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The top 15 big data and data analytics certifications

CIO Business Intelligence

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization. Candidates have 90 minutes to complete the exam.

Big Data 125
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12 data science certifications that will pay off

CIO Business Intelligence

The certification consists of several exams that cover topics such as machine learning, natural language processing, computer vision, and model forecasting and optimization. You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting.

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10 Essential Data-Driven B2B Email Marketing Strategies

Smart Data Collective

Yo can use big data to make this easier. One option is to use data mining tools to learn more about the challenges people are making. You can assimilate data from various polls to learn more about the pain points of your target customers and create content that addresses them. Email marketing is all about experimentation.

B2B 105
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Top 8 predictive analytics tools compared

CIO Business Intelligence

Most tools offer visual programming interfaces that enable users to drag and drop various icons optimized for data analysis. Visual IDE for data pipelines; RPA for rote tasks. The visual IDE offers more than 300 options that can be joined together to form a complex pipeline. Highlights. Deployment.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs. This allowed us to derive insights more easily.”

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.

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How Do Super Rookies Start Learning Data Analysis?

FineReport

Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. In addition, tools for data analysis and data mining are also important. Excel, Python, Power BI, Tableau, FineReport are frequently used by data analysts.