Classbaze

Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Introduction to 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 ...
4.6
4.6/5
(9,824 reviews)
260,755 students
Created by

8.9

Classbaze Grade®

N/A

Freshness

8.4

Popularity

8.9

Material

Introduction to Big Data
Platform: Coursera
Video: 4h 25m
Language: English

Best Data Analysis classes:

Classbaze Rating

Classbaze Grade®

8.9 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.4 / 10
We analyzed factors such as the rating (4.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

8.9 / 10
Video Score: 8.2 / 10
The course includes 4h 25m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 4 hours 49 minutes of 559 Data Analysis courses on Coursera.
Detail Score: 8.7 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.8 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

48 articles.
0 resource.
0 exercise.
7 tests or quizzes.

In this page

About the course

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 can you learn from this course?

What you need to start the course?

The course creator has not defined the requirements for this course.

Who is this course is made for?

The course creator hasn’t defined the level of this course.

Are there coupons or discounts for Introduction to Big Data ? What is the current price?

Access to most course materials is FREE in audit mode on Coursera. If you wish to earn a certificate and access graded assignments, you must purchase the certificate experience during or after your audit.

If the course does not offer the audit option, you can still take a free 7-day trial.
The average price is $8.1 of 559 Data Analysis courses. So this course is 100% cheaper than the average Data Analysis course on Coursera.

Will I be refunded if I'm not satisfied with the Introduction to Big Data course?

Coursera offers a 7-day free trial for subscribers.

Are there any financial aid for this course?

YES, you can get a scholarship or Financial Aid for Coursera courses. The first step is to fill out an application about your educational background, career goals, and financial circumstances. Learn more about financial aid on Coursera.

Who will teach this course? Can I trust Ilkay Altintas?

Ilkay Altintas has created 12 courses that got 1,403 reviews which are generally positive. Ilkay Altintas has taught 410,769 students and received a 4.68 average review out of 1,403 reviews. Depending on the information available, we think that Ilkay Altintas is an instructor that you can trust.
San Diego Supercomputer Center
University of California San Diego
Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence. Since joining SDSC in 2001, she has in the areas of computational data science and e-Sciences at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, observatory systems, conceptual data querying, and software modeling. She is a co-initiator of and an active contributor to the popular open-source Kepler Scientific Workflow System. Ilkay Altintas received her Ph.D. degree from the University of Amsterdam in the Netherlands.

8.9

Classbaze Grade®

N/A

Freshness

8.4

Popularity

8.9

Material

Platform: Coursera
Video: 4h 25m
Language: English

Classbaze recommendations for you