Shortest way of learning algebra, calculus, statistics, trigonometry, and linear algebra through coding in Python
Learn Mathematics in Python:
What you’ll learn
- Pre Algebra.
- Algebra.
- Linear Algebra.
- Abstract Algebra.
- Integral Calculus.
- Statistics.
- Pure Mathematics.
- Differential Calculus.
- Graphing.
- Trigonometry.
- Regression and Data visualization.
- Correlation Coefficient.
- Latex in Python.
- Complex Numbers System.
- Applied Mathematics in Python.
- Probability.
- Matplotlib, Numpy, and Sympy.
- Coordinate Geometry.
- Applied Mathematics.
- Functional Mathematics.
Course Content
- Introduction –> 3 lectures • 16min.
- Algebra –> 2 lectures • 14min.
- Variables in Python –> 1 lecture • 4min.
- Trigonometry in Python –> 1 lecture • 5min.
- Pre Algebra and Algebra in Python –> 5 lectures • 17min.
- Sketching –> 3 lectures • 42min.
- Exponential and Logarithmic Functions –> 1 lecture • 5min.
- Linear Functions, Polynomials and Complex Number System –> 1 lecture • 53min.
- Vectors and Data Visualization Operation –> 1 lecture • 27min.
- Linear Algebra –> 3 lectures • 1hr 58min.
- Statistics in Python –> 1 lecture • 53min.
- Calculus in Python –> 1 lecture • 1hr 2min.
Requirements
- Internet connection.
- Interest in learning new things.
Learn Mathematics in Python:
In this course, you will learn mathematics through coding in Python. We will start from basics mathematical coding in python and end by using the teaching techniques “Maxims of the teaching”(simple to abstract). In the beginning, we will do simple math algorithms and formulas in Python. We will also use the screen board before coding in python to illustrate the concepts and understanding of definitions and examples. After an hour by dipping in the course, you will jump toward the next level of learning. Then we will switch our techniques from basics math to algebra. Algebra coding is super interesting in Python. We will define the algebra topics by examples and code them in Python. Graphing of different algebraic equations is one of the extra interesting parts of this section.
Our next will be linear algebra, We will master matrices, determinants, Gauss method, linear combination, basis, and vectors, norms, linear dependence, and independence.
In statistics, you will learn to mean, mode, median, standard deviation, regression, and correlation analysis for both group and ungrouped data by coding in Python. We will also learn about probability along with statistics.
Calculus: is an advanced topic and here we will master limits and continuity, differentiation, integration, plane curve problems, and coordinate geometry by coding in Python.
Sketching: We have learned to sketch mathematical functions at high school but do you know how this is super interesting in Python by using Python libraries like Matplotlib and Numpy.
Trigonometry: We shall learn the trigonometric identities, angles in radian, and degree through coding in Python
Regression and Correlation Analysis: Here we shall learn the coding of regressional and correlational data in Python. We will plot the scattering curves as well to show the data visualization in Python.
Complex Numbers System: A comprehensive discussion has been made about complex number systems. How to add, subtract, multiply, and how to find the argument of complex numbers through coding in Python.
Latex in Python: This section includes the abstract equation in Python. Latex is another library of Python. How to write mathematics in Python. We shall do a comprehensive discussion in this section.
Course Objective:
1. We want o give the next level of understanding of mathematics from casual calculation to the use of Python.
2. Learning new techniques of learning mathematics.
3. Explanation of simple and easy concepts by the use of Python
4. Making learning possible for every student to learn mathematics.
5. New exploration for all levels of learners.