Coursera – Big Data Specialization (UC San Diego)

Coursera – Big Data Specialization (UC San Diego)
English | Tutorial | Size: 36.37 GB

Unlock Value in Massive Datasets. Learn fundamental big data methods in six straightforward courses.

Specialization – 6 course series

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.

Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.

1. Introduction to Big Data
2. Big Data Modeling and Management Systems
3. Big Data Integration and Processing
4. Machine Learning With Big Data
5. Graph Analytics for Big Data
6. Big Data – Capstone Project

Skills you will gain

– Big Data
– Neo4j
– Mongodb
– Apache Spark


Amarnath Gupta received his Ph.D. in Computer Science from Jadavpur University in India. He is currently a full Research Scientist at the San Diego Supercomputer Center of UC San Diego, and directs the Advanced Query Processing Lab. His primary areas of research include semantic information integration, large-scale graph databases, ontology management, event data management and query processing techniques. Before joining UC San Diego, he was the Chief Scientist at Virage, Inc., a startup company in multimedia information systems. Dr. Gupta has authored over 100 papers and a book on Event Modeling, holds 13 patents and is a recipient of the 2011 ACM Distinguished Scientist award.

Mai H. Nguyen is the Lead for Data Analytics at the San Diego Supercomputer Center (SDSC) of the University of California, San Diego (UCSD). Her research centers on applying machine learning techniques to various scientific problems and combining machine learning methods with distributed computing to analyze large-scale data. Prior to joining SDSC, she worked in industry on applications in machine learning, data mining, business intelligence, and data warehousing. She has also been teaching in these areas since 2009. Mai received her M.S. and Ph.D. degrees in Computer Science from UCSD, with focus on machine learning.

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.

Offered by University of California San Diego

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