The ultimate guide to data science interviews. Developed by FAANG engineers, it covers Python, algorithms, ML concepts, and interview questions. Get interview-ready in just a few hours.

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This course will increase your skills to crack the data science or machine learning interview. You will cover all the most common data science and ML concepts coupled with relevant interview questions.
You will start by covering Python basics as well as the most widely used algorithms and data structures. From there, you will move on to more advanced topics like feature engineering, unsupervised learning, as well as neural networks and deep learning.
This course takes a non-traditional approach to interview prep, in that it focuses on data science fundamentals instead of open-ended questions.

In all, this course will get you ready for data science interviews. By the time you finish this course, you will have reviewed all the major concepts in data science and will have a good idea of what interview questions you can expect.

Data Science Interview Handbook

Backtracking is an approach for recursively solving a problem. Backtracking  does this by solving small pieces one by one and removing the parts that do not contribute to the solution.

This is a recursive approach. When a function calls itself, it is called recursion, which helps break down the problem into smaller pieces, solve the smaller parts, and return the combined solution.



Every recursive function should have a base case, otherwise it will trap the infinite number of calls. The base case is also known as the terminating condition.

When we call the function again, the ideal case is to move towards the base condition and exit from there. Let’s consider this technique using the example of calculating the factorial of a number.

The factorial of a number is represented by n!. This is the multiplication of all the numbers from 1 to n.

$$4! = 4 * 3 * 2 * 1 = 24$$

$$6! = 6 * 5 * 4 * 3 * 2 * 1 = 720$$

We have to write a function that takes a number and returns the factorial of that number. First, let's solve this problem without using recursion. 


Learn how to use backtracking. It is an efficient technique for solving problems using recursion.

Are You Ready to Become a Data Scientist?

Python Basics

Python Libraries

More Data Science Tools

Data Structures and Algorithms - I

Data Structures and Algorithms - II

Statistics and Probability

Feature Engineering

Basics of Machine Learning

Regression

Classification

Unsupervised Learning

Advanced Topics in Machine Learning

Conclusion

Backtracking