MicroMasters® Program in Big Data

edX

Course Features

Duration

12 months

Delivery Method

Online

Available on

Limited Access

Accessibility

Desktop, Laptop

Language

English

Subtitles

English

Level

Advanced

Effort

9 hours per week

Teaching Type

Self Paced

Course Description

Businesses are changing their approach to big data. Businesses can now analyse and collect data insights to improve their decision-making, thanks to a new level of data collection.

As companies seek to improve their business operations through data, they are looking for business analysts and data scientists.

This Big Data MicroMasters program will teach you tools and analytical techniques to use data to make decisions, collect and organize data at scale, as well as how data analysis can be used to support organizational change.

You’, will acquire both technical and computational skills that are highly sought after across a variety of industries. You’, will develop essential skills in programming for data science and computational thinking.

Course Overview

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

How to design algorithms

Understand fundamental programming concepts including data abstraction, storage and structures

Understand computational thinking which includes decomposition, pattern recognition and abstraction

Data-driven problem and algorithm design for big data

Interpretation of data representation and analysis

Understand key mathematical concepts, including dimension reduction and Bayesian models

How to use analytical tools such as R and Java

Course Content

Expand all sections

Module 1: Programming for Data Science

Module 2: Computational Thinking and Big Data

Module 3: Big Data Fundamentals

Module 4: Big Data Analytics

Course Instructors

Aneta Neumann

Postgraduate Researcher, School of Computer Science

Aneta is currently undertaking postgraduate research in the School of Computer Science at the University of Adelaide. Her main research interest is understanding the fundamental link between bio-inspired computation and digital art.

Katrina Falkner

Head - School of Computer Science

Katrina has a strong interest in Computer Science Education Research (CSER), mainly in the areas of collaborative and active pedagogy. She has a particular interest in the use of technology to suppor...

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â€‹Claudia Szabo

Senior Lecturer, School of Computer Science

Claudia's main research interests lie in the area of computer systems and computer science education. Her computer science education focus lies in the area of curriculum design and analysis using eme...

Nick Falkner

Associate Professor, School of Computer Science

Nick loves teaching and does most of his education research into the areas of motivation, time management and effective teaching delivery. He also looks at the role of social networks in forming stro...