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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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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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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Big Data Analytics with these activities:

Review 'Big Data Analytics' by Michael Minelli, Michelle Chambers, and Ambiga Dhiraj

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This book provides a comprehensive overview of big data analytics, including its concepts, techniques, and applications. Reviewing it will help you build a strong foundation for the course.

View Big Data, Big Analytics: Emerging Business... on Amazon

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Read the book and take notes
Complete the exercises and case studies in the book
Discuss the book with other students or a mentor

Refactor your notes

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This course includes concepts covered in probability, statistics, and data structures. Reviewing these materials will increase your understanding of the course materials.

Browse courses on Probability and Statistics

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Review your notes and lecture slides
Read the course syllabus and textbooks to identify what topics will be covered
Rewrite your notes in a way that better aligns with the course requirements

Organize your notes, assignments, and resources

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This will help you keep track of what you have learned and make it easier to review for exams or assignments. Create a system for organizing your materials and stick to it.

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Create a system for organizing your notes
Create a system for organizing your assignments
Create a system for organizing your resources

Six other activities

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Follow tutorials on big data processing and analysis

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This course covers big data processing and analysis using tools like Apache Spark and R. Following tutorials will help you gain practical experience in using these tools.

Browse courses on Apache Spark

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Find tutorials on big data processing and analysis
Follow the tutorials and complete the exercises
Apply what you have learned to your own projects

Practice coding challenges related to big data analysis

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This will help you improve your programming skills and apply your knowledge of data structures to real-world problems. You can find coding challenges on platforms like LeetCode or HackerRank.

Browse courses on Data Structures

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Find coding challenges related to big data analysis
Solve the coding challenges and review your solutions
Discuss your solutions with other students or a mentor

Practice with data exploration and data analysis tools

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This will help you gain hands-on experience in working with big data and applying your knowledge from the course. Choose a dataset that you are interested in and start exploring it.

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Choose a dataset that you are interested in
Explore the dataset using data exploration tools such as Pandas or R
Perform data analysis using techniques such as statistical analysis or machine learning

Attend workshops on big data analytics

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This will allow you to learn from experts in the field and gain insights into the latest trends and technologies. Look for workshops organized by universities, industry groups, or professional organizations.

Browse courses on Cloud-based Big Data Analysis

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Find workshops on big data analytics
Attend the workshops and take notes
Apply what you have learned to your own projects

Create a presentation on a big data analytics project

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This will help you synthesize your knowledge and present it in a clear and concise way. Choose a project that you are passionate about and that demonstrates your skills in big data analytics.

Browse courses on Cloud-based Big Data Analysis

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Choose a big data analytics project to work on
Collect and analyze the data
Create the presentation

Write a blog post about a big data analytics topic

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This will help you deepen your understanding of a topic and share your knowledge with others. Choose a topic that you are interested in and that you think would be valuable to others.

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Choose a big data analytics topic to write about
Research the topic and gather information
Write the blog post

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.

See salaries and explore the career path for Machine Learning Engineer

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.

See salaries and explore the career path for Data Analyst

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.

See salaries and explore the career path for Data Engineer

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.

See salaries and explore the career path for Quantitative Analyst

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.

See salaries and explore the career path for Business Analyst

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.

See salaries and explore the career path for Statistician

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.

See salaries and explore the career path for Data Architect

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Database Administrator

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.

See salaries and explore the career path for Market Researcher

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.

See salaries and explore the career path for Financial Analyst

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.

See salaries and explore the career path for Operations Research Analyst

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.

See salaries and explore the career path for Risk Analyst

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.

See salaries and explore the career path for Actuary

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

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Classic text on data mining, providing a comprehensive overview of the field. It valuable resource for students and professionals who want to learn more about data mining.

Big Data Analytics

What you'll learn

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