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.
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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.
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.
What's inside
Four courses
Programming for Data Science
(90 hours)
Programming for Data Science
(90 hours)
Computational Thinking and Big Data
(90 hours)
Computational Thinking and Big Data
(90 hours)
Big Data Fundamentals
(90 hours)
Big Data Fundamentals
(90 hours)
Big Data Capstone Project
(27 hours)
Big Data Capstone Project
(27 hours)Learning objectives
- 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
- 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
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