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Big Data Syllabus: A Comprehensive Overview

Pickl AI

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

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Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

Descriptive Analytics Projects: These projects focus on summarizing historical data to gain insights into past trends and patterns. Examples include generating reports, dashboards, and data visualizations to understand business performance, customer behavior, or operational efficiency.

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Introduction to R Programming For Data Science

Pickl AI

Packages like stats, car, and survival are commonly used for statistical modeling and analysis. · Data Visualization : R offers several libraries, including ggplot2, plotly, and lattice, that allow for the creation of high-quality visualizations.