The ultimate guide to data science interviews. Get interview-ready in just a few hours with proven strategies developed by FAANG engineers. Practice with interview questions from top companies.

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This course will answer all your queries about starting your career in data science. There is only one prerequisite to taking this course—you are learning to program or working in a job where programming is used.

In this course, your queries regarding career in data science get answered. These include career transitioning or starting, efficient job search, common mistakes that people make, educational requirements, list of topics to study, resume creation, do's and don'ts, job search sites, interview process and the types of interview questions and answers. You will learn about how to navigate through various hurdles to reach your career goals.

After completing this course, you will know how to prepare for data science interviews. Specifically, what you should do and what you should not do. This course will guide you to becoming a self-taught data scientist and speed up your learning path toward careers in data science.

Deep Dive Into Data Science Interview

**Python** is a free and open-source programming language that can run on operating systems such as Windows, Linux, Unix, and macOS. You can use it for data analysis, visualization, website development, software development, automation, and so on. The most attractive thing is its syntax, which imitates the natural language we humans speak, as shown in the examples below:

# Program to check if 9 is a prime number or not
num = 9
# define a flag variable
flag = False
# prime numbers are greater than 1
if num > 1:
    # check for factors
    for i in range(2, num):
        if (num % i) == 0:
            # if factor is found, set flag to True
            flag = True
            # break out of loop
            break
# check if flag is True
if flag:
    print(num, "is not a prime number")
else:
    print(num, "is a prime number")

import scipy.stats as stats
data = [151,153,158,148,153,155,149,151,152,149,147,154]
# perform one sample t-test
t_statistic, p_value = stats.ttest_1samp(a=data, popmean=150)
print(t_statistic , p_value)

**R** is a free and open-source programming language that can run on operating systems such as Windows, Linux, Unix, and macOS. You can use it for data analysis and visualization. The most attractive thing about R is how easy it is to perform statistical computing, as shown in the examples below:

# Program to check if 9 is a prime number or not
num = 9
flag = 0
# prime numbers are greater than 1
if(num > 1) {
    # check for factors
    flag = 1
    for(i in 2:(num-1)) {
        if ((num %% i) == 0) {
            flag = 0
            break
        }
    }
} 
if(num == 2) flag = 1
if(flag == 1) {
    print(paste(num,"is a prime number"))
} else {
    print(paste(num,"is not a prime number"))
}

Discover the data science tools and their required level of expertise.

Getting Started

Data Science Job Outline

What to Study

Portfolio Making

Expertise and Readiness

Efficient Data Science Job Search

The Interview

Types of Questions and Answers

Epilogue

Python vs. R