Big Data Essentials: HDFS, MapReduce and Spark RDD
Overview
Have you ever heard about such technologies as HDFS, MapReduce, Spark? Always wanted to learn these new tools but missed concise starting material? Don’t miss this course either!
In this 6-week course you will:
- learn some basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce and Spark;
- be guided both through systems internals and their applications;
- learn about distributed file systems, why they exist and what function they serve;
- grasp the MapReduce framework, a workhorse for many modern Big Data applications;
- apply the framework to process texts and solve sample business cases;
- learn about Spark, the next-generation computational framework;
- build a strong understanding of Spark basic concepts;
- develop skills to apply these tools to creating solutions in finance, social networks, telecommunications and many other fields.
Your learning experience will be as close to real life as possible with the chance to evaluate your practical assignments on a real cluster. No mocking, a friendly considerate atmosphere to make the process of your learning smooth and enjoyable.
Get ready to work with real datasets alongside with real masters!
Special thanks to:
- Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road.
- Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team.
- Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course.
- Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting.
In this 6-week course you will:
- learn some basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce and Spark;
- be guided both through systems internals and their applications;
- learn about distributed file systems, why they exist and what function they serve;
- grasp the MapReduce framework, a workhorse for many modern Big Data applications;
- apply the framework to process texts and solve sample business cases;
- learn about Spark, the next-generation computational framework;
- build a strong understanding of Spark basic concepts;
- develop skills to apply these tools to creating solutions in finance, social networks, telecommunications and many other fields.
Your learning experience will be as close to real life as possible with the chance to evaluate your practical assignments on a real cluster. No mocking, a friendly considerate atmosphere to make the process of your learning smooth and enjoyable.
Get ready to work with real datasets alongside with real masters!
Special thanks to:
- Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road.
- Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team.
- Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course.
- Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting.
