INTERNATIONAL INSTITUTE OF MANAGEMENT & ENGINEERING

MASTER OF PHILOSOPHY IN COMPUTER SCIENCE

INTERNATIONAL INSTITUTE OF MANAGEMENT & ENGINEERING
Online

Rs 90,000
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Important information

Typology MPhil
Methodology Online
Duration 1 Year
Start Different dates available
Online campus Yes
  • MPhil
  • Online
  • Duration:
    1 Year
  • Start:
    Different dates available
  • Online campus
Description

M. Phil. Computer Science is a program that aims at preparing students to be able to tackle technical issues prevailing in the competitive world of computer science and information technology. Students pursuing this course show ability in the critical evaluation of research techniques and methodologies.

The program focuses on a broad vision of philosophical approach in Computer Science and IT which covers various areas of specialization which students can chose according to their area of interest. The training provided help student increase their potential and increase their CTC. Deep understanding of the trends going on in the Computer science industry is another objective of the course.

Facilities (1)
Where and when
Starts Location
Different dates available
Online
Starts Different dates available
Location
Online

Frequent Asked Questions

· What are the objectives of this course?

Students who have keen interest in developing strong analytical and synthesizing skills with innovative and creative thinking must opt for this course as it can prove to be the right choice for them. Those who have an ability to anticipate the need for information and identify technical problems and troubleshoot them can opt for this course as well. An instinct for being a part of strong scientific and technical community, this course is a must. For students who are interested in advance learning and research in any field of computer application, M. Phil. Computer Science can prove to be beneficial.

· Who is it intended for?

POST GRADUATE STUDENTS CAN APPLY

· Requirements

ID PROOF RESIDENTIAL PROOF EDUCATIONAL DOCUMENTS PASS PORT SIZE PHOTO RESUME

· Qualification

PG IN RELEVENT SUBJECT

· What happens after requesting information?

REGISTRATION & ENROLLMENTS

Opinions

0.0
Not rated
Course rating
100%
Recommended
5.0
excellent
Centre rating

Reviews on other courses at this centre

DIPLOMA IN MECHANICAL ENGINEERING

A
Angelina Sen
5.0 01/07/2016
What I would highlight: Very convenient! Excellent! Could study in my time. Thanks to the team I am on a good job now! Best guidance & counselling provided. Very Honest & straight! Education is the best knowledge they provide. Guided me beyond my expectations. A special thanks to the Director. She motivated me to do the best course and not to look back but move ahead. A humble and a hearty thanks to Madam.
What could be improved: Nothing.
Would you recommend this course?: Yes

DIPLOMA IN MECHANICAL ENGINEERING

M
Mitchelle D.
5.0 01/01/2016
What I would highlight: Best for the working professionals. No time restrictions- I am on a good job now.
What could be improved: Nothing.
Would you recommend this course?: Yes

DIPLOMA IN MECHANICAL ENGINEERING

C
CHANDAN KOLI
5.0 01/08/2015
What I would highlight: Self-learning program as I am a working professional. Exams on demand .
What could be improved: Nothing.
Would you recommend this course?: Yes
Reviews gathered by Emagister & iAgora

What you'll learn on the course

Management
Programming
Artificial Intelligence
Computer Science
Technology
IT Management
Analysis
Science
Software Engineering
Testing

Teachers and trainers (1)

SNEHA SHARMA
SNEHA SHARMA
ENGINEERING JOBS

Course programme

(Bio Technology, Biochemistry, Botany, Chemistry, Commerce, Computer Science, Corporate Secretaryship, Education, Education, Electronics, Information Technology, Microbiology, Home Science, Hotel Management, Hotel Management, Library Science, Management, Physics, Population Studies, Psychology, Public Administration, Sociology, Tourism Management, Zoology) Unit - I Research – Definition – Importance and Meaning of research – Characteristics of research – Types of Research – Steps in research – Identification, Selection and formulation of research problem – Research questions – Research design – Formulation of HypoDissertation – Review of Literature. Unit – II Sampling techniques: Sampling theory – types of sampling – Steps in sampling – Sampling and Non-sampling error – Sample size – Advantages and limitations of sampling. Collection of Data : Primary Data – Meaning – Data Collection methods – Secondary data – Meaning – Relevances, limitations and cautions. Unit – III Statistics in Research: Measure of Central tendency – Dispersion – Skewness and Kurtosis in research. HypoDissertation – Fundamentals of HypoDissertation testing – Standard Error – Point and Interval estimates – Important Non-Parametric tests : Sign, Run, Kruskal – Wallis tests and Mann-Whitney test. Unit – IV Para metric tests: Testing of significance – mean, Proportion, Variance and Correlation – testing for Significance of difference between means, proportions, variances and correlation coefficient. Chi-square tests – ANOVA – One-way and Two-way Unit – V Research Report: Types of reports – contents – styles of reporting – Steps in drafting reports – Editing the final draft – Evaluating the final draft. Reference Books: 1. Statistical Methods S.P. Gupta 2. Research Methodology Methods and Techniques C.R. Kothari 3. Statistics (Theory and Practice) B.N. Gupta 4. Research Methodology Methods and Statistical Techniques Santosh Gupta ADVANCED COMPUTER TECHNIQUES MPCS 102 (Computer Science, Computer Application, Information Technology, Computer Technology and Software Engineering) Unit – I Theory of Programming: Languages Programming Language : Introduction, Characteristics, Uses –Programming Language Processor – Hierarchies of Computers – Data - Elementary data types – Structured data types – expression – statements – procedures – functions – data control and storage management – data abstraction – exception handling – data encapsulation – theoretical models. The above features in C, C++, JAVA Unit – II Software Engineering: Introduction to Software Engineering – Software Project Planning – Requirement analysis specification – Software Design- Implementation issues – Software Testing – Verification and Validation – Software maintenance and Reliability. Unit – III Compiler Design: Introduction – Lexical analysis – syntax analysis – types – storage organization – storage allocation – parameter passing – symbol table – language facilities for dynamic storage – allocation – dynamic storage allocation techniques – Intermediate code generation – code generation – code optimization. Unit – IV Artificial Intelligence and Expert Systems: Introduction : Problem Definition – Search Strategies – Characteristics – Game Playing - Knowledge representation – Expert System – Roles of Expert System – Knowledge acquisition, Meta knowledge – Heuristics knowledge – Interface : Backward and forward chaining – Fuzzy reasoning – Learning – Adaptive Learning – Types of Expert System : MYSIN, PIP, INTERNIST, DART, XOON, Expert Systems Shells. Unit – V Neural Networks: Introduction – Humans and computers – Structure of the Brain, Learning in Machine – differences – Pattern Recognition – The Basic Neutron – Perception – Limitation – Multilayer Perception – Organising Networks – Hopfield Networks – Associative Memory. Reference Books: 1.Data Structures and Algorithms by Alfred V. Aho, John E. Hoperoft and D. Ulman, Wesley Publishing Company, 1987. 2. Computer Algorithms by Ellis Horowitz and Sartaj Sahni, Galgotia Publications Pvt. Ltd., 1993. 3. Software Engineering, Concepts by Richard Fairley, Mc. Graw Hill, 1985. 4. Software Engineering : A Practioner’s Approach, Mc. Graw Hill, 1987. 5. Software Engineering by M.L. Shooma, Mc. Graw Hill, 1983. 6. Compiler Principles, techniques and tool by Alfred. V. Aho, Ravi Sethi and Jeffrey D. Ullman, Addison Wesley Publishing Company, 1986. 7. Compiler Construction by William M. Waite and Gerhard Boos, Springer Verlag, New York Inc., 1984. 8. Artificial Intelligence by Elaine Rich – Mc. Graw Hill 9. Principles of Artificial Intelligence by Nildon, N.J. Springer Verlag, 1981. 10. Principles and Case Study by Richard Folrsyth, Champman and Hall 1984. 11. Neural Computing: An Introduction by R. Beale and T. Jackson, Adam Hilger, 1990. 12. Adaptive Pattern Recognition and Neural Networks by Pao. Y.H., Addision Wesley, 1989.

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