervals and Hypothesis Tests

<p>This course covers two important methodologies in statistics – <em>confidence intervals</em> and <em>hypothesis testing</em>. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug?"</p>

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Linear Algebra I: Linear Equations

<p>This course takes you through the first three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>

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Linear Algebra II: Matrix Algebra

<p>This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>

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Linear Algebra III: Determinants and Eigenvalues

<p>This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>

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Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD

<p>This course takes you through roughly five weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>

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Data Analytics for Business

<p>This course prepares students to understand business analytics and become leaders in these areas in business organizations.</p>

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Introduction to Analytics Modeling

<p>Learn essential analytics models and methods and how to appropriately apply them, using tools such as R, to retrieve desired insights.</p>

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Probability and Statistics I: A Gentle Introduction to Probability

<p>This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems.</p>

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Probability and Statistics II: Random Variables – Great Expectations to Bell Curves

<p>This course discusses properties and applications of random variables. For instance, how many customers are likely to arrive in the next hour? What’s the probability that a lightbulb will last more than a year?</p> <p>When you’re done with this course, you’ll have enough firepower to undertake a wide variety of modeling and analysis problems; and you’ll be well-prepared for the upcoming Statistics courses.</p>

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Probability and Statistics III: A Gentle Introduction to Statistics

<p>This course provides an introduction to basic statistical concepts. We begin by walking through a library of probability distributions – including the normal distribution, which in turn leads to the Central Limit Theorem. We then discuss elementary descriptive statistics and estimation methods.</p>

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Probability and Statistics IV: Confidence Intervals and Hypothesis Tests

<p>This course covers two important methodologies in statistics – <em>confidence intervals</em> and <em>hypothesis testing</em>. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug?"</p>

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Linear Algebra I: Linear Equations

<p>This course takes you through the first three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>

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Linear Algebra II: Matrix Algebra

<p>This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.</p>