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Mathematics

Are you looking to learn the different rules of mathematics? For those who find it hard to understand, mathematics can be quite challenging. This is why we have presented some of the best online lectures on mathematics where we will discuss a wide array of different topics.

In our video lectures, we are going to talk about finite mathematics, differential equations, statistical probability, Laplace transforms, Fourier series and more. Mathematics as a subject is vast and with these online tutorials, we have tried to segregate some major topics into distinct lectures. Those who are looking to study calculus can find lectures devoted to differential equations and advanced methods of dealing with numerical analysis of such differential equations too.

Further, we also have courses for functional analysis, real analysis, geometry and advanced matrix theory as well. Statistics is considered by many as another separate branch of mathematics and you can find a lot of video lectures devoted to the same. We have video lectures for regression analysis, multivariate analysis, numerical analysis, computational techniques and more.

Every single one of our lectures has been made keeping the needs of the readers in mind. The online lectures are going to explain the core concepts and then we subsequently build upon your foundation to help you solve advanced and complex problems. With our varied online video tutorials, people can learn some of the most mind boggling mathematical concepts and gain proficiency in the same.

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The application of optimization methods to important engineering problems in thermodynamics, statistics, design, control, economics and scheduling. The course will emphasize p
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  • 19 hrs 0 min
  • Self Paced
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This course is an introduction to probability as a language and set of tools for understanding statistics, science, risk, and randomness. The ideas and methods are useful in s
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  • 3 hrs 4 min
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Other Summer 2017
This course is focused on the question: How do we do matrix computations with acceptable speed and acceptable accuracy? The course is taught in Python with Jupyter Notebooks,
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  • 16 hrs 32 min
  • Self Paced
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Introduction:Data Mining, Data Assimilation, Inverse problems and Prediction - Static vs. dynamic and deterministic vs. stochastic problems- formulation & classification;Mathe
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Theorems of Picard, Casorati-Weierstrass and Riemann on Removable Singularities:Properties of the Image of an Analytic Function:Introduction to the Picard Theorems,Recalling S
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UC Berkeley Spring 2014
Programming for numerical calculations, round-off error, approximation and interpolation, numerical quadrature, and solution of ordinary differential equations. Practice on th
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Logic, infinity, and induction; applications include undecidability and stable marriage problem. Modular arithmetic and GCDs; applications include primality testing and crypto
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Theorems of Rouche and Hurwitz:Fundamental Theorems Connected with Zeros of Analytic Functions - The Argument (Counting) Principle, Rouche's Theorem and The Fundamental Theore
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Introductory - Mathematics in the Vedas and Sulva Sutras - Panini - Pingala - Mathematics in the Jaina Texts - Development of Place Value System - Aryabhatiya of Aryabhata - A
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Pigeon hole Principle - Elementary Concepts - Elementary concepts and basic counting principles - Elementary concepts; Binomial theorem; Bijective proofs - Properties of binom
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Set Theory:Introduction to the theory of sets; combination of sets; power sets; finite and infinite sets; principle of inclusion and exclusion; selected problems from each top
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Initial Value Problems (IVP) and existence theorem. Truncation error, deriving finite difference equations - Single step methods for I order IVP- Taylor series method, Euler m
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Probability Theory Refresher: Axiomatic construction of probability spaces, random variables and vectors, probability distributions, functions of random variables; mathematica
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Introduction and Motivation - Basic concepts of point estimation: unbiasedness, consistency and efficiency of estimators, examples - Finding Estimators: method of moments and
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Basics of Convex Optimization - Basic facts of Convex Optimization - Basic properties of convex sets - Introduction to Polyhedral sets - Separation theorems for convex sets -
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Optimization - Introduction - Formulation of LPP - Geometry of LPP and Graphical Solution of LPP - Solution of LPP : Simplex Method - Big - M Method - Two - Phase Method - Spe
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Introduction:First Basic Problem - Systems of Linear equations - Matrix Notation - The various questions that arise with a system of linear eqautions - Second Basic Problem -
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Basic principles of counting - Sample space , events, axioms of probability - Conditional probability, Independence of events - Random variables, cumulative density function,
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  • Self Paced