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12 data science certifications that will pay off

CIO Business Intelligence

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

Predictive analytics in business Predictive analytics draws its power from a wide range of methods and technologies, including big data, data mining, statistical modeling, machine learning, and assorted mathematical processes. Manufacturing: Predict the location and rate of machine failures.

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. Without big data in predictive analytics, these descriptive models can’t offer a competitive advantage or negotiate future outcomes.

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

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Machine learning and deep learning are both subsets of AI.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

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3 Key Components of the Interdisciplinary Field of Data Science

Domino Data Lab

Data science is a field that uses math and statistics as part of a scientific process to develop an algorithm that can extract insights from data. All models are not made equal. After cleaning, the data is now ready for processing. At this stage, data scientists begin writing code for computation and model-building.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. A targeted approach will optimize the user experience and enhance an organization’s ROI.