Linear Programming in Data Science: College/University Level

What you'll learn

Coordinate system

Locations of points in coordinate system

Linear Inequalities

Practical examples of linear inequalities

Graphing of linear inequalities

Solution of linear inequalities

Properties of linear inequality

Linear programming

Objective functions

Optimal Solutions

Linear Programming theorem

Solution regions

Solution regions of constrains with respect to objective functions

Requirements

Basics of mathematics

Description

In this course, you will learn all about the mathematical optimization of linear programming in data science. This course is very unique and has its own importance in its respective disciplines. Data science and business study heavily rely on optimization. Optimization is the study of analysis and interpreting mathematical data under special rules and formulas. Thousands of students worldwide are searching this topic of Linear Programming in Data Science but they can't find the complete courses in Linear Programming in Data Science.

The length of the course is more than 6 hours and there are a total of more than 4 sections in this course. The quality and quantity of the course are super and you will enjoy the course all the way during the course.

The course is prepared according to the current needs of the students and I was much asked to prepare this course and then finally I started working on it and now it is life. Many students around the globe are taking this type of course and there was nothing in the online learning platform including YouTube and I think it is good for Udemy that they have such types of courses.

In the first section of the course, we have discussed the coordinate system to develop an understanding of the basics of linear programming. While in the second section you will master the basics and advance concepts of linear inequality and finally you will get jump into Linear Programming for Data Science and Business Analysis

The question-answer section is available for the students where they can ask as many questions as they can ask and I will respond to each of your questions promptly. The more questions that you will ask the more are learning to master your concepts. It is found that the students who ask the more question are more likely to be favorite students in their learning perspectives.

Linear optimization or linear programming is considered as the mathematical study of data science and business analytics. Therefore the students which are good at mathematics can take this course in an efficient way. However, I have tried my best to complete each section in an easy way. The most important thing is when you are being asked for the questions as you can put as many you want then why not you should put So just keep in touch with your instructor and don't feel shy or hesitant to talk with your instructor.

Remember that I am teaching on Udemy for the past 3 years and have a total of 18 years of teaching experience. I am a master in applied mathematics and give solutions to the people where Math has its applications. I have changed the life of many students around the world from my experience and polishing my world which has math difficulty.

Who this course is for:

Data science, machine learning, deep learning, artificial intelligence





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