Unit 1. Cloud Computing  

Data Intensive sciences and the data center model; Clouds with infrastructure, platform, and software as a service; Virtualization technologies and tools; Introduction to future. Grid (or Openstack) as an experimental tesbed; Parallel programming using MapReduce vs MPI; MapReduce and data parallel applications using Hadoop ;Iterative MapReduce and data mining algorithms using Twister (expectation maximization, clustering, multi-dimensional scaling, latent Dirichlet allocation, Bayes networks);MapReduce on multicore/graphics processing unit (CUDA);NoSQL databases (Google BigTable and Hadoop HBase)      and parallel query processing ; High level language (Hive and Pig) ; Amazon EC2 and Microsoft Azure and their applications 

Unit 2. Web programming (Practical course) 

Basics of Web networking: Client-Server communication, the HTTP protocol, DNS, setting up a Web server; Client-side programming with HTML, CSS and JavaScript, and an introduction to Ajax and JavaScript frameworks;  Server-side programming with Python: at first CGI, and later with Django. Topics that will becovered in more depth include form processing, session management, authentication andcreating CRUD applications with Django;  Server-side database management: setting up MySQL, basic querying and database design,Python interface for database access; Working in a *NIX environment.