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Data Science 101: 9 Terms You Should Know

Before you can be a data scientist, you have to be able to speak like a data scientist.

Think of learning how to talk about data science like learning a new language. There are a few fundamental words to be learned and mastered. From there, it’s a matter of building out your data science vocabulary as you come across new ideas and concepts. Luckily, you can learn how to talk like a data scientist faster than you might have thought.

We go over nine terms that every beginning data scientist should know. To make each data science term more relatable, we provide a real-world example to show how the concept is used. Read through each example and answer the poll with your best guess at what each term means. The full list of definitions can be found at the end of this post.

Enjoy learning to talk data!

Artificial Intelligence

Why Edge Computing Might Transform Autonomous Cars

Real-world use: An autonomous vehicle that can learn to identify and react to driving obstacles in real-time.

You can think of artificial intelligence as ___

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Data Lake

Data Science 101: 9 Terms You Should Know

Real-world use: An enterprise looking for reliable, accessible storage of petabytes of data that has no need for immediate analysis.

You can think of a data lake as ___

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Database

Data Science 101: 9 Terms You Should Know

Real-world use: An ecommerce website that must process data associated with millions of users browsing for products, reading and writing reviews, and placing orders.

You can think of a database as ___

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Data Warehouse

Data Science 101: 9 Terms You Should Know

Real-world use: A handful of internal users at an enterprise looking to find the fastest growing product and the most profitable product categories.

You can think of a data warehouse as ___

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Heteroscedasticity, Heteroscedastic data

Data Science 101: 9 Terms You Should Know

Real-world use: A viral social media post that has garnered thousands of comments and millions of views in a short period of time.

You can think of heteroscedastic data as ___

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Image Recognition

Data Science 101: 9 Terms You Should Know

Real-world use: An automobile manufacturer that wants to detect and alert drivers who may be fatigued.

You can think of image recognition as ___

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Machine Learning

Data Science 101: 9 Terms You Should Know

Real-world use: An online retailer that wants to find and display the products to a user that have the highest chance of being bought.

You can think of machine learning as ___

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Natural Language Processing

Data Science 101: 9 Terms You Should Know

Real-world use: A digital assistant that identifies and presents relevant information based on your voice instructions.

You can think of natural language processing as ___

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Visualization

Data Science 101: 9 Terms You Should Know

Real-world use: A university that wants to create a dashboard to understand the factors—such as enrollment, course offerings, and class sizes—that impact student success.

You can think of data visualization as ___

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Term Definitions:

Artificial intelligence – the ability of machines to use logic and advanced computation to learn and make decisions similar to humans

Data lake – a low-cost, reliable storage solution that’s accessible from anywhere

Database – a system where data can be stored, accessed, and transformed

Data warehouse – the place where companies mine data for business intelligence

Heteroscedasticity, heteroscedastic data – data that moves quickly and changes often

Image recognition – the use of computers to understand, identify and classify objects

Machine learning – an application of computer science to train machines using advanced models to understand patterns in data

Natural language processing – the use of computers to interpret and respond to spoken human language

Visualization – a method to understand the value of data visually and intuitively

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