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Applied Calculus with Python · LearnSpace
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Applied Calculus with Python

Курс от Johns Hopkins University
Средний≈ 23.1 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course is designed for the Python programmer who wants to develop the foundations of Calculus to help solve challenging problems as well as the student of mathematics looking to learn the theory and numerical techniques of applied calculus implemented in Python. By the end of this course, you will have learned how to apply essential calculus concepts to develop robust Python applications that solve a variety of real-world challenges. Video lectures, readings, worked examples, assessments, and Python code are all provided in the course. These are used to illustrate techniques to solve equations, work with functions, and compute and apply derivatives and integrals. If you are interested in starting to develop concepts in fields such as applied math, data science, cybersecurity, or artificial intelligence, or just need a refresher of calculus or coding in Python, then this course is right for you.

Навыки, которые вы освоите

Python ProgrammingCalculusDerivativesIntegral CalculusApplied MathematicsMathematical SoftwareNumerical AnalysisGraphingAlgebraModel Optimization

Программа курса

5 модулей · 82 учебных материалов

01Introduction to Python7 материалов

Introduction to Python and SymPy

Introduction to PythonВидеоOptions for Using PythonЧтениеData Types and Variables in PythonЧтениеOperators and Expressions in PythonЧтение

Учитесь у экспертов

Joseph W. Cutrone, PhD

Associate Teaching Professor and Director of Online Programs

Applied Calculus with Python
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Обучение на Coursera

≈ 23.1 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Хинди, Японский, Казахский, Польский

Часть программы вашего университета
SymPy BasicsЧтение
Working with SymPyВидео
Introduction to Python and SymPyЗадание
02Functions19 материалов

2.1 Introduction to Functions

Theory: FunctionsВидеоTheory: More about FunctionsВидеоFunctions and Linear FunctionsЧтениеTheory: Graphing and CompositionВидеоFunctions in PythonЧтениеPython: Graphing FunctionsВидеоPython: Interactive Quadratic CalculatorВидеоSample Problems - Introduction to FunctionsЧтениеIntroduction to FunctionsЗадание

2.2 Exponential and Logarithmic Functions

Theory: Exponential FunctionsВидеоTheory: Logarithmic FunctionsВидеоTheory: The Natural LogarithmВидеоExponential and Logarithmic FunctionsЧтениеExponents and Logarithms in SymPyЧтениеSolving Equations in SymPyЧтение

Module 2 Lab

Finding an Exponential ModelЛабораторная
03Rates of Change and the Derivative21 материалов

3.1 Limits and Rates of Change

Lists and Tuples in PythonЧтениеTheory: Introduction to LimitsВидеоLimits and Rates of ChangeЧтениеTheory: Limits Involving InfinityВидеоTheory: One-Sided LimitsВидеоExamples to Find LimitsВидеоLimits and Rates of Change in SymPyЧтениеPython: Finding Limits ВидеоSample Problems - Limits and Rates of ChangeЧтениеLimits and Rates of ChangeЗадание

3.2 The Derivative

Theory: DerivativesВидеоExamples: Finding Derivatives using LimitsВидеоTheory: Using Limits to Find the Slope of the Tangent LineВидеоTheory: Higher DerivativesВидеоTheory: The Derivative as a FunctionВидеоThe DerivativeЧтение

Module 3 Lab

Graphing Tangent LinesЛабораторная
04Derivative Rules and Applications18 материалов

4.1 Derivative Rules

Theory: Derivatives of Polynomial FunctionsВидеоTheory: Derivatives of ExponentialsВидеоTheory: The Quotient RuleВидеоTheory: The Product RuleВидеоTheory: Chain RuleВидеоDerivative RulesЧтениеSample Problems - Derivative RulesЧтениеDerivative RulesЗадание

4.2 Using the Derivative

Theory: Max and Min ValuesВидеоTheory: How Derivatives Affect the Shape of a GraphВидеоMaxima, Minima, Concavity, and Inflection PointsЧтениеPython: Local Extrema CalculatorВидеоOptimization ExamplesВидеоOptimization Word ProblemsЧтение

Module 4 Lab

OptimizationЛабораторная
05Accumulated Change and Integrals17 материалов

5.1 Distance, Accumulated Change, and the Definite Integral

Theory: Area under a LineВидеоTheory: Area Under CurvesВидеоTheory: The Definite IntegralВидеоTheory: Properties of the Definite IntegralВидеоDistance, Accumulated Change, and the Definite IntegralЧтениеPython: Approximate and Exact IntegrationВидеоRiemann Sums and Definite Integrals in PythonЧтениеSample Problems - Distance, Accumulated Change, and the Definite IntegralЧтениеDistance, Accumulated Change, and the Definite IntegralЗадание

5.2 The Fundamental Theorem of Calculus

Theory: AntiderivativesВидеоTheory: The Fundamental Theorem of Calc ВидеоAntiderivatives and the Fundamental Theorem of CalculusЧтениеIndefinite Integrals in SymPyЧтениеTheory: Worked ExamplesВидеоSample Problems - The Fundamental Theorem of CalculusЧтение

Module 5 Lab

Area Between CurvesЛабораторная
Python: Exponentials and LogarithmsВидео
Sample Problems - Exponential and Logarithmic FunctionsЧтение
Exponential and Logarithmic FunctionsЗадание
Python: Finding Derivatives using SympyВидео
Derivatives in SymPyЧтение
Sample Problems - The DerivativeЧтение
The DerivativeЗадание
Using the Derivative with SymPyЧтение
Sample Problems - Using the DerivativeЧтение
Using the DerivativeЗадание
The Fundamental Theorem of CalculusЗадание