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Introduction to Big Data

Big Data,

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+.

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Rating 4.3 based on 922 ratings
Length 4 weeks
Effort 3 weeks of study, 5-6 hours/week
Starts Oct 12 (last week)
Cost $59
From University of California San Diego via Coursera
Instructors Ilkay Altintas, Amarnath Gupta
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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What people are saying

about big data

I learned a lot about Big Data.

I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)I did this specialization to get new knowledge about Big Data and better understand the technology and your practical applications.

I love how this course was organised, I had an idea about big data but I never had a whole over view about the bigger picture, I feel I am ready for more specialisation and read to take an Entry level interview for a BigData company.

But level is "for beginners", so I do not complain :) its really good for beginner Good for beginners This course makes understand the foundation about Big Data.

I would like to recommend to each people who dont know anything about big data This was a very good course.

I would recommend it if some one wants to start about Big data from base 0.

Its a great session very useful for my career IT WAS A GREAT EXPERIENCE...THANKS A TON Great fundational course about Big Data This course is an excellent introduction to Hadoop system and Big Data concepts.

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well structured

The lectures are well structured and the quizzes are useful to detemine whether one has understood everything.

Very well structured well explained landscape of data science too easy I was looking for this type of course of BigData.

The course is very well structured.

Great course & well structured, learnt a lot !

The course is well structured with relevant theories & definitions.

First of all i would like to take this opportunity to thanks the instructors the course is well structured and explained the foundations with real world problems with easy to understand the concepts.

I think the course is well structured, very knowledge intensive, but well balanced.

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looking forward

I'm eagerly looking forward to the rest of the courses in the specialisation.

Looking forward to more in the Specialization!

and not in concepts It was a very nice introductory course, and I'm looking forward to the future modules!

Looking forward for the upcoming courses.

I think this course was a great introduction the data science.. but needs some updating in terms of instantiation of the Cloudera image.. Docker was a much cleaner way for me to get up and running with the image.Also this course was mostly about the methods of Data Science, not necessarily about big data.. but a great foundation has been laid and still looking forward to more coding with hadoop in future courses.

This being my course from coursera I'm looking forward to do more course here.

Looking forward to the next course.

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well organized

Very well organized and professionally done.

I will take other courses from UC San Loved every lecture in this course as the content was presented clearly in a very well organized manner.

It help to re visit the point we missed during class It was very comprehensive and well organized.

Excellent course to get an introduction and hands on on Big Data excellent course for beginners well organized , so much interesting Great course material for an introduction.

Very well organized, it reaches such a degree of detail that all the doubts that appeared were clearly answered Contragulations great I found this course mostly vague and the videos highly redundant and unorganized into a useful building of knowledge.

The materials are very well organized and apt for the title.

Awesome course, the content is well organized and it gives you all you need to know.

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easy to follow

The hands-on are very easy to follow.

Excellent course material, simple, lucid and easy to follow structure, contextual examples - all this is worth making the Intro to B Great big data introduction course .

It was very easy to follow.

It was very detailed and easy to follow.

Simple introduction, easy to follow.

Content is generally easy to follow.

It is very easy to follow the course.

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real life examples

I loved this courses real life examples of the materials being discussed.

Very Good introduction to Big Data Concepts using real life examples and problems Best course to get started with Big data.

Very understandable content and very well explained - concepts of Big Data tied to real life examples were excellent.

The real life examples were good to understand and correlate with topics.

This is the very good session where the trainers have been explain each and every aspect of BigData with real time and real life examples.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Volunteer Big Data Engineer $48k

Data Scientist - Big Data $68k

Big Data and AWS Data Lake $73k

Big Data Developer (Streaming Data) $77k

Big data developer with AWS $78k

Research Scientist Big Data $94k

Big Data Developer Consultant $98k

Big Data Engineer 6 $107k

Big data and ETL specialist $121k

Big Data Specialist $149k

Principal Big Data Architect $180k

Senior Big Data Sales $181k

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Rating 4.3 based on 922 ratings
Length 4 weeks
Effort 3 weeks of study, 5-6 hours/week
Starts Oct 12 (last week)
Cost $59
From University of California San Diego via Coursera
Instructors Ilkay Altintas, Amarnath Gupta
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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