Big Data Analysis: Map Reduce, Spark, BigTable/HBase, Distributed Data
Faculty Profiles
Pavel Klemenkov
Chief Data Scientist (Data Platform) at NVIDIA; Founder of the Moscow Spark Tech community; Co-author of “Big Data for Data Engineers” Coursera specialisation
Alexey Dral
Founder and CEO at BigData Team; Head of “Big Data for Data Engineers” Coursera specialisation
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
During this course, the students will master and sharpen their knowledge in basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce, Spark, NoSQL. The subject of particular interest during this course is efficient data warehousing using Hive, Spark SQL and Spark Dataframes.
Being supervised, they will study the intricacies of systems’ internals and their applications as well as learn the distributed file systems, the purpose of their existence, the ways of their application. The listeners will also practice using the MapReduce framework, a workhorse for many modern Big Data applications. The possibility to apply knowledge into practice in order to process texts and solve sample business cases is the part and parcel of this course. The participants will deal with the next-generation computational framework - Spark, from its basic concepts up to advanced applications made to squeeze maximum performance. Finally, they will build and deploy their own service which will utilise SQL or NoSQL databases on the big scale.
Learning highlights
- Explain the principles of work and usage of NoSQL databases compared to traditional RDBMS systems
- Identify practical problems which can be solved with machine learning
- Build, tune and apply linear models with Spark MLLib
- Construct their own Big Data Service
- Apply the acquired skills in finance, social networks, telecommunications and many other fields
Course outline
4 classes
Session 1
Working with distributed file systems (HDFS)
Session 2-3
Understanding and working with MapReduce
Session 4-5
SQL over BigData: Hive
Session 6-7
Spark: in-memory computational model
Prerequisites
This course is one of three in a wholistic series.
Students that have already taken MSL-111 and those with prior experience with HTML, CSS, and Javascript building simple web pages will be good candidates for this module.
Pavel has graduated from the Lomonosov Moscow State University in 2009, department of Computational Mathematics and Cybernetics. In 2013 he has finished his PhD program. Pavel started his professional career as a software engineer at one of the largest Russian telecom companies Beeline. Then he moved to Rambler&Co, which is the largest Internet media company in Russia. He developed machine learning algorithms for Rambler/News (second largest news aggregator in Russia).
Then he worked as the technical leader for Rambler/News and Rambler/Portal. Last 4 years Pavel worked as the Head of Machine Learning Department at Rambler&Co, supervising machine learning solutions for all kinds of business areas (computer vision, advertising, recommendations, credit scoring). Now he works as the Chief Data Scientist at NVIDIA supervising all machine learning tasks which use telemetry data collected from GPUs all over the world. Pavel is also the founder of the Moscow Spark community which unites several hundred professional users and developers of Apache Spark.
See full profileAlexey Dral is the Founder and Chief Executive Officer at BigData Team. His 10 year working experience for the top Russian and international companies, including Amazon AWS, Yandex, Rambler and qualification on large-scale problems, leading R&D teams, defining strategy for the whole departments build up a great mentor with an aspiration to offer insights to his students. He teaches around the globe, launches new onsite and online courses to reduce the gap between industry and academia, supervise Data Science and Data Engineering initiatives.
-10 years of IT experience (Amazon AWS, Yandex, Rambler);
See full profileApply for this course
Big Data Analysis: Map Reduce, Spark, BigTable/HBase, Distributed Data
by Pavel Klemenkov, Alexey Dral
Total hours
45 Hours
Dates
Jun 11 - Jun 29, 2018
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.