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Big Data Analytics

Lewis Mitchell, Simon Tuke, and David Suter

Gain essential skills in today’s digital age to store, process and analyse data to inform business decisions.

In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Apache Spark and R.

Topics covered in this course include:

cloud-based big data analysis;
predictive analytics, including probabilistic and statistical models;
application of large-scale data analysis;
analysis of problem space and data needs.

By the end of this course, you will be able to approach large-scale data science problems with creativity and initiative.

What you'll learn

How to develop algorithms for the statistical analysis of big data;
Knowledge of big data applications;
How to use fundamental principles used in predictive analytics;
Evaluate and apply appropriate principles, techniques and theories to large-scale data science problems.

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Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Lewis Mitchell, Simon Tuke and David Suter, this course is ideal for students interested in data analytics or cloud-based big data analysis

Supports an understanding of probabilistic and statistical models, bridging theoretical knowledge with real-world applications

Teaches fundamental principles used in predictive analytics, providing learners with essential knowledge for data-driven decision-making

Provides hands-on experience with Apache Spark and R, industry-standard tools for big data analysis

Assumes no prior knowledge of big data, making it accessible to learners of all backgrounds

Can be part of a micro master's program, allowing learners to extend their knowledge

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Career center

Learners who complete Big Data Analytics will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is responsible for developing and implementing data-driven solutions to business problems. This course provides a strong foundation in the skills needed to be successful in this role, including data analysis techniques, machine learning, and cloud computing. The course also covers topics such as predictive analytics and large-scale data analysis, which are increasingly important in today's data-driven world.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer is responsible for developing and implementing machine learning models to solve business problems. This course provides a strong foundation in the skills needed to be successful in this role, including machine learning techniques, programming, and cloud computing. The course also covers topics such as predictive analytics and large-scale data analysis, which are increasingly important in today's data-driven world.

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Data Analyst

A Data Analyst is responsible for collecting, cleaning, and analyzing data in order to provide insights to businesses. This course provides a strong foundation in the skills needed to be successful in this role, including data analysis techniques, programming, and cloud computing. The course also covers topics such as predictive analytics and large-scale data analysis, which are increasingly important in today's data-driven world.

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Data Engineer

A Data Engineer is responsible for designing and building data pipelines to store and process data. This course provides a strong foundation in the skills needed to be successful in this role, including data engineering techniques, cloud computing, and programming. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop data-driven solutions to business problems.

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Quantitative Analyst

A Quantitative Analyst is responsible for using mathematical and statistical models to analyze financial data. This course provides a strong foundation in the skills needed to be successful in this role, including data analysis techniques, financial modeling, and programming. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop trading strategies and risk models.

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Business Analyst

A Business Analyst is responsible for analyzing business processes and systems to identify areas for improvement. This course provides a strong foundation in the skills needed to be successful in this role, including data analysis techniques, process mapping, and business modeling. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to improve business decisions.

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Statistician

A Statistician is responsible for collecting, analyzing, and interpreting data. This course provides a strong foundation in the skills needed to be successful in this role, including statistical techniques, programming, and data visualization. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop data-driven solutions to business problems.

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Data Architect

A Data Architect is responsible for designing and managing data architectures. This course provides a strong foundation in the skills needed to be successful in this role, including data modeling techniques, cloud computing, and programming. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop data-driven architectures.

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Software Engineer

A Software Engineer is responsible for designing, developing, and maintaining software applications. This course provides a strong foundation in the skills needed to be successful in this role, including programming, software design, and cloud computing. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop data-driven software applications.

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Database Administrator

A Database Administrator is responsible for managing and maintaining databases. This course provides a strong foundation in the skills needed to be successful in this role, including database management techniques, cloud computing, and programming. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to optimize database performance and security.

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Market Researcher

A Market Researcher is responsible for conducting research to understand market trends and customer behavior. This course provides a strong foundation in the skills needed to be successful in this role, including research methods, data analysis techniques, and programming. The course also covers topics such as predictive analytics and large-scale data analysis, which can be used to develop data-driven marketing strategies.

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Financial Analyst

A Financial Analyst is responsible for analyzing financial data to make investment decisions. This course may provide a helpful foundation in the skills needed to be successful in this role, including data analysis techniques, financial modeling, and programming.

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Operations Research Analyst

An Operations Research Analyst is responsible for using mathematical and statistical models to solve business problems. This course may provide a helpful foundation in the skills needed to be successful in this role, including data analysis techniques, mathematical modeling, and programming.

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Risk Analyst

A Risk Analyst is responsible for analyzing risk and developing risk management strategies. This course may provide a helpful foundation in the skills needed to be successful in this role, including data analysis techniques, risk modeling, and programming.

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Actuary

An Actuary is responsible for assessing and managing risk. This course may provide a helpful foundation in the skills needed to be successful in this role, including data analysis techniques, statistical modeling, and programming.

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Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Big Data Analytics.

Data Mining