Knowledge Hut

DECEMBER 22, 2023

Statistics are important for analyzing and interpreting the data. Programming: There are many programming languages out there that were created for different purposes. Some offer great productivity and performance to process significant amounts of data, making them better suitable for data science.

Portfolio 98

Portfolio Data Science Programming Language Scala 98

AltexSoft

OCTOBER 30, 2021

Regardless of the structure they eventually build, it’s usually composed of two types of specialists: builders, who use data in production, and analysts, who know how to make sense of data. Distinction between data scientists and engineers is similar. Data scientist’s responsibilities — Datasets and Models.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Edureka

JANUARY 18, 2024

Need for Data Science Data scientists play a vital part in improving decision-making, increasing business efficiency, and turning massive volumes of data into actionable insights. They manage intricate datasets, create forecasting models, and examine consumer behavior to deliver tailored experiences.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

ProjectPro

MARCH 7, 2016

It is necessary for individuals to bridge the wide gap between the academia big data programs and the industry practices. Most of the big data certification initiatives come from the industry with the intent to establish equilibrium between the supply and demand for skilled big data professionals.

Big Data 40

Big Data Certification Hadoop Big Data Skills 40