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This course is part of Big Data Specialization
Instructors: Ilkay Altintas
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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+.
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!
2 videos2 readings1 discussion prompt
Data -- it's been around (even digitally) for a while. What makes data "big" and where does this big data come from?
13 videos13 readings1 assignment2 discussion prompts
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.
7 videos9 readings1 assignment2 discussion prompts
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.
11 videos12 readings1 assignment2 discussion prompts
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.
4 videos4 readings1 assignment
Let's look at some details of Hadoop and MapReduce. Then we'll go "hands on" and actually perform a simple MapReduce task using a Docker container. Pay attention - as we'll guide you in "learning by doing" in diagramming a MapReduce task as a Peer Review.
11 videos8 readings2 assignments1 peer review1 discussion prompt
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
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Reviewed on Sep 14, 2019
It is a comprehensive introduction to big data which covers significant components with enough content that can be absorb at this stage. A very good kick-start and excited for the next course ahead.
Reviewed on Apr 22, 2018
A great introduction. Excellent lectures and practical exercises that reinforce the understand of the basic theory plus vital concepts to further comprehend and apply the topics in the real life.
Reviewed on Mar 30, 2020
One of the best course to start learning new cutting-edge technology and to get deeper insights into Big Data. Thanks to the great instructors for amazing explanations of each module and e-materials.
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