Applied Calculus with Python
- Offered byCoursera
Applied Calculus with Python at Coursera Overview
Duration | 23 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Applied Calculus with Python at Coursera Highlights
- Earn a Certificate upon completion
Applied Calculus with Python at Coursera Course details
- 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
Applied Calculus with Python at Coursera Curriculum
Introduction to Python
Introduction to Python
Working with SymPy
Options for Using Python
Data Types and Variables in Python
Operators and Expressions in Python
SymPy Basics
Introduction to Python and SymPy
Functions
Theory: Functions
Theory: More about Functions
Theory: Graphing and Composition
Python: Graphing Functions
Python: Interactive Quadratic Calculator
Theory: Exponential Functions
Theory: Logarithmic Functions
Theory: The Natural Logarithm
Python: Exponentials and Logarithms
Functions and Linear Functions
Functions in Python
Sample Problems - Introduction to Functions
Exponential and Logarithmic Functions
Exponents and Logarithms in SymPy
Solving Equations in SymPy
Sample Problems - Exponential and Logarithmic Functions
Introduction to Functions
Exponential and Logarithmic Functions
Rates of Change and the Derivative
Theory: Introduction to Limits
Theory: Limits Involving Infinity
Theory: One-Sided Limits
Examples to Find Limits
Python: Finding Limits
Theory: Derivatives
Examples: Finding Derivatives using Limits
Theory: Using Limits to Find the Slope of the Tangent Line
Theory: Higher Derivatives
Theory: The Derivative as a Function
Python: Finding Derivatives using Sympy
Lists and Tuples in Python
Limits and Rates of Change
Limits and Rates of Change in SymPy
Sample Problems - Limits and Rates of Change
The Derivative
Derivatives in SymPy
Sample Problems - The Derivative
Limits and Rates of Change
The Derivative
Derivative Rules and Applications
Theory: Derivatives of Polynomial Functions
Theory: Derivatives of Exponentials
Theory: The Quotient Rule
Theory: The Product Rule
Theory: Chain Rule
Theory: Max and Min Values
Theory: How Derivatives Affect the Shape of a Graph
Python: Local Extrema Calculator
Optimization Examples
Derivative Rules
Sample Problems - Derivative Rules
Maxima, Minima, Concavity, and Inflection Points
Optimization Word Problems
Using the Derivative with SymPy
Sample Problems - Using the Derivative
Derivative Rules
Using the Derivative
Accumulated Change and Integrals
Theory: Area under a Line
Theory: Area Under Curves
Theory: The Definite Integral
Theory: Properties of the Definite Integral
Python: Approximate and Exact Integration
Theory: Antiderivatives
Theory: The Fundamental Theorem of Calc
Theory: Worked Examples
Distance, Accumulated Change, and the Definite Integral
Riemann Sums and Definite Integrals in Python
Sample Problems - Distance, Accumulated Change, and the Definite Integral
Antiderivatives and the Fundamental Theorem of Calculus
Indefinite Integrals in SymPy
Sample Problems - The Fundamental Theorem of Calculus
Distance, Accumulated Change, and the Definite Integral
The Fundamental Theorem of Calculus
Applied Calculus with Python at Coursera Admission Process
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