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edX

Big Data

University of Adelaide via edX Micromasters

Overview

Big data is changing the way businesses operate. Driven by a new scale of data collection that provides massive levels of information, businesses are now able to analyse and gather data insights to make better-informed decisions.

Data scientists and business analysts are in high-demand as companies look to use data to improve their business operations.

In this Big Data MicroMasters program, you will learn tools and analytical methods to use data for decision-making, collect and organise data at scale, and gain an understanding of how data analysis can help to inform change within organisations.

You’ll develop both the technical and computational skills that are in high demand across a range of industries. You’ll develop critical skills in programming for data science, computational thinking, algorithm design, big data fundamentals, and data-driven analysis, with plenty of opportunities to apply and explore your new learnings through a range of case studies.

Syllabus

Courses under this program:
Course 1: Programming for Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems.



Course 2: Computational Thinking and Big Data

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets.



Course 3: Big Data Fundamentals

Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.



Course 4: Big Data Analytics

Learn key technologies and techniques, including R and Apache Spark, to analyse large-scale data sets to uncover valuable business information.



Course 5: Big Data Capstone Project

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project.



Courses

Taught by

Aneta Neumann, Katrina Falkner, ​Claudia Szabo, Nick Falkner, David Suter, Lewis Mitchell, Simon Tuke, Frank Neumann, Gary Glonek, Lingqiao Liu, Gavin Meredith, Ian Knight, Markus Wagner, Wanru (Kelly) Gao and Vahid Roostapour

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