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Create a blog

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17160SEC26 Allied – IV – Management Information Systems

17160SEC26 Allied – IV – Management Information Systems
Department of BBA
17160SEC26 Allied – IV – Management Information Systems
UNIT-I
System analysis and design- An overview- System study- System design- development and
implementation.
UNIT-II:
Management information System- An overview- concept- evolution and element of MISdefinition-
characteristics and basic requirement of MIS- structure- computerized MISpre-
requisites of an effective MIS.
UNIT-III
Computers and its effect on MIS- Limitations- MIS and DSS- MIS and information
resource management- executive information artificial intelligence and expert system- MIS
in Indian organizations- recent developments in information technology.
UNIT-IV
Computers and communication- An overview- the information technology- concept of global
village- communication channels- communication networks- local area networks- wide area
networks- video conferencing.
UNIT-V
Client/ server computing communication servers- digital networks- ERP systems- interorganizational
information systems- value added networks- networking E-commerce and
internet- application of internet and website management


Click here for full Notes as  pdf 

Data structure and Algorithm

NOTE: Before going deep into data structure, you should have a good knowledge of programming either in C or in C++ or Java or Python etc

A data structure is a particular way of organizing data in a computer so that it can be used effectively. For example, we can store a list of items having the same data-type using the array data structure.
Notes
Data Structure Unit I 
Data Structure Unit - II
Data Structure Unit III 
Data Structure Unit - IV
Data Structure Unit - V

In theoretical computer science and mathematics, the theory of computation is the branch that deals with how efficiently problems can be solved on a model of computation, using an algorithm. The field is divided into three major branches: automata theory and languages, computability theory, and computational complexity theory, which are linked by the question: "What are the fundamental capabilities and limitations of computers?"

IT6006 Data Analytics syllabus

IT6006 Data Analytics

Introduction to Big Data Platform – Challenges of conventional systems - Web data – Evolution of Analytic scalability

, analytic processes and tools, Analysis vs reporting - Modern data analytic tools, Stastical concepts: Sampling distributions, resampling, statistical inference, prediction error.

UNIT II DATA ANALYSIS
Regression modeling, Multivariate analysis, Bayesian modeling, inference and Bayesian networks, Support vector and kernel methods, Analysis of time series: linear systems analysis, nonlinear dynamics - Rule induction - Neural networks: learning and generalization, competitive learning, principal component analysis and neural networks; Fuzzy logic: extracting fuzzy models from data, fuzzy decision trees, Stochastic search methods.

UNIT III MINING DATA STREAMS
Introduction to Streams Concepts – Stream data model and architecture - Stream Computing, Sampling data in a stream – Filtering streams – Counting distinct elements in a stream – Estimating moments – Counting oneness in a window – Decaying window - Realtime Analytics Platform(RTAP) applications - case studies - real time sentiment analysis, stock market predictions.

UNIT IV FREQUENT ITEMSETS AND CLUSTERING
Mining Frequent itemsets - Market based model – Apriori Algorithm – Handling large data sets in Main memory – Limited Pass algorithm – Counting frequent itemsets in a stream – Clustering Techniques – Hierarchical – K- Means – Clustering high dimensional data – CLIQUE and PROCLUS – Frequent pattern based clustering methods – Clustering in non-euclidean space – Clustering for streams and Parallelism.

UNIT V FRAMEWORKS AND VISUALIZATION
MapReduce – Hadoop, Hive, MapR – Sharding – NoSQL Databases - S3 - Hadoop Distributed file systems – Visualizations - Visual data analysis techniques, interaction techniques; Systems and applications:

CS6801 Multi – Core Architectures and Programming

CS6801 Multi – Core Architectures and Programming

CS6801 Syllabus Multi Core Architectures and Programming

CS6801 Syllabus Multi Core Architectures and Programming Regulation 2013 Anna University free download. Multi Core Architectures and Programming CS6801 Syllabus pdf free download.

UNIT I MULTI-CORE PROCESSORS 9 CS6801 Syllabus MCAP Multi Core Architectures and Programming

Single core to Multi-core architectures – SIMD and MIMD systems – Interconnection networks – Symmetric and Distributed Shared Memory Architectures – Cache coherence – Performance Issues – Parallel program design.

UNIT II PARALLEL PROGRAM CHALLENGES 9 CS6801 Syllabus MCAP Multi Core Architectures and Programming

Performance – Scalability – Synchronization and data sharing – Data races – Synchronization primitives (mutexes, locks, semaphores, barriers) – deadlocks and livelocks – communication between threads (condition variables, signals, message queues and pipes).

UNIT III SHARED MEMORY PROGRAMMING WITH OpenMP 9 CS6801 Syllabus Multi Core Architectures and Programming

OpenMP Execution Model – Memory Model – OpenMP Directives – Work-sharing Constructs – Library functions – Handling Data and Functional Parallelism – Handling Loops – Performance Considerations.

UNIT IV DISTRIBUTED MEMORY PROGRAMMING WITH MPI 9 CS6801 Syllabus Multi Core Architectures and Programming

MPI program execution – MPI constructs – libraries – MPI send and receive – Point-to-point and Collective communication – MPI derived datatypes – Performance evaluation

UNIT V PARALLEL PROGRAM DEVELOPMENT 9 CS6801 Syllabus Multi Core Architectures and Programming

Case studies – n-Body solvers – Tree Search – OpenMP and MPI implementations and comparison.

IT6006 Data Analytics Notes

IT6006 Data Analytics Notes