MLACW (now mLAC) is an institution of excellence located strategically in the vicinity of national institutes of repute, such as Indian Institute of Science, Institute of Wood Science & Technology, National Institute of Advanced Studies, Raman Research Institute and Central Power Research Institute.

Image

About

Department of Computer Science

VISION OF THE DEPARTMENT

To impart quality academic and research oriented undergraduate education

MISSION OF THE DEPARTMENT

  1. To cater to needs of students with diverse talent, aspirations and professional requirements
  2. To empower the students with the required skills to solve the complex   technological problems of modern society and to be employable
  3. To provide a framework for promoting collaborative and multidisciplinary activities
  4. To impart moral, ethical values and interpersonal skills to the students.
  5. To provide environment for students to acquire graduate attributes.

The Department of Computer Science at mLAC began its journey in the year 1987, with a pre-university (PUC) course. A B.Sc. degree in Computer Science was started in the year 1989. Mrs. Sudha Murty, Chairperson, Infosys Foundation, headed the Department since its inception till the year 1996. In 1996, Dr. Rama M. A. took over the sails and headed the Department till 2015. In 2000, a course in Computer Applications was the need of the hour and thus, the Bachelor of Computer Applications (BCA) degree was introduced. The Department of Computer Science is affiliated to Bangalore University and was headed by Prof. Chitra Ravi till 2015. In 2021, Ft.Lt. Harish H took charge as Head of the Department.
Both the B.Sc.- Physics, Mathematics, Computer Science (PMC) and BCA programmes received academic autonomy in the year 2016. The Department consists of accomplished faculty from various specializations of Computer Science. The Department strives to deliver quality education to students that seamlessly blends with research. On the research forefront, both the faculty and students are actively engaged in research work through various Department of Biotechnology (DBT) funded projects.


The Department has state-of-the-art infrastructure and computing equipment which is supported by high speed Ethernet and wireless networks. The Department also offers University Grants Commission (UGC) sponsored, job-oriented add-on courses at Certificate and Diploma levels.


The Department regularly organizes workshops, seminars, industrial visits, and alumni Interaction activities to enhance students' skills. The students are also encouraged to participate in extra-curricular & co-curricular activities alongside academics to groom holistic personalities.


The clear vision, dedication and commitment of the faculty members along with a robust academia-industry interface that ensures good career support have been contributing factors to the growth and success of the Department.

 

Syllabus

Title Year Download
Certificate course in Computer Networking and Simulation 30 Jun, 2016 Download
BCA (2016-18) 03 Jul, 2016 Download
BSc.PMCs (2016-2019) 01 Jun, 2016 Download
Network Defence Security 04 Aug, 2017 Download
Web Design 04 Aug, 2017 Download
ASP. net 09 Aug, 2019 Download
CCNA 06 Sep, 2018 Download
Server Management 09 Aug, 2018 Download
Artificial Intelligence 04 Sep, 2019 Download
Advanced Java 09 Aug, 2019 Download
BCA (2019-2022) 03 Jul, 2019 Download
Bsc PMCs (2019-2021) 03 Jul, 2019 Download

Course Outcome

 

BCA

SEMESTER I

CPG.T1-1:PROBLEM SOLVING TECHNIQUES USING C CO1.1: Introduction to software, programming concepts such as structured programming and modular programming, skill to develop logic for problems using algorithms and flowcharts and overview of C programming language.

CPG.T1-1: PROBLEM SOLVING TECHNIQUES USING C CO1.2: Managing input output operations, decision making structures, branching and looping structures with examples being implemented in C programming.

CPG.T1-1: PROBLEM SOLVING TECHNIQUES USING C CO1.3:  Ability to define data types and use them in simple data processing applications using the concept of arrays, strings and storage classes.

CPG.T1-1: PROBLEM SOLVING TECHNIQUES USING C CO1.4: Gain knowledge on various types of functions, recursive functions, their implementation using various examples, concept of pointers, dynamic memory allocation, ability to define function, analyzes, and interprets the concept of pointers, dynamic memory allocation, defining and using macros.

CPG.T1-1: PROBLEM SOLVING TECHNIQUES USING C CO1.5:  Ability to define structures and union and understand the differences, user defined data types and text and binary files and their implementation using suitable examples.

CRA.T1-1: COMPUTER ORGANIZATION AND ARCHITECTURE  CO2.1: Gain knowledge on basics of computer architecture and organization, logic gates and digital gates.

CRA.T1-1: COMPUTER ORGANIZATION AND ARCHITECTURE  CO2.2: Understand Boolean Algebra, De Morgan's Theorem, SOP and POS simplification and Karnaugh Map, and to design Combinational Circuit and Sequential Circuits.

CRA.T1-1: COMPUTER ORGANIZATION AND ARCHITECTURE  CO2.3: Gain knowledge on various computer instructions, processor structure and function and types of parallel processor systems.

CRA.T1-1: COMPUTER ORGANIZATION AND ARCHITECTURE  CO2.4: Understand the memory organization, memory systems, mapping process and external memory.

CRA.T1-1: COMPUTER ORGANIZATION AND ARCHITECTURE  CO2.5: Gain knowledge on Input / output organization, external devices and external Interconnection Standards.

MFC-1: MATHEMATICAL FOUNDATIONS FOR COMPUTER APPLICATIONS CO3.1: Gain knowledge on sets, set operations, relations, functions, mathematical logic and switching systems.

MFC-1: MATHEMATICAL FOUNDATIONS FOR COMPUTER APPLICATIONS CO3.2: Understand matrices and determinants, types of matrices, minors, cofactors, inverse of matrix, eigen values and eigen vectors.

MFC-1: MATHEMATICAL FOUNDATIONS FOR COMPUTER APPLICATIONS CO3.3: Understand permutations and combinations, application in problems, vectors- dot and cross product.

MFC-1: MATHEMATICAL FOUNDATIONS FOR COMPUTER APPLICATIONS CO3.4: Gain knowledge on Groups, Graph terminologies, types of graphs, operations on graphs, incidence matrix and adjacency matrix representation of graphs.

MFC-1: MATHEMATICAL FOUNDATIONS FOR COMPUTER APPLICATIONS CO3.5: Gain knowledge on Analytical Geometry in 2 dimensions and problems based on the concept of equation of straight line, distance of point from a line. CPG.P1-1: C PROGRAMMING LAB COP1.1: Ability to gain problem solving skills and implementation using C programming control structures such as decision making, looping, functions and pointers.

CPG.P1-1: C PROGRAMMING LAB COP1.2: Ability to gain problem solving and coding skills using C programming String manipulation, macros, command line arguments, structures and files.

CRA-P1-1: COMPUTER ARCHITECTURE AND ORGANIZATION LAB COP2.1: Study of logic gates and flip flops, implementation of shift registers.

CRA-P1-1: COMPUTER ARCHITECTURE AND ORGANIZATION LAB COP2.2: Design of combinational logic circuits, multiplexer, demultiplexer, parity generator and checker circuits.

 

SEMESTER II

DST.T2-2: DATA STRUCTURES CO4.1: Gain knowledge on Data organization, Data structures, design and analyze the time and space efficiency of the data structure, representation of linear arrays in memory, and operations on linear array with implementation in C programming language.

DST.T2-2: DATA STRUCTURES CO4.2: Design and analysis of various sorting techniques, comparison, tracing of algorithms with examples, searching techniques like linear search and binary search, their comparison and various string processing techniques and pattern matching algorithm.

DST.T2-2: DATA STRUCTURES CO4.3: Gain knowledge on linked list creation, operations on linked lists like insertion, deletion, types of linked lists -singly linked list, doubly linked list, circular linked list and their implementation using arrays and pointers and the concept of Garbage collection, implementation using C language.

DST.T2-2: DATA STRUCTURES CO4.4: Understanding stacks and queues, operations on stacks and queues, applications of stacks and queues Recursion, Towers of Hanoi problem, Polish notation, implementation of stacks and queues.

DST.T2-2: DATA STRUCTURES CO4.5: Ability to gain knowledge in practical applications of data structures like trees and graphs, their representation in memory, and operations like insertion and deletion, implementation using C language.

DMS.T2-2: DATA BASE MANAGEMENT SYSTEMS CO5.1: Understanding Database Management System, Database concepts, architecture, classification of DBMS.

DMS.T2-2: DATA BASE MANAGEMENT SYSTEMS CO5.2: Gain knowledge on Data modelling using ER model, data model, Record storage and primary file organization, Hashing techniques.

DMS.T2-2: DATA BASE MANAGEMENT SYSTEMS CO5.3: Relational Data Model and Relational Algebra, Examples of Relational Algebra queries, Functional Dependencies, Transitive Dependency and Normalization for Relational Database.

DMS.T2-2: DATA BASE MANAGEMENT SYSTEMS CO5.4: Relational Database Language, Data types, DDL and DML queries, Nested Queries, PL/SQL, Applications of various types of SQL queries and their implementation.

DMS.T2-2: DATA BASE MANAGEMENT SYSTEMS CO5.5: Understand Transaction Processing Concepts, Concurrency Control techniques, Distributed Databases and Client Server Architecture and ACID properties

NSM-2: NUMERICAL AND STATISTICAL METHODS CO6.1: Floating point representation of numbers, types of errors- Round-off errors, Truncation, Absolute, Relative errors; finding roots of algebraic and transcendental equations Bisection, Regula Falsi and Second method and their comparison.

NSM-2: NUMERICAL AND STATISTICAL METHODS CO6.2: Interpolation and systems of linear equations -Newton Gregory interpolation formula, Lagrange's interpolation formula; numerical solution of systems of linear equations- Gauss Elimination, Gauss Jordan, Jacobi methods, Gauss Seidel Iterative method.

NSM-2: NUMERICAL AND STATISTICAL METHODS CO6.3: Gain knowledge on fundamentals of statistics, correlation, regression and their applications.

NSM-2: NUMERICAL AND STATISTICAL METHODS CO6.4:  Gain knowledge on Probability and random variables, Bayes theorem, probability mass function and applications based on these concepts.

NSM-2: NUMERICAL AND STATISTICAL METHODS CO6.5: Joint probability, marginal probability distribution, conditional probability distribution, Theoretical distributions like Bernoulli, Binomial, Poisson and Normal.

DST.P2-2: DATA STRUCTURES LAB COP4.1: Implementation of searching techniques, sorting techniques, string manipulation using pointers, stacks, linear and circular queues, creation of binary search tree.

DST.P2-2: DATA STRUCTURES LAB COP4.2: Implementation of data structure operations on linked lists, applications of stack like recursion and Towers of Hanoi problem, evaluation of postfix expression.

DMS.P2-2: DBMS LAB COP5.1: Design of queries for creation of database, tables with primary key and foreign key constraints, data manipulation operations like insertion, deletion, modification, creation of views and displaying of records.

DMS.P2-2: DBMS LAB COP5.2: Creation of multiple tables in database, establishing relationship between them and designing complex queries, nested queries, Entity Relationship diagram for case studies of Bank Database and College Database.

           

SEMESTER III

JVA.T3-3: OBJECT ORIENTED PROGRAMMING USING JAVA CO7.1: Understanding the concepts of Object-oriented, event driven and concurrent programming paradigm using JAVA.

JVA.T3-3: OBJECT ORIENTED PROGRAMMING USING JAVA CO7.2: Understanding classes and objects, arrays, strings, vector, the concept of constructors, inheritance, real life objects can be implemented by creating classes as blueprint and introducing methods for actions.

JVA.T3-3: OBJECT ORIENTED PROGRAMMING USING JAVA CO7.3: Gain knowledge on Packages and Interfaces which provides code reusability and naming collision which is very useful in real time projects in companies and also multithreading programming and synchronization methods.

JVA.T3-3: OBJECT ORIENTED PROGRAMMING USING JAVA CO7.4: Handling of Exceptions mainly used to manage problems ranging from hard disk crash to simple programming errors and also creation of applets, understanding difference between applets and applications, Event handling mechanism, Abstract Windowing Toolkit AWT classes and controls.

JVA.T3-3: OBJECT ORIENTED PROGRAMMING USING JAVA CO7.5: Ability to handle files, input and output streams in Java

OSL.T3-3: OPERATING SYSTEM AND LINUX CO8.1: Gain knowledge on basic operating system concepts, ad processes relevant to operating system such as process creation, management and scheduling algorithms.

OSL.T3-3: OPERATING SYSTEM AND LINUX CO8.2: Gain knowledge on Process synchronization, process state transitions, Classical Problems of synchronization, Deadlock recovery, avoidance and prevention.

OSL.T3-3: OPERATING SYSTEM AND LINUX CO8.3: Understand the concepts of Memory management, page management, file management, disk management in operating systems.

OSL.T3-3: OPERATING SYSTEM AND LINUX CO8.4: Gain knowledge on Linux, Files and file organization, wild card, system permissions, file handling.

OSL.T3-3: OPERATING SYSTEM AND LINUX CO8.5: Gain programming skills using shell scripting in Linux.

DEA.T3-3: DESIGN AND ANALYSIS OF ALGORITHMS CO9.1: Gain knowledge on algorithms, Design and Analysis Framework, Asymptotic notations, Analysis of Non-recursive and Recursive algorithms and various algorithm design paradigms, solving problems using Brute force technique.

DEA.T3-3: DESIGN AND ANALYSIS OF ALGORITHMS CO9.2: Ability to derive and solve the time complexities of algorithms using divide and conquer, decrease and conquer, transform and conquer strategies.

DEA.T3-3: DESIGN AND ANALYSIS OF ALGORITHMS CO9.3: Ability to solve problems using graph algorithms and analyse using Greedy method, Dijkstra’s shortest path algorithm.

DEA.T3-3: DESIGN AND ANALYSIS OF ALGORITHMS CO9.4: Devise optimal solution for recursive problems using Dynamic programming paradigm.

DEA.T3-3: DESIGN AND ANALYSIS OF ALGORITHMS CO9.5: Solution for problems on Backtracking and Branch and Bound techniques, finding a feasible solution for decision problems, P and NP problems. JVA.P3-3: JAVA LAB COP7.1: Ability to gain programming skills by implementing the concepts of string operations, method overloading, method overriding, constructor overloading, multi-threading and file handling in Java.

JVA.P3-3: JAVA LAB COP7.2: Implementation of Exception handling, Applet programming, AWT concepts, Event handling and Animation in Java.

OSL-P3-3: OPERATING SYSTEM AND LINUX LAB COP8.1: Ability to write Linux shell script for simple problems, test UNIX file commands, creating of files, file types and permissions.

OSL-P3-3: OPERATING SYSTEM AND LINUX LAB COP8.2: Ability to write Linux shell script using control structures, file compression and decompression, usage of regular expressions -grep command, to execute command at scheduled time.

 

 

SEMESTER IV

ALP.T4-4: ICROPROCESSOR AND ASSEMBLY LANGUAGE CO10.1: Understand the architecture of 8085 microprocessor and memory and Input/Output Interfacing.

 ALP.T4-4: MICROPROCESSOR AND ASSEMBLY LANGUAGE CO10.2: Gain knowledge on instruction formats, classification of instructions, addressing modes and to write the basic assembly language programs.

 ALP.T4-4: MICROPROCESSOR AND ASSEMBLY LANGUAGE CO10.3: Apply 8085 programming techniques such as looping, counting, indexing, stacks and subroutines to various assembly language programs.

 ALP.T4-4: MICROPROCESSOR AND ASSEMBLY LANGUAGE CO10.4: Understand the memory and I/O mapping and interfacing along with vectored and non-vectored interrupts.

 ALP.T4-4: MICROPROCESSOR AND ASSEMBLY LANGUAGE CO10.5: Understand the interfacing of peripherals and its applications, such as 8279 programmable keyboard /display interface, 8255 PPI, 8259 PIC, DMA and 8257 DMA controller, RS232 interface.

WPG.T4-4: WEB PROGRAMMING CO11.1: Understand the basics of Internet, web, web pages, www, and Web Server, tools for designing web pages HTML, XHTML, identify elements and attributes in web page, Lists and Tables.

WPG.T4-4: WEB PROGRAMMING CO11.2: Usage of Forms, Frames in HTML, CSS style sheets and creation of web pages using XHTML and Cascading Style Sheets.

WPG.T4-4: WEB PROGRAMMING CO11.3: Ability to use Javascript for solving simple problems.

WPG.T4-4: WEB PROGRAMMING CO11.4: Understand Javascript execution environment, Document object model, Event handling and embedding objects in web page.

WPG.T4-4: WEB PROGRAMMING CO11.5: Build dynamic web pages using JavaScript (Client-side programming), XML document structure and web services.

SOE-4: SOFTWARE ENGINEERING CO12.1: Gain knowledge on software process models, professional responsibility, computer-based system engineering, requirements and specifications.

SOE-4: SOFTWARE ENGINEERING CO12.2: Understand software prototyping, user interface prototyping, and software design and domain specific architecture.

SOE-4: SOFTWARE ENGINEERING CO12.3: Gain knowledge on object oriented and function-oriented design, user interface design.

SOE-4: SOFTWARE ENGINEERING CO12.4: Gain knowledge on software reliability metrics, statistical testing, fault avoidance and tolerance, exception handling, defensive programming, software reusability.

SOE-4: SOFTWARE ENGINEERING CO12.5: Gain knowledge on software testing and its importance, test planning and strategies, project management, quality management, cost estimation and software maintenance. ALP.P4-4: ASSEMBLY LANGUAGE PROGRAMMING LAB COP10.1: Usage of simulator software to execute assembly language programs in 8085, for addition, subtraction, exchange, transfer of block of data, multiplication, sorting of numbers.

ALP.P4-4: ASSEMBLY LANGUAGE PROGRAMMING LAB COP10.2: Ability to write assembly language programs to find ones and twos complements, largest of numbers, counting number of 1s and 0s, division and generation of Fibonacci numbers.

WPG.P4-4: WEB PROGRAMMING LAB COP11.1: Creation of HTML form with various elements and writing JavaScript code for various operations, creating dynamic effects and including layers and basic animation and event handling.

WPG.P4-4: WEB PROGRAMMING LAB COP11.2: Ability to apply the knowledge gained in creating small websites using HTML, CSS, JavaScript and XML.

 

SEMESTER V

DCN-5: DATA COMMUNICATION AND NETWORKS CO13.1: Ability to understand Data communication concepts, Computer Networks, protocols and standard model of communication (OSI and TCP/IP).

DCN-5: DATA COMMUNICATION AND NETWORKS CO13.2: Ability to understand the process of data transmission, switching, multiplexing by taking telephone networks and cable TV as real time example.

DCN-5: DATA COMMUNICATION AND NETWORKS CO13.3: Ability to understand the concept of error detection and correction, framing, flow and error control along with IEEE standards and its types, reservation, polling, token passing, channelization.

DCN-5: DATA COMMUNICATION AND NETWORKS CO13.4: Understand the concept of wireless networks, connecting devices, SONET, IP Addressing, mapping and delivery, forwarding and routing concepts.

DCN-5: DATA COMMUNICATION AND NETWORKS CO13.5: Knowledge on transport layer, UDP, TCP and application layer protocols like Domain Name System; Telnet, E-maill, FTP, WWW and HTTP.

CAR -5: COMPUTER ARCHITECTURE CO14.1: Knowledge on computer organization and architecture, digital logic circuits, combinational and sequential circuits and integrated circuits.

CAR -5: COMPUTER ARCHITECTURE CO14.2: Gain knowledge on registers, shift registers, Decoders, Encoders, Multiplexers, Binary counters, and to understand the structure of RAM and ROM ICs.

CAR -5: COMPUTER ARCHITECTURE CO14.3: Gain knowledge on CPU organization, Bus structure, micro-operations, instruction formats, addressing modes, RISC and CISC computers.

CAR -5: COMPUTER ARCHITECTURE CO14.4: Understanding Input output organization, Direct Memory Access, modes of data transfer, Programmed I/O and Interrupt driven I/O, Memory Hierarchy, Associative memory, Cache memory, Virtual memory.

CAR -5: COMPUTER ARCHITECTURE CO14.5: Knowledge on parallel processing systems, multiprocessors, clusters, multi core, GPGPUs, Performance issues, Amdahl’s law, Moore’s law, Little’s law.

PPG.T5-5: PYTHON PROGRAMMING CO15.1: Understand Python programming basics and control structures.

PPG.T5-5: PYTHON PROGRAMMING CO15.2: Gain knowledge on use of Python functions, anonymous functions, recursive functions and modules for code reusability, command line arguments and to be able to write simple Python programs for solving problems.

PPG.T5-5: PYTHON PROGRAMMING CO15.3: Ability to use data structures in Python such as arrays, lists, tuples, dictionaries and sets.

PPG.T5-5: PYTHON PROGRAMMING CO15.4: Ability to develop programmes on files, Binary data interchange formats, Exception handling, defining and using regular expressions in Python.

PPG.T5-5: PYTHON PROGRAMMING CO15.5: Ability to develop small applications  on GUI, Data Visualization, Database connectivity in Python.

DWM.T5-5: DATA WAREHOUSING AND DATA MINING CO16.1: Knowledge on functionalities of Data Mining, Data Warehouse Architecture and Online Analytical Processing systems.

DWM.T5-5: DATA WAREHOUSING AND DATA MINING CO16.2: Knowledge on importance of Data pre-processing and its techniques and algorithms for Association Analysis.

DWM.T5-5: DATA WAREHOUSING AND DATA MINING CO16.3: Ability to implement various Classification algorithms, linear and non-linear prediction techniques.

DWM.T5-5: DATA WAREHOUSING AND DATA MINING CO16.4: Knowledge on various clustering techniques and its implementation and Outlier analysis.

DWM.T5-5: DATA WAREHOUSING AND DATA MINING CO16.5: Understanding mining complex types of data in various domains and various application areas of Data Mining.

PRJ-5: PROJECT CO22.1: Ability to do literature survey, select suitable problem, understand system requirements, and prepare the Software Requirement Specification document for minor project.

PRJ-5: PROJECT CO22.2: Ability to design the system form design, database design, report design.

PRJ-5: PROJECT CO22.3: Implementation of the system using latest trends in technologies.

PRJ-5: PROJECT CO22.4: Verification and validation of Software developed, using Software Testing methods.

PRJ-5: PROJECT CO22.5: Documentation of the whole process and generation of project report. PPG.P5-5: PYTHON PROGRAMMING LAB COP15.1: Gain programming skills in Python to solve simple problems using looping structures, decision structures, functions, modules strings, lists, tuples, dictionaries, sets.

PPG.P5-5: PYTHON PROGRAMMING LAB COP15.2: Implement concepts of objects, inheritance, exception handling, file handling, data visualization using Python programming.

DWM.P5-5: DATA WAREHOUSING AND DATA MINING LAB COP16.1: Implementation of Data mining operations such as Data cleaning, Data pre-processing, and association analysis.

DWM.P5-5: DATA WAREHOUSING AND DATA MINING LAB COP16.2: Creation of data sets and implementation of Data classification, prediction and clustering algorithms on various data sets.

 

 

            SEMESTER VI        

PRJ-6: PROJECT CO23.1: Ability to do literature survey, select suitable problem, understand system requirements, and prepare the Software Requirement Specification document for major project.

PRJ-6: PROJECT CO23.2: Ability to design the system form design, database design, report design.

PRJ-6: PROJECT CO23.3: Implementation of the system by coding using suitable software tools.

PRJ-6: PROJECT CO23.4: Verification and validation using Software Testing methods.

PRJ-6: PROJECT CO23.5: Documentation of the whole process and generation of project report.

SPG-6: SYSTEM PROGRAMMING CO18.1: Gain knowledge on various system software components and IBM 360/370 instruction set.

SPG-6: SYSTEM PROGRAMMING CO18.2: Ability to design assemblers and also gain knowledge about the databases involved, table processing processes, various techniques of searching and sorting.

SPG-6: SYSTEM PROGRAMMING CO18.3:  Usage of macro processor programs for language expansion and standalone programs to process any kind of text.

SPG-6: SYSTEM PROGRAMMING CO18.4:  Gain knowledge about various loader schemes, activities such as allocation, linking, relocation and loading, binders, overlays, data structures and algorithms.

SPG-6: SYSTEM PROGRAMMING CO18.5: Gain knowledge about compilers needed to implement a programming language, the different phases of compiler design, data structures, storage classes, and optimization techniques are learnt.

DAA-6: DESIGN AND ANALYSIS OF ALGORITHMS CO19.1: Gain knowledge on algorithms, Design and Analysis Framework, Asymptotic notations, Analysis of Non-recursive and Recursive algorithms and various algorithm design paradigms, solving problems using Brute force technique.

DAA-6: DESIGN AND ANALYSIS OF ALGORITHMS CO19.2: Ability to derive and solve the time complexities of algorithms using divide and conquer, decrease and conquer, transform and conquer strategies.

DAA-6: DESIGN AND ANALYSIS OF ALGORITHMS CO19.3: Ability to solve problems using graph algorithms and analyse using Greedy method, Dijkstra’s shortest path algorithm.

DAA-6: DESIGN AND ANALYSIS OF ALGORITHMS CO19.4: Devise optimal solution for recursive problems using Dynamic programming paradigm.

DAA-6: DESIGN AND ANALYSIS OF ALGORITHMS CO19.5: Solution for problems on Backtracking and Branch and Bound techniques, finding a feasible solution for decision problems, P and NP problems.

DTA.T6-6: DATA ANALYTICS CO20.1: Gain knowledge on types of data, types of analytics and the process of data analytics and introduction to R programming.

DTA.T6-6: DATA ANALYTICS CO20.2: Knowledge about Descriptive analytics, data collection methods, graphical data description, inferential statistics, measures of central tendency, probability distributions, Hypothesis testing and implementation using R programming.

DTA.T6-6: DATA ANALYTICS CO20.3: Gain knowledge on Predictive analytics, regression types, KNN, Analysis of Variance ANOVA and implementation of algorithms using R programming.

DTA.T6-6: DATA ANALYTICS CO20.4: Gain knowledge about various supervised and unsupervised machine learning algorithms and implementation using R using datasets.

DTA.T6-6: DATA ANALYTICS CO20.5: Understand the concepts of Big Data, Hadoop Ecosystem, Hadoop streaming, HDFS and Mapreduce. DTA.P6-6: DATA ANALYTICS LAB COP20.1: Implementation of the concepts of select, split, transform using R, hypothesis testing, data visualization, time series analysis, machine learning algorithms-Linear regression, logistic regression, Classification algorithm -Naïve Bayes classifier, decision tree and clustering algorithms-K means clustering.

DTA.P6-6: DATA ANALYTICS LAB COP20.2: Implementation of Big Data and Hadoop concepts such as file management tasks, execution of Mapreduce applications, matrix multiplication, Hadoop streaming.

Our Faculty

Dr. Chitra Ravi

Head of Department

Dr. Anita Patrot

Assistant Professor

Shruthi M G

Assistant Professor

Nethravathy K

Assistant Professor

Bharathi D S

Assistant Professor

Shruthi C Karigar

Assistant Professor

Mamatha M

Assistant Professor

Fg. Offr. Harish H

Associate Professor

Ms. Geetha P L

Assistant Professor

Shambbavi S

Assistant Professor

Thamizhselvi P

Assistant Professor

Pratibha M

Associate Professor

Apply Now Enquire