1. Core Subjects:
1) Database Management Systems
Learning fundamental concept modeling techniques, capture DB requirements, implement schema
from their conceptual design, physical Storage, Indexing, fundamental practices in DBMS to ensure
transaction concurrency and recovery from failure.
2) Advanced Algorithms:
The course had followingkeycomponentsTheoretical andmathematical foundationsof algorithms
major design strategies such as the greedy method, divide-and-conquer, dynamic programming, Graph
and network algorithms, Internet algorithms: web, peer-to-peer, social media, NP-completeness.
3) Artificial Intelligence:
The course helpedtolearnthe basicsof AI alongwith all its componentslike IntelligentAgents,A*
search, heuristic Functions, constraint satisfaction, game playing, propositional logic, first order logic,
uncertainty,DynamicBayeisanNetworksandsolvingproblemsusingaprogramminglanguage calledFRIL.
4) Operating Systems:
The course involved learning the function, design, and integration of the parts of an operating
system, evaluate different operating system algorithms, and apply the knowledge of multi-process
programming to efficiently utilize services provided by an operating system.
5) Computer Networks:
The course enabledstudentstounderstandthedesignandprinciplesof computernetworks,analyze
and evaluate network protocols, and apply the knowledge of network protocols to develop efficient
network applications.
6) Quality Control:
Examines the processes and tools used to ensure quality of an item, a system, a process, or an
engineering endeavor. The topics of total quality management, statistical process control, and quality
systems are explored. Also, the historical development and current trends in quality are examined.
7) Innovative Design and Thinking:
IDT will help innovators be more successful at what they do and will teach some of the basic
vernacularandtoolsnecessarytogenerate new ideasandquicklytransformthose conceptsintoaviable
pipeline of new products and services.
8) Information Data Analysis:
Thiscourse is designedtointroduce algorithmicandcomputational foundationsof the fieldof data
mining and analysis. Various types of data are examined for discovery of patterns embedded in them.
Studentsare introducedtothe mathematical foundations,algorithms,scalability,andcomplexityaspects
for variousdataminingtasks.Variousapplicationsof these algorithmsare alsopresented.Issuesrelating
toincreasinglylargesizeof datasetswillbe addressed.Allalgorithmsare presentedinthecontextof some
real-life applications.