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Linear Programming for Data Science

Enhance your optimization techniques by learning Linear Programming for Data Science.

Instructor:

Dr. Abhinanda Sarkar
4.59
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Beginner

Level

4.5 Hrs

Learning hours

11.7K+
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Linear Programming for Data Science

4.5 Learning Hours . Beginner

Enrol free with email

Skills you’ll Learn

Linear Programming

About this course

Linear programming is an optimization technique to identify the optimal solution in a mathematical or business model for a system of linear constraints and a linear objective function. Linear Regression in Data Science is one of the hot topics today. It is a technique that identifies a linear relationship between dependent and independent variables. And in this course, you will get introduced to Linear Programming, its Graphical method, sensitivity analysis, and assumptions in Linear Programming, and some hands-on exercise.

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Course Outline

Introduction to Linear Programming

Linear programming is a mathematical modeling technique in which a linear function is maximized or minimized when subjected to various constraints. In this module, you will be introduced to linear programming. 

Graphical method
Sensitivity analysis
Assumptions in Linear Programming
Case study - Investment Problem
Case study - Portfolio optimization
Case study - Recruitment planning

Our course instructor

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Dr. Abhinanda Sarkar

Academic Director - Data Science & Machine Learning

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531.7K+ Learners
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17 Courses
Dr. Abhinanda Sarkar has B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He was a lecturer at Massachusetts Institute of Technology (MIT) and a research staff member at IBM. Post this he spent a decade at General Electric (GE). He has provided committee service for the University Grants Commission (UGC) of the Government of India, for infoDev – a World Bank program, and for the National Association of Software and Services Companies (NASSCOM). He is a recipient of the ISI Alumni Association Medal, an IBM Invention Achievement Award, and the Radhakrishan Mentor Award from GE India. He is a seasoned academician and has taught at Stanford, ISI Delhi, the Indian Institute of Management (IIM-Bangalore), and the Indian Institute of Science. Currently, he is a Full-Time Faculty at Great Lakes. He is Associate Dean at the MYRA School of Business where he teaches courses such as business analytics, data mining, marketing research, and risk management. He is also co-founder of OmiX Labs – a startup company dedicated to low-cost medical diagnostics and nucleic acid testing.

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Ratings & Reviews of this Course

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Muhammad Yasir Imtiaz

5.0

★★★★ ★
Engaging Content, Practical Applications, and Insightful Discussions
I appreciate the course's engaging content, practical applications, and insightful discussions. It offers real-world examples and interactive activities that enhance understanding. The well-structured lessons and supportive community make learning enjoyable and effective.
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Utsav adhikari

5.0

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Linear Programming for Data Science
Unlock data science potential: Learn Linear Programming with Great Learning's expert course!

Earn a certificate of completion

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Get free course content

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Learn at your own pace

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Master in-demand skills & tools

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Test your skills with quizzes

Linear Programming for Data Science

4.5 Learning Hours . Beginner

Enrol free with email

Frequently Asked Questions

Is linear programming used in Data Science?

Linear programming can be used in Data Science to find the optimal solution to a situation with linear constraints and objective function. You can learn more about the role of linear programming in Data Science through Great Learning’s free Linear Programming for Data Science course.

Will I get a certificate after completing this Linear Programming for Data Science free course?

Yes, you will get a certificate of completion for Linear Programming for Data Science after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.

How much does this Linear Programming for Data Science course cost?

It is an entirely free course from Great Learning Academy. Anyone interested in learning the basics of Linear Programming for Data Science can get started with this course.

Is there any limit on how many times I can take this free course?

Once you enroll in the Linear Programming for Data Science course, you have lifetime access to it. So, you can log in anytime and learn it for free online.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.

Why choose Great Learning Academy for this free Linear Programming for Data Science course?

Great Learning Academy provides this Linear Programming for Data Science course for free online. The course is self-paced and helps you understand various topics that fall under the subject with solved problems and demonstrated examples. The course is carefully designed, keeping in mind to cater to both beginners and professionals, and is delivered by subject experts. Great Learning is a global ed-tech platform dedicated to developing competent professionals. Great Learning Academy is an initiative by Great Learning that offers in-demand free online courses to help people advance in their jobs. More than 5 million learners from 140 countries have benefited from Great Learning Academy's free online courses with certificates. It is a one-stop place for all of a learner's goals.

What are the steps to enroll in this Linear Programming for Data Science course?

Enrolling in any of the Great Learning Academy’s courses is just one step process. Sign-up for the course, you are interested in learning through your E-mail ID and start learning them for free online.

Will I have lifetime access to this free Linear Programming for Data Science course?

Yes, once you enroll in the course, you will have lifetime access, where you can log in and learn whenever you want to.

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Linear Programming in Data Science

Linear programming for Data Science is a course designed to help learners understand and apply the principles of linear programming in the Data Science context. It provides an in-depth understanding of linear programming principles, assumptions, and applications and their practical applications in areas such as optimization and decision-making. The course includes a wide range of topics, including introduction to linear programming, graphical method, sensitivity analysis, and assumptions in linear programming.

This course on Linear Programming for Data Science is designed to provide learners with a comprehensive overview of the principles and techniques of linear programming. Learners will learn to apply linear programming to solve various optimization problems. The course will begin by discussing the basics of linear programming, definitions, and the different mathematical models.

The graphical method is used to represent linear programming problems graphically. This method is used to identify the optimal solution and analyze the solution's sensitivity to changes in the problem parameters. The graphical method is used to identify the optimal solution and also analyze the sensitivity of the solution to changes in the problem parameters.

Sensitivity analysis is also included in this course. This is an essential tool used in linear programming to examine the effects of changes in the parameters or the problem's constraints on the optimal solution. This method is used to identify the optimal solution and analyze the sensitivity of the solution to changes in the problem parameters.

Finally, the assumptions in linear programming are discussed. This includes the assumptions of linearity, homogeneity, additivity, convexity, and non-negativity. These assumptions help to simplify the optimization process, leading to faster and more accurate solutions.

This course on linear programming for data science provides learners with a comprehensive understanding of the principles, assumptions, and applications of linear programming. Learners will gain a strong understanding of the mathematical models and the graphical methods used to solve linear programming problems. Furthermore, they will gain an understanding of the assumptions of linear programming and the sensitivity analysis used to identify the optimal solution. This course is an excellent resource for learners interested in applying linear programming in the data science field.

 

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