Статьи по Data Science

In this comprehensive guide, we look at the most important Python libraries in data science and discuss how their specific features can boost your data science practice.

This article provides a primer on MLOps maturity models for data teams to follow and consider when evolving their machine learning capabilities.

A comprehensive guide to machine learning: understand its definition, types (supervised, unsupervised, reinforcement), tools, applications, and career opportunities.

Data cleaning takes up 80% of the data science workflow. Use this checklist to identify and resolve any quality issues with your data

Navigating the world of data certificates and certification programs can be overwhelming, from understanding the requirements to recognizing the value that each may provide. We’ll help you understand the basics so you can make the right decisions for your needs.

DataCamp recently migrated RStudio workspaces to DataCamp’s Notebook Editor which features a JupyterLab interface. This post is designed to help R users get started and be productive with JupyterLab.

Learn about the Zen of Python and discover the principles of writing clean, elegant code in Python.

Learn what a data architect does and how to launch a lucrative career in this rapidly expanding niche.

We're launching a four-day DataFramed Careers Series covering the ins and outs of building a career in data, and the different aspects of standing out from the crowd in the job hunt.

Recruiting for data roles has become extremely difficult. From a scarcity of qualified talent to time consuming assessments, the hurdles are endless. In this article, we'll go through the current state of hiring for data roles and how DataCamp can help you find and hire you data teams better.

Discover how DataCamp is helping candidates land their dream jobs and letting recruiters find the best data talent in one place.

Learn about the key differences between the two most popular data science roles, including which skill sets are required, key duties, project life cycles, and earning potential.