Introduction to Big Data from Coursera

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

At the end of this course, you will be able to:

* Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors.

* Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting.

* Get value out of Big Data by using a 5-step process to structure your analysis.

* Identify what are and what are not big data problems and be able to recast big data problems as data science questions.

* Provide an explanation of the architectural components and programming models used for scalable big data analysis.

* Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model.

* Install and run a program using Hadoop!

This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments.

Hardware Requirements:

(A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size.

Software Requirements:

This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.

What's inside

Syllabus

Welcome

Welcome to the Big Data Specialization! We're excited for you to get to know us and we're looking forward to learning about you!

Big Data: Why and Where

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores foundational concepts of Big Data, providing a strong starting point for beginners

Studies Big Data's dimensions of scalability, enhancing understanding of its complexities

Develops critical skills for approaching data science problems using a structured methodology

Provides valuable insights into the core components of Hadoop stack, empowering learners with essential knowledge for working with Big Data

Offers hands-on experience with Hadoop, enabling learners to apply their understanding practically

Reviews summary

Intro to big data concepts & hadoop

According to learners, this course provides a solid introduction to the world of big data for absolute beginners. It covers the core concepts like the V's and introduces the Hadoop ecosystem, including HDFS and MapReduce. Many students found the conceptual explanations clear and appreciated that no prior programming experience was required. However, a recurring point of concern for some was the hands-on component involving setting up and using the required virtual machine, which proved challenging or frustrating for some. There were also mentions that the software versions used felt somewhat outdated compared to current industry standards. Overall, it's seen as a valuable first step for understanding what big data is and its potential applications, particularly relevant for those interested in business or career implications, although the technical setup can be a significant hurdle.

Provides valuable context for business/career.

"Helped me understand how big data can be useful in a business context."

"Relevant for getting a high-level understanding needed in many roles."

"Gave me the vocabulary to discuss big data with colleagues and managers."

Covers the basics of Hadoop and its components.

"The course gives a necessary intro to Hadoop, HDFS, and MapReduce."

"I appreciated learning about the core Hadoop stack components."

"It provides a valuable first look at how these distributed systems work."

"Learned the fundamental architecture of the Hadoop framework."

Suitable for those with no prior data experience.

"As someone completely new to data science, this course was accessible."

"No prior programming was really needed, which was great and true to the description."

"It’s a perfect starting point if you know nothing about big data concepts."

"Great first step into a complex field without being overwhelming."

Provides a solid introduction to big data concepts.

"I gained a good understanding of the core big data concepts like the V's and the landscape."

"The initial modules did a great job explaining why big data is important."

"It helped me grasp the foundational ideas without getting too technical initially."

"The explanations of the different 'V's of big data were particularly helpful."

Software/tools used may be older than current standards.

"The version of Hadoop used in the VM felt a bit outdated compared to what's used now."

"I found it challenging to find current resources online for the older software versions used."

"Wish the course used more current versions of the big data tools."

"While foundational, the specific tech stack felt slightly behind current industry trends."

Includes practical exercises using a virtual machine.

"Setting up and getting the VM to work was the hardest part of the course."

"I struggled a lot with the technical requirements and VM installation steps."

"The hands-on MapReduce task in the VM was a good idea but execution was tricky."

"Needed significant troubleshooting help with the virtual machine setup."

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 Introduction to Big Data with these activities:

Read "Big Data: A Revolution That Will Transform How We Live, Work, and Think" by Viktor Mayer-Schönberger and Kenneth Cukier

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Gain valuable insights into the history and potential of big data to enhance your understanding of the course material.

View Reinventing Capitalism in the Age of Big Data on Amazon

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Read the book thoroughly, taking notes on key concepts and examples
Identify the main themes and arguments presented by the authors
Summarize the book's key points in your own words

Review Foundations of Data Science

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Solidify your foundational data science concepts before class starts to set yourself up for successful learning.

Browse courses on Data Science

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Review probability theory concepts (e.g., Bayes' theorem, conditional probability, random variables)
Review statistical concepts (e.g., mean, variance, standard deviation, hypothesis testing)
Practice applying statistics to real-world scenarios

Organize and Review Course Materials

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Enhance your learning by organizing and reviewing course materials regularly to improve retention and understanding.

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Create a system for organizing lecture notes, readings, and assignments
Review materials regularly, summarizing key concepts and identifying areas for further study
Seek clarification on any unclear concepts with the instructor or classmates

Five other activities

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Complete Hadoop Tutorials

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Develop practical skills in using Hadoop to enhance your understanding of big data systems.

Browse courses on Hadoop

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Find tutorials on Hadoop concepts and installation
Follow the tutorials step-by-step, practicing the concepts
Complete exercises or projects to test your understanding

Participate in a Peer Discussion on Big Data Applications

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Connect with classmates and share insights to broaden your understanding of big data applications in different industries.

Browse courses on Big Data Applications

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Join or create a peer discussion group
Prepare by researching case studies or industry trends related to big data
Engage in discussions, sharing your perspectives and learning from others

Solve Big Data Problems Using MapReduce Simulations

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Strengthen your understanding of MapReduce and develop problem-solving skills by practicing simulations.

Browse courses on MapReduce

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Find online simulators or exercises for MapReduce
Practice solving data processing problems using MapReduce
Review your solutions and identify areas for improvement

Design a Scalable Data Architecture for a Real-World Problem

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Apply your knowledge of big data systems to design scalable solutions for real-world data challenges.

Browse courses on Data Architecture

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Identify a real-world problem that involves big data
Design a scalable data architecture to address the problem using Hadoop or similar technologies
Present your design, including its components, data flow, and scalability considerations

Contribute to the Apache Hadoop Project

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Deepen your understanding of Hadoop and contribute to its development by participating in the open-source community.

Browse courses on Open Source

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Review the Hadoop documentation and codebase
Identify a bug or feature enhancement to work on
Submit a pull request with your proposed changes

Career center

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

Data Scientist

A Data Scientist gathers, organizes, and analyzes big data, often using Hadoop, to create insights that help businesses make better decisions. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Scientists who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Scientist

Big Data Engineer

The Big Data Engineer designs, builds, and maintains big data systems. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Big Data Engineers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Big Data Engineer

Data Analyst

A Data Analyst collects, processes, and analyzes data to help businesses make informed decisions. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Analysts who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Analyst

Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Software Engineers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Software Engineer

Database Administrator

A Database Administrator manages and maintains databases. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Database Administrators who want to learn more about big data and Hadoop.

See salaries and explore the career path for Database Administrator

Business Analyst

A Business Analyst helps businesses understand and solve problems by analyzing data. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Business Analysts who want to learn more about big data and Hadoop.

See salaries and explore the career path for Business Analyst

Data Architect

A Data Architect designs and builds data systems. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Architects who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Architect

Data Engineer

A Data Engineer builds and maintains data pipelines. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Engineers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer designs and builds machine learning models. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Machine Learning Engineers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Machine Learning Engineer

Data Administrator

A Data Administrator manages and maintains data. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Administrators who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Administrator

Data Manager

A Data Manager manages data assets. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Managers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Manager

Data Visualization Engineer

A Data Visualization Engineer designs and builds data visualizations. This course provides an introduction to big data and the Hadoop ecosystem. It offers hands-on exercises that will help you get started with Hadoop and gain a foundation in big data analysis. This course may be useful for aspiring Data Visualization Engineers who want to learn more about big data and Hadoop.

See salaries and explore the career path for Data Visualization Engineer