Data Science and Big Data Analytics v2 Course Overview

The Data Science and Big Data Analytics v2 course is designed to introduce learners to the expansive world of data science and big data analytics. It covers the essentials of the field, including the defining characteristics of big data and the important business drivers that necessitate the use of big data analytics. The course outlines the pivotal role of the data scientist and the skills necessary to succeed in the field.

Through a structured Data analytics lifecycle, learners will grasp the sequential phases of a project including discovery, data preparation, model planning, and model building, with associated activities and roles. The course delves into Initial data analysis using R, statistical measures, and Hypothesis testing.

Advanced analytics techniques such as k-means clustering, linear and logistic regression, decision trees, and Text analytics are explored. The course also addresses the technological challenges of big data, presenting tools like MapReduce and Apache Hadoop, along with In-database analytics and Advanced SQL methods.

Finally, it emphasizes the importance of operationalizing analytics projects and the effective communication of findings through data visualization techniques, ensuring insights are actionable and impactful. This comprehensive course is an invaluable resource for those looking to master data science and big data analytics.