Hoppa till huvudinnehållet
HemPython

Kurs

Practicing Coding Interview Questions in Python

AvanceradKunskapsnivå
Uppdaterad 2025-02
Prepare for your next coding interviews in Python.
Starta kursen gratis
PythonProgramming
4 tim
16 videor
61 Övningar
5,050 XP
28,693
Intyg om genomförande

Skapa ditt kostnadsfria konto

Fortsätt med GoogleVisa fler alternativ

eller


Genom att fortsätta godkänner du våra Användarvillkor, vår Integritetspolicy och att dina uppgifter lagras i USA.

Omtyckt av lärande på tusentals företag

Group

Utbildar du ett team?

Prova för företag

Kursbeskrivning

Coding interviews can be challenging. You might be asked questions to test your knowledge of a programming language. On the other side, you can be given a task to solve in order to check how you think. And when you are interviewed for a data scientist position, it's likely you can be asked on the corresponding tools available for the language. In either of the cases, to get a cool position as a data scientist, you need to do a little work to perform the best. That's why it's very important to practice in order to prove your expertise! This course serves as a guide for those who just start their path to become a professional data scientist and as a refresher for those who seek for other opportunities. We'll go through fundamental as well as advanced topics that aim to prepare you for a coding interview in Python. Since it is not a normal step-by-step course, some exercises can be quite complex. But who said that interviews are easy to pass, right?

Förkunskapskrav

Python ToolboxRegular Expressions in PythonData Manipulation with pandas
1

Python Data Structures and String Manipulation

In this chapter, we'll refresh our knowledge of the main data structures used in Python. We'll cover how to deal with lists, tuples, sets, and dictionaries. We'll also consider strings and how to write regular expressions to retrieve specific character sequences from a given text.
Starta kapitel
2

Iterable objects and representatives

This chapter focuses on iterable objects. We'll refresh the definition of iterable objects and explain, how to identify one. Next, we'll cover list comprehensions, which is a very special feature of Python programming language to define lists. Then, we'll recall how to combine several iterable objects into one. Finally, we'll cover how to create custom iterable objects using generators.
Starta kapitel
3

Functions and lambda expressions

This chapter will focus on the functional aspects of Python. We'll start by defining functions with a variable amount of positional as well as keyword arguments. Next, we'll cover lambda functions and in which cases they can be helpful. Especially, we'll see how to use them with such functions as map(), filter(), and reduce(). Finally, we'll recall what is recursion and how to correctly implement one.
Starta kapitel
4

Python for scientific computing

This chapter will cover topics on scientific computing in Python. We'll start by explaining the difference between NumPy arrays and lists. We'll define why the former ones suit better for complex calculations. Next, we'll cover some useful techniques to manipulate with pandas DataFrames. Finally, we'll do some data visualization using scatterplots, histograms, and boxplots.
Starta kapitel
Practicing Coding Interview Questions in Python
Kurs
slutförd

Tjäna ett prestationsbevis

Lägg till det här beviset i din LinkedIn-profil, ditt CV eller din meritförteckning
Dela det i sociala medier och i din medarbetarutvärdering
Registrera dig nu

Gå med 19 miljoner lärande och börja Practicing Coding Interview Questions in Python idag!

Skapa ditt kostnadsfria konto

Fortsätt med GoogleVisa fler alternativ

eller


Genom att fortsätta godkänner du våra Användarvillkor, vår Integritetspolicy och att dina uppgifter lagras i USA.

Utveckla dina datakunskaper med DataCamp för mobilen

Gör framsteg när du är på språng med våra mobila kurser och dagliga 5-minuters kodningsutmaningar.