Data Science Interview Handbook

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.

Intermediate

72 Lessons

Certificate of Completion

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.

AI-POWERED

Mock Interview

Explanations

AI-POWERED

Mock Interview

Explanations

This course includes

140 Playgrounds

205 Quizzes

This course includes

140 Playgrounds

205 Quizzes

Course Overview

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...Show More

Course Content

Are You Ready to Become a Data Scientist?

Learn how to use data science principles, processes, and advancements for solving real-world problems.

Data Science and YOU!

Data Science Process Pipeline

Advancements in Data Science

Python Basics

Look at Python basics, including variables, decision-making, loops, functions, lists, dictionaries, and classes.

Introduction to Python

Python Libraries

Examine essential Python libraries for data science, from NumPy to TensorFlow.

More Data Science Tools

Grasp the fundamentals of essential data science tools for analysis, visualization, and model deployment.

Data Structures and Algorithms - I

Deepen your knowledge of essential data structures and algorithms for effective problem-solving.

Why Data Structures and Algorithms are Important

Data Structures and Algorithms - II

4 Lessons

Follow the process of solving problems with Greedy, Divide and Conquer, Backtracking, and Dynamic Programming.

Statistics and Probability

6 Lessons

Piece together the parts of statistics, correlation, probability, random variables, and distributions.

Feature Engineering

6 Lessons

Try out feature engineering techniques to enhance data quality and improve model performance.

Basics of Machine Learning

3 Lessons

Unpack the core of machine learning problems, model performance evaluation, and enhancement strategies.

10.

Regression

5 Lessons

Break apart regression principles, from simple to nonparametric, while mastering model assessment metrics.

11.

Classification

7 Lessons

Find out about classification techniques, including linear classifiers, logistic regression, and decision trees.

12.

Unsupervised Learning

4 Lessons

Take a closer look at various clustering methods and nearest neighbor search in unsupervised learning.

13.

Advanced Topics in Machine Learning

4 Lessons

Tackle Neural Networks, Deep Learning issues, Recommendation Engines, and Natural Language Processing advancements.

14.

Conclusion

2 Lessons

Master the steps to begin your data science career, with emphasis on continuous learning.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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Put your skills to the test in a simulated interview setting. Receive personalized feedback based on your performance. Available in Premium & Premium Plus plans.

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