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

Data -- it's been around (even digitally) for a while. What makes data "big" and where does this big data come from?

Characteristics of Big Data and Dimensions of Scalability

You may have heard of the "Big Vs". We'll give examples and descriptions of the commonly discussed 5. But, we want to propose a 6th V and we'll ask you to practice writing Big Data questions targeting this V -- value.

Data Science: Getting Value out of Big Data

We love science and we love computing, don't get us wrong. But the reality is we care about Big Data because it can bring value to our companies, our lives, and the world. In this module we'll introduce a 5 step process for approaching data science problems.

Foundations for Big Data Systems and Programming

Big Data requires new programming frameworks and systems. For this course, we don't programming knowledge or experience -- but we do want to give you a grounding in some of the key concepts.

Systems: Getting Started with Hadoop

Let's look at some details of Hadoop and MapReduce. Then we'll go "hands on" and actually perform a simple MapReduce task in the Cloudera VM. Pay attention - as we'll guide you in "learning by doing" in diagramming a MapReduce task as a Peer Review.

Good to know

Know what's good

, what to watch for

, 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

Big data: a beginner's guide for decision makers

learners say this introductory course in Big Data provides a solid foundation for those with no prior knowledge. It covers concepts such as why Big Data is important, the 5 V's of Big Data, HDFS, Hadoop, and the MapReduce algorithm. The course also features a hands-on lab where you can practice using Hadoop. However, some reviewers note that the content is a bit outdated and that the quizzes can be challenging.

Students report that the quizzes can be challenging, but they also appreciate that the quizzes help them to retain the information.

"The quizzes in the first two weeks are not practical at all."

"Sometime the video duration takes to long but overall is good."

This course earns largely positive reviews from students, who find it engaging and informative.

"I loved this course which covers the concepts very well with adequate dose of hands on and quizzes."

"Very good introductory training,nevertheless is a little outdated and needs to keep up with changes on the respective technology domain"

The course includes a practical lab where students can apply their knowledge of Hadoop.

"I Loved the course and Expecting a much more detailed course with hadoop specially and spark as well ,both the instructors were very well thank you"

"It was an amazing experience taking this course and I must say I'll love to take more.Coursera is indeed a nice platform for online classes."

Some students mention that the course material is outdated and could use updates.

"You can easily get away with skipping the first two weeks of the course."

"The whole specialisation is a joke."

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

Show steps

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

Show steps

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

Show steps

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

Browse courses on Data Science

Show steps

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

Show steps

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

Show steps

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

Expand to see all activities and additional details

Show all eight activities

Complete Hadoop Tutorials

Show steps

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

Browse courses on Hadoop

Show steps

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

Show steps

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

Browse courses on Big Data Applications

Show steps

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

Show steps

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

Browse courses on MapReduce

Show steps

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

Show steps

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

Browse courses on Data Architecture

Show steps

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

Show steps

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

Browse courses on Open Source

Show steps

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

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

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

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

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

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

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

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

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 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 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