Hands On Training

Big Data Analytics: Opportunities, Challenges, and the Future

via

Future Learn

Course Features

Duration

2 weeks

Delivery Method

Online

Available on

Lifetime Access

Accessibility

Mobile, Desktop

Language

English

Subtitles

English

Level

Beginner

Effort

4 hours per week

Teaching Type

Self Paced

Course Description

Analytics with big data helps us understand the vast amount of information generated by our world. Analytics can be used to identify hidden patterns, predict trends and gauge customer opinions, among other things. This course was developed by Professor Bela Static and Griffith University's Big Data and Smart Analytics Lab. It teaches you how to analyze data from multiple sources and how big data can be used in different industries to solve problems and shape the future. The challenges and implications of big data analytics will be discussed, as well as how they can impact your daily life.

Course Overview

Alumni Network

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Describe how big data analytics can solve problems across disciplines

Evaluate data from different sources

Explain the key concepts of big data analytics

Identify implications of big data analytics

Target Students

It may be of particular use to social media users, or those interested in seeing how big data may affect their particular industry

This course would suit anyone interested in learning about the fast-growing field of big data, including those considering a career in the industry

Course Content

Expand all sections

Module 1: Introduction to big data and where it comes from

Module 2: Overview of the data analytics cycle

Module 3: Social media platforms and types of data

Module 4: Applications of big data across different industries

Course Instructors

Sebastian B

Instructor

I am a Senior Lecturer in the School of Information and Communication Technology at Griffith University, with a passion for online teaching and technical interests in data mining and AI