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Introduction to Big Data complete course is currently being offered by UC San Diego through Coursera platform.
Learning Outcomes for Introduction to Big Data Course!
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.
Instructors for Introduction to Big Data Course!
– Ilkay Altintas
– Amarnath Gupta
Skills You Will Gain
- Big Data
- Apache Hadoop
- Mapreduce
- Cloudera
Also Check: How to Apply for Coursera Financial Aid
Foundations for Big Data
- Foundations stand the test of time.
- Foundations is all that is required to show a mastery of big data concepts.
- Foundations allow for the understanding of practical concepts in Hadoop.
- Foundations help you revisit calculus concepts required in the understanding of big data.
- Prevents network connection failure
- Prevents individual component failures
- Much faster than a traditional super computer
- Data Parallel Job Restart
- Utilize Map Reduction Methods
- Support Big Data Operations
- Enable Adding of More Racks
- Optimization of Specific Data Types
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