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Coding vs Data Science: A comprehensive guide to unraveling the differences

Data Science Dojo

This discipline takes raw data, deciphers it, and turns it into a digestible format using various tools and algorithms. Tools such as Python, R, and SQL help to manipulate and analyze data. Statistics helps data scientists to estimate, predict and test hypotheses.

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How to become a data scientist

Dataconomy

Data management and manipulation Data scientists often deal with vast amounts of data, so it’s crucial to understand databases, data architecture, and query languages like SQL. Skills in manipulating and managing data are also necessary to prepare the data for analysis.

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Training Sessions Coming to ODSC APAC 2023

ODSC - Open Data Science

Build Classification and Regression Models with Spark on AWS Suman Debnath | Principal Developer Advocate, Data Engineering | Amazon Web Services This immersive session will cover optimizing PySpark and best practices for Spark MLlib. Free and paid passes are available now–register here.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. Python is the most common programming language used in machine learning.

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What Does the Modern Data Scientist Look Like? Insights from 30,000 Job Descriptions

ODSC - Open Data Science

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL is expected, youll need to go beyond that. Employers arent just looking for people who can program.