What experience level is required for AdelaideX: Big Data Fundamentals?

This course is aimed at the Intermediate level. Having some basic understanding of the topic will help you get the most out of the curriculum.

How long does it take to complete AdelaideX: Big Data Fundamentals?

The total duration of the course is approximately 10 weeks. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

Do I get a certificate after completing AdelaideX: Big Data Fundamentals?

Yes, a certificate of completion is included, which you can add to your professional profile or resume to showcase your newly acquired skills.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Computer Science and adjacent technical fields looking to upskill.

Computer Science

AdelaideX: Big Data Fundamentals

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

Intermediate FriendlyCertification IncludedSelf-Paced Learning

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₹16517

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🧠 Good for intermediate learners

⚠ May feel basic for advanced users

Learning Journey Context

Works well as a continuation after mastering Computer Science fundamentals. It bridges the gap toward advanced, production-level engineering.

Career Relevance

Relevant for: Frontend Developer, Full Stack Developer, Web Engineer.

Quick Facts

10 weeks

AdelaideX

Intermediate

Self-Paced Online

Online Course

edx

Catalan

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What You’ll Learn

Organizations now have access to massive amounts of data and it’s influencing the way they operate. They are realizing in order to be successful they must leverage their data to make effective business decisions.

In this course, part of the Big Data MicroMasters program, you will learn how big data is driving organisational change and the key challenges organizations face when trying to analyse massive data sets.

You will learn fundamental techniques, such as data mining and stream processing. You will also learn how to design and implement PageRank algorithms using MapReduce, a programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. You will learn how big data has improved web search and how online advertising systems work.

By the end of this course, you will have a better understanding of the various applications of big data methods in industry and research.

See how this course curriculum compares with alternatives

Outcomes

Knowledge and application of MapReduce.
Understanding the rate of occurrences of events in big data.
How to design algorithms for stream processing and counting of frequent elements in Big Data.
Understand and design PageRank algorithms.
Understand underlying random walk algorithms.

See side-by-side differences in learning outcomes