This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Statistics : Fundamental statistical concepts and methods, including hypothesistesting, probability, and descriptive statistics. R : Often used for statistical analysis and data visualization.
Skills and Tools of Data Scientists To excel in the field of Data Science, professionals need a diverse skill set, including: Programming Languages: Python, R, SQL, etc. Statistical Analysis: Hypothesistesting, probability, regression analysis, etc. Data Visualization: Matplotlib, Seaborn, Tableau, etc.
By the end of this blog, you will feel empowered to explore the exciting world of Data Science and achieve your career goals. Proficiency with tools like Tableau , Matplotlib , and ggplot2 helps create charts, graphs, and dashboards that effectively communicate insights to stakeholders.
Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines principles from statistics, mathematics, computerscience, and domain-specific knowledge to analyse and interpret complex data.
We organize all of the trending information in your field so you don't have to. Join 17,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content