Optimization is the way of life. We all have finite resources and time and we want to make the most of them. From using your time productively to solving supply chain problems for your company – everything uses optimization.
And that’s where learning linear programming will make you a better data science professional.
We are solving optimization problems everyday - without realizing it. Think of how you distributed the chocolate among your peers or siblings - that’s your way of optimizing the situation. On the other hand devising inventory and warehousing strategy for an e-tailer can be very complex. Millions of SKUs with different popularity in different regions to be delivered in defined time and resources.
And linear programming helps us solve these optimization problems with ease and efficiency. As a data science professional, you are bound to come across these optimization problems that you will solve using linear programming.
Simply put, you should know what linear programming is, and the different methods to solve linear programming problems.
- What is linear programming?
- Why should you learn linear programming?
- What are the different linear programming terminologies?
- What programming languages should you know to apply linear programming?
- Can I solve a linear programming problem using Microsoft Excel?
- What kind of projects can you do using linear programming?
- Interview questions - what to expect around linear programming?
- What are the applications of linear programming in real-life?
This course explains the concept of linear programming in simple English. We have kept the content as simple as possible so even beginners will be able to quickly pick up how linear programming works. You will, of course, also learn how to solve linear programming problems!
Who is the Introduction to Linear Programming for Data Science Professionals Course for?
This course is for anyone who:
- Wants to learn about linear programming
- Wants to understand how linear programming works and how to solve linear programming problems
- Isn’t a programmer but is curious how to work on linear programming problems (MX Excel!)
- Wants to master a niche branch of data science to gain a competitive advantage over their peers
- Is looking to solve optimization problems using linear programming
What do you need to get started with the Introduction to Linear Programming for Data Science Professionals course?
Here’s what you’ll need:
- A working laptop/desktop with 4 GB RAM
- A working Internet connection
- Working knowledge of Microsoft Excel
- Optional - Basic knowledge of R
That’s it! You’re all set to learn linear programming and solve optimization problems!
What is linear programming?
As we discuss in the course: “Linear programming is a simple technique where we depict complex relationships through linear functions and then find the optimum points. The important word in the previous sentence is depict. The real relationships might be much more complex – but we can simplify them to linear relationships.”
Why should you learn linear programming?
I’m sure you’ve had this question ever since you came across linear programming. Well - here’s the good news. The use cases of linear programming are all around us.
We use linear programming in both our personal and professional fronts. We use linear programming when we are driving from home to work and want to take the shortest route. Or when we have a project delivery we make strategies to make our team work efficiently for on time delivery. You get the idea!
What are the different linear programming terminologies?
Here are the key terminologies you’ll come across when learning linear programming:
● Decision variables
● Objective function
● Non-negativity restriction
We will cover each of these terms in detail inside the course.
What programming languages should you know to apply linear programming?
We showcase how to solve a linear programming problem using R in the course. However, you don’t need to know programming to learn linear programming! As we show in the course, you can also use Excel and even manual methods to solve a typical linear programming problem.
In real life, you might need to rely a lot more on languages like R and Python since the dataset you’ll be working with might be too big for Excel.
Can I solve a linear programming problem using Microsoft Excel?
Of course! That’s another powerful aspect of linear programming - you don’t need to master a programming language to solve linear programming problems. The ‘OpenSolver’ feature of Excel works perfectly and is made for linear programming problems.
What kind of projects can you do using linear programming?
Any project that requires optimization can be used to apply linear programming. As you’ll see inside the course, we solve various types of linear programming problems, including a fascinating case study of a chocolate manufacturing business wanting to maximize its profits.
Interview questions - what to expect around linear programming?
This is an interesting question. Personally, this is a mixed round as far as data science interviews go. You might not get a direct question on linear programming, such as “How would you use linear programming to solve an optimization problem?”.
Instead, there’s a high probability of getting a case study like optimizing delivery routes. This is where your knowledge of linear programming will come in handy.
We have seen a lot of folks not paying attention to this branch of data science - and that’s a mistake. It’s an excellent tool to have at your fingertips and will make your life in the data science field a lot easier.
What are the applications of linear programming in real-life?
There are innumerable applications of linear programming in the real-world. Here are 4 key ones that you'll come across:
● Manufacturing industries use linear programming for analyzing their supply chain operations
● Organized retail for shelf space optimization
● Optimizing Delivery Routes. Think Zomato, Swiggy, Amazon, Uber, Ola, etc.
● Machine Learning algorithms!
- How to Use the Mini-Course Template
- AI&ML Blackbelt Plus Program (Sponsored)
- Introduction to Linear Programming
- What is Linear Programming
- Formulating a problem – Let’s manufacture some chocolates
- Common Terminologies in Linear Programming
- Process to Formulate a Linear Programming Problem
- Using Graph: Problem
- Using Graph : Solution
- Using R Programing: Problem
- Using R Programing: Solution
- Using Open-Solver(Excel):Problem
- Using Open-Solver(Excel): Solution
- Method 1 - Simplex Method(Question)
- Simplex method: Solution
- Method 2 - Northwest Corner Method(Problem)
- Northwest Corner Method: Solution
- Method 3 - Least Cost Method
- What Next?
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Who should take the Introduction to Linear Programming for Data Science Professionals course?
This course is designed for anyone who wants to understand what linear programming is, how it works, what are the different linear programming problems out there, and how to solve them. This is an under-appreciated topic in data science that will propel your skillset to a entirely different level.
I have decent programming experience but no background in machine learning. Is this course right for me?
Absolutely! This course covers a topic that is not reliant on machine learning knowledge. That’s the beauty of linear programming - you will rely on a bit of math and a programming language or tool (like MS Excel). That’s all you need to learn and solve linear programming problems!
What is the fee for the course?
This course is free of cost! All you need to do is sign up and get started.
How long would I have access to the “Introduction to Linear Programming for Data Science Professionals” course?
Once you register, you will have 6 months to complete the course. If you visit the course 6 months after your initial registration, you will need to enroll in the course again. Your past progress will be lost.
How much effort do I need to put in for this course?
You can complete the “Introduction to Linear Programming for Data Science Professionals” course in a few hours.
I’ve completed this course and have a good grasp on linear programming. What should I learn next?
The next step in your journey is to build on what you’ve learned so far. We recommend taking the popular “Applied Machine Learning” course.
Can I download the videos in this course?
We regularly update the “Introduction to Linear Programming for Data Science Professionals” course and hence do not allow videos to be downloaded. You can visit the free course anytime to refer to these videos.