We will have 9 lectures, each is for 2 hours.
You should also do 18 hours for self-study. Overall, 36 hours should be spent for learning concepts. Further learning time will be spent in tutorials and the work in assignments.
Basic information about the course will be given:
In this lecture we will discuss what a big data platform is about. We
will study key motivations for us to learn topics of big data platforms.
The lecture will be done on 13.01.2020.
We study and discuss key architectural principles for designing big data platforms. The lecture will be on 20.01.2020
Cloud technologies are important for developing and operating big data
platforms. We will discuss the roles of cloud infrastructures for big
We examine service models and integration for big data platforms. The lecture will be on 27.01.2020
Big data storages, databases and services in big data platforms. The lecture will be on 03.02.2020
Big data ingestion techniques. The lecture will be on 10.02.2020
We will discuss about Hadoop and its key components for big data ecosystem. The lecture will be on 03.03.2020
MapReduce and Spark programming models for big data processing. The lecture will be on 10.03.2020
Stream processing for big data and its relation to big data platforms. The lecture will be on 24.03.2020
Workflow technologies and frameworks for big data. The lecture will be on 31.03.2020