SlideShare uma empresa Scribd logo
1 de 18
Course Title: Introduction to Information Technology
Course no: CSC-101 Full Marks: 87+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Fundamental concept of Information technology. Computer
systems, Computer software, DBMS, and application of computer
science.
Goal: This course introduces fundamental concepts of Information Technology and
computer science.
Course Contents:
Unit 1. Introduction to Computer Systems 10 Hrs.
Introduction to computers, Classification of digital computer systems, Anatomy of a
digital Computer, Computer Architecture, Memory system, Memory Units, Auxiliary
Storage devices, Inputs devices, Output Devices.
Unit 2. Computer Software and Software Development 6 Hrs.
Introduction to Computer Software, Operating Systems, Programming Languages,
General Software Features and Trends.
Unit 3. Database Management Systems 6 Hrs.
Data processing, Introduction to Database Management systems, Database design
Unit 4. Telecommunications 8 Hrs.
Introduction to Telecommunications, Computer Networks, Communication Systems,
Distributed systems
Unit 5. Internet and New Technologies in Information Technology 10 Hrs.
Internet, Multimedia tools and system, Intranets, Electronic Commerce, Hypermedia,
Data Warehouses and Data Marts, Data Mining, Geographical Information System
Unit 6. Applications of Information Technology 5 Hrs.
Computers in Business and Industry, Computers in education, training, Computers in
Entertainment, science, medicine and Engineering
Laboratory works: The main objective is familiarizing students with operating system
and desktop applications using current version of windows.
Text / Reference books: Alexis Leon, Mathews Leon, Fundamentals of
Information Technology, Leon TechWorld
Course Title: Fundamentals of Computer Programming
Course no: CSC-102 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: This course contains the concepts of programming methodology
using C.
Goal: This course is designed to familiarize students to the techniques of programming in C.
Course Contents:
Unit 1. Problem Solving with Computer 2 Hrs.
Problem analysis, Algorithms and Flowchart, Coding, Compilation and Execution,
History of C, Structure of C program, Debugging, Testing and Documentation
Unit 2. Elements of C 4 Hrs.
C Tokens, Escape sequence, Delimiters, Variables, Data types, Constants/ Literals,
Expressions, Statements and Comments
Unit 3. Input and Output 2 Hrs.
Conversion specification, I/O operation, Formatted I/O
Unit 4. Operators and Expression 4 Hrs.
Arithmetic operator, Relational operator, Logical or Boolean operator, Assignment,
Operator, Ternary operator, Bitwise operator, Increment or Decrement operator,
Comma operator.
Unit 5. Control Statement 4 Hrs.
Branching, Looping, Conditional Statement, Exit function, Difference between break
and exit
Unit 6. Arrays 6 Hrs.
Introduction, Declaration of array, Initialization of array, Sorting, Multidimensional
array
Unit 7. Functions 5 Hrs.
Library Functions, User defined functions, Recursion, Function declaration, Local
and global variables, Use of array in function, Passing by Value, Passing by Address
Unit 8. Pointers 6 Hrs.
Introduction, The & and * operator, Declaration of pointer, Pointer to pointer, Pointer
arithmetic, Array and Pointer, Pointer and array, Pointer with multidimensional array,
Pointer and strings, Array of pointer with string, Dynamic memory allocation
Unit 9. Structure and Union 5 Hrs.
Introduction, Array of structure, Passing structure to function, Passing array of
structure to function, Structure within structure ( Nested Structure), Union, Pointer to
structure
Unit 10. Files and file handling in C 4 Hrs.
Concept of file, Opening and closing of file, Modes, Input/ output function, Random
access in file, Printing a file
Unit 11. Introduction to Graphics 3 Hrs.
Modes, Initialization, Graphics Function
Laboratory works: This course requires a lot of programming practices. Each topic
must be followed by a practical session. Some practical
sessions include programming to:
• Create, compile and run simple C programs, handle different data types available
in C, perform arithmetic operations in C, perform formatted input and out put
operations, perform character input and output operations.
• Perform logical operations, create decision making programs, create loops to
repeat task, sue different looping method.
• Create user-defined factions, create recursive functions, work with automatic,
global and static variables, create manipulate arrays and matrices (single and
multi-dimensional), work with pointes, dynamically allocate de-allocate storage
space during runtime, manipulate strings (character arrays) using various string
handling functions.
• create and use structures an files to keep record of students, employees etc
References:
• Deitel, C.: How to Program, 2/e (With CD), Pearson Education.
• Al Kelley, Ira Pohl: "A Book on C", Pearson Education.
• Brian W. Keringhan & Dennis M. Ritchie: "The C programming Language", PHI
• Bryons S. Gotterfried: "Programming with C," TMH
• Stephen G. Kochan: "Programming in C", CBS publishers & distributors.
• Yashavant Kanetkar: "Let us C", BPB Publications
Course Title: Probability and Statistics
Course no: STA-103 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Concept of descriptive statistics, probability, probability
distributions, inferential statistics and their applications.
Goal: This course enhances the ability of students in computing and understanding
summary statistics; understanding the concept of probability and probability
distributions with their applications in statistics. Finally, students will develop
their ability of using inferential statistics in decision-making processes.
Course Contents:
Unit 1. Introduction 2 Hrs.
Scopes and limitations of statistics in empirical research; Role of probability theory in
statistics; Role of computer technology in statistics
Unit 2. Descriptive Statistics 6 Hrs.
Measures of location: mean, median, mode, partition values and their properties;
Measures of dispersion: absolute and relative measure of variation; range, quartile
deviation, standard deviation; Other measures: Coefficient of variation; Measures of
skewness and kurtosis.
Unit 3. Probability 5 Hrs.
Introduction of probability: Basic terminology in probability: sample space, events,
random experiment, trial, mutually exclusive events, equally likely events,
independent events; Definitions of probability: Classical, statistical, axiomatic
definitions; Basic principles of counting; Laws of probability: Additive and
multiplicative; Conditional probability; Bayes' Theorem.
Unit 4. Random Variable and Expectation 2 Hrs.
Random Variables: Discrete and continuous random Variables; Probability
distribution of random variables; Expected value of discrete & continuous random
Variable.
Unit 5. Jointly Distributed Random Variables and Probability Distributions 4 Hrs.
Joint Probability Distribution of two random variables: Joint probability mass
functions and density functions; Marginal probability mass and density functions;
Mean, variance, covariance and correlation of random variables; Independent random
variables; Illustrative numerical problems.
Unit 6. Discrete Probability Distributions 5 Hrs.
Bernoulli and binomial random variable and their distributions and moments;
Computing binomial probabilities; Fitting of binomial distribution; Poisson random
variable and its distribution and moments; Computing Poisson probabilities; Fitting of
Poisson distribution.
Unit 7. Continuous Probability Distributions 6 Hrs.
Normal distribution and its moments; Standardization of normally distributed random
variable; Measurement of areas under the normal curve; Negative exponential
distribution and its moments; Concept of hazard rate function.
Unit 8. Chi-square, t and F Distribution 4 Hrs.
Characteristics function of normal random variable; Distribution of sum and mean of
n independent normal random variables; Canonical definitions of chi-square, t and F
random variables and their distributions; Joint distribution of X and S2
in case of
normal distribution.
Unit 9. Inferential Statistics 7 Hrs.
Simple random sampling method and random sample; Sampling distribution and
standard error; Distinction between descriptive and inferential statistics; General
concept of point and interval estimation; Criteria for good estimator; Maximum
likelihood method of estimation; Estimation of mean and variance in normal
distribution; Estimation of proportion in binomial distribution; Confidential interval
of mean in normal distribution; Concept of hypothesis testing; Level of significance
and power of a test; Tests concerning the mean of a normal distribution case – when
variance is known (Ζ-test) and unknown (t-test)
Unit 10. Correlation and Linear Regression 4 Hrs.
Simple Correlation: Scatter diagram; Karl Pearson's correlation coefficient and its
properties, Simple Linear Regression: Model and assumptions of simple linear
regression; Least square estimators of regression coefficients; Tests of significance of
regression coefficients; Coefficient of determination
Text Books: Sheldon M. Ross, Introduction to Probability and Statistics for
Engineers and Scientists, 3rd
Edition, India: Academic Press, 2005.
References: • Richard A. Johnson, Miller and Freund's probability and
Statistics for Engineers, 6th
Edition, Indian reprint: Pearson
Education, 2001.
• Ronald E. Walpole, R.H. Myers, S.L. Myers, and K. Ye, Probability
and Statistics for Engineers and Scientists, 7th
Edition, Indian
reprint: Pearson Education, 2005.
Note:
1. Theory and practice should go side by side.
2. It is recommended 45 hours for lectures and 15 additional hours for tutorial class
for completion of the course in the semester.
3. SPSS software should be used for data analysis.
4. Students should have intermediate knowledge of Mathematics.
5. Home works and assignments covering the lecture materials will be given
throughout the semester.
Course Title: Calculus and Analytical Geometry
Course no: MTH-104 Full Marks: 90+10
Credit hours: 3 P.M: 36+4
Nature of Course: Theory
Course Synopsis: Preliminaries revision of differentiation and integration;
Techniques of integration infinite series; Vectors and analytical
geometry in space (differential geometry). Vector valued
functions. Multivariable functions and partial derivatives. Multiple
integrals and integration in vector fields. Partial derivatives;
Equations of First Partial Derivatives.
Goal: This course aims at providing students with some advanced topics in undergraduate
calculus and fundamental concepts of partial differentiation and P.D.E of second
order. It is assured that a student who has done Certificate Level papers in
mathematics will be able to study this course.
Course Contents:
Unit 1. Topics in Differential Calculus and Integral Calculus 8 Hrs.
1.1 Functions and Graphs
1.2 Extreme values of functions; graphing of derivatives
1.3 Mean value integers
1.4 Definite integers, Properties and application, Mean value
theory for definite integers
1.5 Fundamental theory of Integral Calculus and application, Improper
integrals
Unit 2. Infinite Series 5 Hrs.
2.1 Infinite sequence and sequence of convergence and divergence
2.2 Integral test, comparison test, ratio and root test
2.3 Absolute and conditional convergence
1.4 Power series, Taylor and Maclaurin series, convergence of Taylor series
Unit 3. Conic Section 3 Hrs.
3.1 Classifying conic sections by eccentricity
3.2 Plane curves, parametric and polar equations, integration in polar coordinates
Unit 4. Vectors and Vectors Valued Functions 6 Hrs.
4.1 Vectors in the space
4.2 Lines and planes in space
4.3 Cylinders and Quadric surfaces
4.4 Cylindrical and Spherical Coordinates
4.5 Vector valued functions and space curves
4.6 Unit tangent vector, curvature and torsion and TNB system
Unit 5. Multiple Integrals 5 Hrs.
5.1 Double integrals in rectangular polar coordinates
5.2 Finding areas, moments and centre of mass
5.3 Triple integrals in rectangular coordinates and application
5.4 Substitutes in multiple integrals
Unit 6. Multivariate Calculus 9 Hrs.
6.1 Functions, limits and continuity of two or more variables
6.2 Partial derivatives
6.3 Differentiability, Differentials, Total Differential Coefficients
6.4 Directional derivatives and gradient vectors
6.5 Extreme values
6.6 Lagrange Multiplies
Unit 7. Partial Differential Equations 9 Hrs.
7.1 Review of Ordinary Differential Equations
7.2 Analysis of P.D.E of 1st
and 2nd
order
7.3 Linear equations of the 1st
order and the general solutions
7.4 P.D.E of 2nd
order, its derivation and basic concepts
7.5 Solution of general P.D.E with constant coefficients, complimentary solution
and integral solution
7.6 Wave equations and heat equations and their solutions (Chapter II, Section
11.1, 11.2, 11.4, 11.5). Erwin and Kreyszig. 8th
edition, John-Wiley
Publications.
Text Books
Thomas and Fenns: Calculus and Analytical Geometry, 9th
Edition, 2004. (Thomas,
Jr. G. B., and Finney, Ross L. Publisher: Pearson Education Pvt. Ltd.
Kreyszig, Erwin, Advanced Engineering Mathematics, John- Wiley & Sons (1991).
5th
Edition.
References
E.W. Swokowski, Calculus with Analytical Geometry, Second Alter Edition.
Sneddan Ian- Elements of Partial Differential Equations.
Course Title: Physics I
Course no: PHY-105 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: The course deals with related topics in Mechanics and
Electrodynamics. Mechanics: Non Relativistic Particle dynamics, conservation laws,
harmonic Oscillator, dynamics of rigid body, strength of materials, hydrodynamics.
Electrodynamics: Electrostatics, dielectrics, Electrostatic and magnetic energy,
Maxwell's equation, propagation of electromagnetic wave. Laboratory works are
designed to complement and supplement the theory course.
Goal: The course aims at introducing the concepts and methods of physics needed for
application in various branch of modern science and technology.
Course Content:
Mechanics
Unit 1. Newton's Law of Motion and Galilean Invariance 4 Hrs.
1.1 Newton's laws of motion
1.2 Reference frame, Galilean transformation, Galilean Invariance
1.3 Transformation equations
1.4 Non inertial frames of reference fictious forces
- Centrifugal and coriolis forces
Unit 2. Non Relativistic Particle Dynamics 4 Hrs.
2.1 Equation of motion of uncharged and charged particles, Charged particles in
constant and alternating electric field
2.2 Charged particles in a fields, magnetic field- cyclotron, magnetic focusing
2.3 Charge particles in combined electric and magnetic field
Unit 3. Conservation Laws 7 Hrs.
3.1 Laws of conservation of momentum and energy.
3.2 Conservative forces, potential energy,
3.3 Potential energy in electric and gravitational fields.
3.4 Non conservative forces, General laws of conservation of energy.
3.5 Collision in three dimensions, lab and cm. frames of reference, final
velocities after collision, scattering angle,
3.6 Law of conservation of angular momentum - rotational invariance of
potential energy
3.7 Example - motion of a planet, Kepler's laws
Unit 4.Harmonic Oscillator 6 Hrs.
4.1 Harmonic oscillator, energy, example: diatomic molecule.
4.2 An harmonic oscillator - pendulum with large oscillation
4.3 Damped oscillations, power factor, Q - factor
4.4 Driven oscillations, resonance, phase and half width
4.5 LCR and parallel resonance circuits.
Unit 5. Viscosity 2 Hrs.
5.1 Viscosity, Newton's law of viscous force, analogy between current flow and
viscous flow
5.2 Motion of a body in a viscous medium.
Electrodynamics
Unit 6. Electrostatics 7 Hrs.
6.1 Electric field and electric potential
6.2 Divergence of E and Gauss's law, applications
6.3 Solution of electrostatic problems, Poisson's and Lap lace's equations
6.4 Solution of Lap laces equations in spherical cylindrical coordinates and
rectangular coordinates
6.5 Examples conducting sphere in a uniform E field, method of images, point
charge and a conducting sphere, line charge and line images, systems of
conductors.
6.6 Solution of Poisson's equation
Unit 7.Dielectrics 4 Hrs.
7.1 Electric field in a dielectric media
- Polarization, field inside and outside a dielectric gauss's law in a dielectric
medium-displacement vector, electric susceptibility and
dielectric constant
- Boundary conditions on field vectors, boundary value problems in a
dielectric medium, dielectric sphere in a uniform el. field.
7.2 Molecular theory of dielectrics, induced dipoles
Unit 8.Electrostatic Energy 1 Hr.
8.1 Potential energy of a group of charges and charge distributions, energy density.
8.2 energy of a system of charged conductors
Unit 9. Magnetic Field Energy 1 Hr.
9.1 Vector potential, and magnetic field
9.2 Energy density in the magnetic field, magnetic energy of coupled circuits.
Unit 10. Slowly Varying Current 3 Hrs.
10.1 Transient and steady state behavior
10.2 Series and parallel connection of impedances
10.3 Power, power factor, Resonance.
Unit 11. Maxwell's Equation 6 Hrs.
11.1 Maxwell's equations - displacement current
11.2 Electromagnetic energy
11.3 Wave equations without and with source, boundary conditions
Laboratory Works:
• To draw I-V characteristics of Ohmic and non Ohmic resisters and find voltage
current ration.
• To study the junction diode and LED characteristics.
• To study the temperature dependence of resistance of a given semiconductors
• To determine the moment of inertia of a fly wheel.
• To determine the modulus of rigidity for the material of a rod by using the horizontal
pattern of the twisting apparatus.
• To determine the terminal velocity and find coefficient of viscosity by Stoke's
method.
• To determine the surface tension of work with a capillary tube.
• To determine the impedance of a given LCR circuit.
• To study characteristics of NPN transistor.
• To determine dielectric constant by using Lissagous pattern.
• To construct CE amplifier for the determination of the voltage gain of the amplifier.
• To study the characteristic of a Zener a diode (Switches) and use it to regulate power
supply.
• To construct and study the working of NOT-AND-OR, NAND and NOR gates.
• To construct and study the working of OR, NAN and NOR gates.
Text books:
(1) D.S. Mathur, Mechanics, S. Chand and Company Ltd
(2) John R. Ritz, Frederick J. Milford and Robert W. Christy, Foundations of
Electromagnetic Theory, Narosa Publishing House
References:
(1) David J Griffith, Introduction to Electrodynamics, 2nd
Edition, Prentice Hall of
India, 1994.
Prerequisite: Calculus based introductory physics
Note: Home work assignments: Several numerical problems to be given every week.
Course Title: Biology I
Course no: BIO-106 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Living System and their properties, major biological molecules, basic
physiological processes, introduction of genetics, basic concepts of diversity and
evolution.
Goal: The course is aimed at providing the introduction of biological system with
respect to nature, behavior and functioning of the cell.
Course Contents:
Unit 1. 5 Hrs.
1.1 Introduction: Brief introduction to all aspects of Biology
1.2 Bio-molecular: Carbohydrates, Lipids, Proteins and Nucleic acid
Unit 2. 19 Hrs.
2.1 Cell structure and functions: Cell theory, cell membrane, transport system
across the membrane, organelles composed of membranes, nonmenbranous
organelles, nuclear components and major cell types
2.2 Enzymes: Nomenclature, biocatalysis, action of enzymes, environmental
factors, co-enzymes, enzyme activation and inhibition.
2.3 Biochemical Pathways: Introduction, cellular respiration, glycolysis, TCA
Cycle, ETC, ATP calculation, fermentation, protein and fat metabolism,
photosynthesis-C3 and C4 pathways, photorespiration, chemosynthesis,
transpiration.
Unit 3. 7 Hrs.
3.1 Genetics: Laws of inheritance, linkage and crossing over
3.2 Diversity within species: Gene pool concept, genetic variety, role of natural
selection in evolution, factors influencing natural selection, Hardy-Weinberg
equilibrium concept and application
Unit 4. 6 Hrs.
4.1 Material exchange in the body: Basic principle, blood circulation, pulmonary
and systemic, nature of blood and role of heart, gas exchange, respiratory
anatomy, lung function, digestive system, kidney structure and function
Unit 5. 8 Hrs.
5.1 Body's control mechanism: Nerve impulse, synapse, CNS organization,
endocrine system, sensory input and output coordination
5.2 Immune system: Defense mechanism, humeral and cell mediated immune
responses, vaccines and monoclonal antibody.
Laboratory Works:
1. Identification of biomolecules: cellulose, Lignin, Lipid, Protein.
2. Analysis of amino acids in protein by paper chromatography and paper
electrophoresis.
3. Separation of photo synthetic pigments by paper chromatography.
4. Determination of value of RQ of different respiratory substrates.
5. Study of different types of plant and anima cells in temporary preparation.
Text Books:
E.D. Enger & F.C. Ross, Concepts in Biology, 9th
Edition, Tata McGraw Hill
Reference Book:
P.H. Reven et.al, Biology, 5th
Ed. WBC McGraw Hill.
Course Title: Geology I
Course no: GEO-107 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Fundamental concepts of contemporary earth and environmental
science and engineering with increasing computer application.
Goal: This course aims at providing general understanding of Earth and environmental
science and engineering
Course Contents:
Unit 1. 10 Hrs.
1.1 New Global Tectonic framework of the earth: Continental margins, earthquakes,
volcanoes and mountain ranges.
1.2 Crystal, minerals and rocks: rock types and rock systematic
Unit 2. 10 Hrs.
2.1 Mineral deposits and mineral mining: technologies, reserves, economics and
environment
2.2 Engineering geology: construction and stability of structures and natural and
artificial face stability
Unit 3. 10 Hrs.
3.1 Climate changes and natural disasters: Landslides, Floods and Desertification.
3.2 Natural resources depletion: Hydrocarbons, metals and new sources of energy and
materials.
Unit 4. 10 Hrs.
4.1 Geographic Information system (GIS): Vectors and raster and remote sensing
database management.
4.2 Computer aided data management: remote sensing data acquisition, storage,
processing and interpretation.
4.3 GIS and RS packages: ERDAS, ER Mapper, ArcView and other operating
systems and capabilities
Laboratory works: Mineral / Rock identification, Soil types, Reserve calculation,
Slope stability calculation, Rock Mass Ratings, ER Mapper,
ArcView, ILWIS tour, RS data analysis, Digitization, practice and
Geographic locking, GIS Layers shows and illustrations, GIS
assignment with digital RS data.
Practical:
• To identify elements of symmetry of a cube.
• To identify 5 oxides and 5 sulphide minerals.
• To calculate reserve of a ore deposit.
• To calculate cost - benefit analysis of a mining enterprise
• To calculate the stability of natural slope
• To calculate and interpret precipitation data
• To calculate rock mass rating form data
• To perform digitization and geographic locking in computer
• GIS assignment with RS data.
Text Books: No specific text book covering all materials but a working manual could be
easily prepared.
Reference:
Homework: Homework assignments covering lecture materials and primary
numerical exercises.
Assignments: Given throughout the semester.
Computer Usage: MS-WINDOWS (WINDOWS 98/XP) base PC of workstation
Prerequisites: Basic IT literacy
Category contents: Science Aspect: 50%
Engineering Aspect: 50%
Course Title: Statistics I
Course no: STA-108 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Concept of Applied Statistical Techniques and its Applications
Goal: This course makes students able to understand Applied Statistical Techniques and
their applications in the allied areas.
Course Contents:
Unit 1: Sampling Techniques 10 Hrs.
Types of Sampling; Simple Random Sampling with and without Replacement;
Stratified Random Sampling; Ratio and Regression Method of Estimation under
Simple and Stratified Random Sampling; Systematic Sampling; Multistage Sampling;
Estimation of population total and its Variance.
Unit 2: Non Parametric Test 16 Hrs.
Chi-square test: Test of goodness of fit; Test for independence (Categorical Data).
Definition of Order Statistics; Run Test; Sign Test; Wilcoxon Matched Pairs Signed
Ranks Test; Mann-Whitney U Test; Median Test; Kolmogorov Smirnov Test (One
Sample Case); Cochran Q Test; Kruskl Wallis One way ANOVA Test; Friedman
Two way ANOVA Test.
Unit 3: Correlation and Regression Analysis 19 Hrs.
Partial and Multiple Correlations; Multiple Linear Regressions: Assumptions;
Coefficient Estimation, and Significance Test; Coefficient of Determination; Cobb-
Dauglas Production Function; Growth Model; Logistic Regression; Autoregressive
Model of order One, and Appraisal of Linear Models (Heteroscedasticity,
Multicolinearity, Autocorrelation).
Note:
1. Theory and practice should go side by side.
2. It is recommended 45 hours for lectures and 15 additional hours for tutorial
class for completion of the course in the semester.
3. SPSS Software should be used for data analysis.
4. Home works and assignments covering the lecture materials will be given
throughout the semester.
Text Books:
• Draper, N. and H. Smith, Applied Regression Analysis, 2nd
edition, New York:
John Wiley & Sons, 1981.
• Hogg & Tanis, Probability & Statistical Inference, 6th edition, First Indian
Reprint, 2002.
• Gujaratii, D. Basic Econometrics, International edition, 1995.
• Gibbons, J.D. Nonparametric Statistical Inference. International Student
Edition.
• Siegel, S. Nonparametric Statistics for the Behavioural Sciences. McGraw-
Hill, New York.
References:
• Hollander, M. & Wolfe, Nonparametric Statistical Methods. Johns Wiley &
Sons, New York.

Mais conteúdo relacionado

Mais procurados

Sentiment analysis using naive bayes classifier
Sentiment analysis using naive bayes classifier Sentiment analysis using naive bayes classifier
Sentiment analysis using naive bayes classifier Dev Sahu
 
Model evaluation in the land of deep learning
Model evaluation in the land of deep learningModel evaluation in the land of deep learning
Model evaluation in the land of deep learningPramit Choudhary
 
Machine Learning Applications in NLP.ppt
Machine Learning Applications in NLP.pptMachine Learning Applications in NLP.ppt
Machine Learning Applications in NLP.pptbutest
 
Machine Learning Unit 1 Semester 3 MSc IT Part 2 Mumbai University
Machine Learning Unit 1 Semester 3  MSc IT Part 2 Mumbai UniversityMachine Learning Unit 1 Semester 3  MSc IT Part 2 Mumbai University
Machine Learning Unit 1 Semester 3 MSc IT Part 2 Mumbai UniversityMadhav Mishra
 
Machine Learning: Foundations Course Number 0368403401
Machine Learning: Foundations Course Number 0368403401Machine Learning: Foundations Course Number 0368403401
Machine Learning: Foundations Course Number 0368403401butest
 
Introduction to Item Response Theory
Introduction to Item Response TheoryIntroduction to Item Response Theory
Introduction to Item Response TheoryNathan Thompson
 
Human in the loop: Bayesian Rules Enabling Explainable AI
Human in the loop: Bayesian Rules Enabling Explainable AIHuman in the loop: Bayesian Rules Enabling Explainable AI
Human in the loop: Bayesian Rules Enabling Explainable AIPramit Choudhary
 
Text Classification, Sentiment Analysis, and Opinion Mining
Text Classification, Sentiment Analysis, and Opinion MiningText Classification, Sentiment Analysis, and Opinion Mining
Text Classification, Sentiment Analysis, and Opinion MiningFabrizio Sebastiani
 
Islamic University Pattern Recognition & Neural Network 2019
Islamic University Pattern Recognition & Neural Network 2019 Islamic University Pattern Recognition & Neural Network 2019
Islamic University Pattern Recognition & Neural Network 2019 Rakibul Hasan Pranto
 
Machine learning - session 3
Machine learning - session 3Machine learning - session 3
Machine learning - session 3Luis Borbon
 
Presentation on supervised learning
Presentation on supervised learningPresentation on supervised learning
Presentation on supervised learningTonmoy Bhagawati
 
Using Item Response Theory to Improve Assessment
Using Item Response Theory to Improve AssessmentUsing Item Response Theory to Improve Assessment
Using Item Response Theory to Improve AssessmentNathan Thompson
 
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...Madhav Mishra
 
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)台灣資料科學年會
 
Learning from Multiple Annotators
Learning  from  Multiple AnnotatorsLearning  from  Multiple Annotators
Learning from Multiple AnnotatorsGaurav Trivedi
 
Efficiently finding the parameter for emergign pattern based classifier
Efficiently finding the parameter for emergign pattern based classifierEfficiently finding the parameter for emergign pattern based classifier
Efficiently finding the parameter for emergign pattern based classifierGanesh Pavan Kambhampati
 

Mais procurados (18)

Sentiment analysis using naive bayes classifier
Sentiment analysis using naive bayes classifier Sentiment analysis using naive bayes classifier
Sentiment analysis using naive bayes classifier
 
Model evaluation in the land of deep learning
Model evaluation in the land of deep learningModel evaluation in the land of deep learning
Model evaluation in the land of deep learning
 
Machine Learning Applications in NLP.ppt
Machine Learning Applications in NLP.pptMachine Learning Applications in NLP.ppt
Machine Learning Applications in NLP.ppt
 
Machine Learning Unit 1 Semester 3 MSc IT Part 2 Mumbai University
Machine Learning Unit 1 Semester 3  MSc IT Part 2 Mumbai UniversityMachine Learning Unit 1 Semester 3  MSc IT Part 2 Mumbai University
Machine Learning Unit 1 Semester 3 MSc IT Part 2 Mumbai University
 
Machine Learning: Foundations Course Number 0368403401
Machine Learning: Foundations Course Number 0368403401Machine Learning: Foundations Course Number 0368403401
Machine Learning: Foundations Course Number 0368403401
 
Introduction to Item Response Theory
Introduction to Item Response TheoryIntroduction to Item Response Theory
Introduction to Item Response Theory
 
Human in the loop: Bayesian Rules Enabling Explainable AI
Human in the loop: Bayesian Rules Enabling Explainable AIHuman in the loop: Bayesian Rules Enabling Explainable AI
Human in the loop: Bayesian Rules Enabling Explainable AI
 
Text Classification, Sentiment Analysis, and Opinion Mining
Text Classification, Sentiment Analysis, and Opinion MiningText Classification, Sentiment Analysis, and Opinion Mining
Text Classification, Sentiment Analysis, and Opinion Mining
 
Islamic University Pattern Recognition & Neural Network 2019
Islamic University Pattern Recognition & Neural Network 2019 Islamic University Pattern Recognition & Neural Network 2019
Islamic University Pattern Recognition & Neural Network 2019
 
Machine learning - session 3
Machine learning - session 3Machine learning - session 3
Machine learning - session 3
 
Presentation on supervised learning
Presentation on supervised learningPresentation on supervised learning
Presentation on supervised learning
 
Decision tree
Decision tree Decision tree
Decision tree
 
Using Item Response Theory to Improve Assessment
Using Item Response Theory to Improve AssessmentUsing Item Response Theory to Improve Assessment
Using Item Response Theory to Improve Assessment
 
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...
Applied Artificial Intelligence Unit 4 Semester 3 MSc IT Part 2 Mumbai Univer...
 
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)
孔令傑 / 給工程師的統計學及資料分析 123 (2016/9/4)
 
Item Response Theory (IRT)
Item Response Theory (IRT)Item Response Theory (IRT)
Item Response Theory (IRT)
 
Learning from Multiple Annotators
Learning  from  Multiple AnnotatorsLearning  from  Multiple Annotators
Learning from Multiple Annotators
 
Efficiently finding the parameter for emergign pattern based classifier
Efficiently finding the parameter for emergign pattern based classifierEfficiently finding the parameter for emergign pattern based classifier
Efficiently finding the parameter for emergign pattern based classifier
 

Destaque (8)

2nd sem
2nd sem2nd sem
2nd sem
 
3rd sem
3rd sem3rd sem
3rd sem
 
3rd sem
3rd sem3rd sem
3rd sem
 
Ci 102
Ci 102Ci 102
Ci 102
 
2nd sem
2nd sem2nd sem
2nd sem
 
Keeping it in the family animated
Keeping it in the family   animatedKeeping it in the family   animated
Keeping it in the family animated
 
Tareasoftware
TareasoftwareTareasoftware
Tareasoftware
 
Keeping It In The Family Animated
Keeping It In The Family   AnimatedKeeping It In The Family   Animated
Keeping It In The Family Animated
 

Semelhante a 1st sem (20)

4th sem
4th sem4th sem
4th sem
 
HiteshAgarwal_CPEE
HiteshAgarwal_CPEEHiteshAgarwal_CPEE
HiteshAgarwal_CPEE
 
797_NaveenKKapoor_CEE
797_NaveenKKapoor_CEE797_NaveenKKapoor_CEE
797_NaveenKKapoor_CEE
 
5th sem
5th sem5th sem
5th sem
 
5th sem
5th sem5th sem
5th sem
 
776_AlluruMPranav_CEE
776_AlluruMPranav_CEE776_AlluruMPranav_CEE
776_AlluruMPranav_CEE
 
603_SaiKiranPutta_CEE
603_SaiKiranPutta_CEE603_SaiKiranPutta_CEE
603_SaiKiranPutta_CEE
 
402_DheerajKura
402_DheerajKura402_DheerajKura
402_DheerajKura
 
Machine learning ppt unit one syllabuspptx
Machine learning ppt unit one syllabuspptxMachine learning ppt unit one syllabuspptx
Machine learning ppt unit one syllabuspptx
 
421_PrakashMudholkar
421_PrakashMudholkar421_PrakashMudholkar
421_PrakashMudholkar
 
Miraj Vashi_CPEE
Miraj Vashi_CPEEMiraj Vashi_CPEE
Miraj Vashi_CPEE
 
438_AmeeruddinMohammed
438_AmeeruddinMohammed438_AmeeruddinMohammed
438_AmeeruddinMohammed
 
671_JeevanRavula_CEE
671_JeevanRavula_CEE671_JeevanRavula_CEE
671_JeevanRavula_CEE
 
598_RamaSrikanthJakkam_CEE
598_RamaSrikanthJakkam_CEE598_RamaSrikanthJakkam_CEE
598_RamaSrikanthJakkam_CEE
 
Amcat test-syllabus
Amcat test-syllabusAmcat test-syllabus
Amcat test-syllabus
 
Amcat test syllabus
Amcat test syllabusAmcat test syllabus
Amcat test syllabus
 
2018 Modern Math Workshop - Nonparametric Regression and Classification for M...
2018 Modern Math Workshop - Nonparametric Regression and Classification for M...2018 Modern Math Workshop - Nonparametric Regression and Classification for M...
2018 Modern Math Workshop - Nonparametric Regression and Classification for M...
 
566_SriramDandamudi_CEE
566_SriramDandamudi_CEE566_SriramDandamudi_CEE
566_SriramDandamudi_CEE
 
Amcat test-syllabus
Amcat test-syllabusAmcat test-syllabus
Amcat test-syllabus
 
Mtech syllabus computer science uptu
Mtech syllabus computer science uptu Mtech syllabus computer science uptu
Mtech syllabus computer science uptu
 

Último

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 

Último (20)

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 

1st sem

  • 1. Course Title: Introduction to Information Technology Course no: CSC-101 Full Marks: 87+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: Fundamental concept of Information technology. Computer systems, Computer software, DBMS, and application of computer science. Goal: This course introduces fundamental concepts of Information Technology and computer science. Course Contents: Unit 1. Introduction to Computer Systems 10 Hrs. Introduction to computers, Classification of digital computer systems, Anatomy of a digital Computer, Computer Architecture, Memory system, Memory Units, Auxiliary Storage devices, Inputs devices, Output Devices. Unit 2. Computer Software and Software Development 6 Hrs. Introduction to Computer Software, Operating Systems, Programming Languages, General Software Features and Trends. Unit 3. Database Management Systems 6 Hrs. Data processing, Introduction to Database Management systems, Database design Unit 4. Telecommunications 8 Hrs. Introduction to Telecommunications, Computer Networks, Communication Systems, Distributed systems Unit 5. Internet and New Technologies in Information Technology 10 Hrs. Internet, Multimedia tools and system, Intranets, Electronic Commerce, Hypermedia, Data Warehouses and Data Marts, Data Mining, Geographical Information System Unit 6. Applications of Information Technology 5 Hrs. Computers in Business and Industry, Computers in education, training, Computers in Entertainment, science, medicine and Engineering Laboratory works: The main objective is familiarizing students with operating system and desktop applications using current version of windows. Text / Reference books: Alexis Leon, Mathews Leon, Fundamentals of Information Technology, Leon TechWorld
  • 2. Course Title: Fundamentals of Computer Programming Course no: CSC-102 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: This course contains the concepts of programming methodology using C. Goal: This course is designed to familiarize students to the techniques of programming in C. Course Contents: Unit 1. Problem Solving with Computer 2 Hrs. Problem analysis, Algorithms and Flowchart, Coding, Compilation and Execution, History of C, Structure of C program, Debugging, Testing and Documentation Unit 2. Elements of C 4 Hrs. C Tokens, Escape sequence, Delimiters, Variables, Data types, Constants/ Literals, Expressions, Statements and Comments Unit 3. Input and Output 2 Hrs. Conversion specification, I/O operation, Formatted I/O Unit 4. Operators and Expression 4 Hrs. Arithmetic operator, Relational operator, Logical or Boolean operator, Assignment, Operator, Ternary operator, Bitwise operator, Increment or Decrement operator, Comma operator. Unit 5. Control Statement 4 Hrs. Branching, Looping, Conditional Statement, Exit function, Difference between break and exit Unit 6. Arrays 6 Hrs. Introduction, Declaration of array, Initialization of array, Sorting, Multidimensional array Unit 7. Functions 5 Hrs. Library Functions, User defined functions, Recursion, Function declaration, Local and global variables, Use of array in function, Passing by Value, Passing by Address
  • 3. Unit 8. Pointers 6 Hrs. Introduction, The & and * operator, Declaration of pointer, Pointer to pointer, Pointer arithmetic, Array and Pointer, Pointer and array, Pointer with multidimensional array, Pointer and strings, Array of pointer with string, Dynamic memory allocation Unit 9. Structure and Union 5 Hrs. Introduction, Array of structure, Passing structure to function, Passing array of structure to function, Structure within structure ( Nested Structure), Union, Pointer to structure Unit 10. Files and file handling in C 4 Hrs. Concept of file, Opening and closing of file, Modes, Input/ output function, Random access in file, Printing a file Unit 11. Introduction to Graphics 3 Hrs. Modes, Initialization, Graphics Function Laboratory works: This course requires a lot of programming practices. Each topic must be followed by a practical session. Some practical sessions include programming to: • Create, compile and run simple C programs, handle different data types available in C, perform arithmetic operations in C, perform formatted input and out put operations, perform character input and output operations. • Perform logical operations, create decision making programs, create loops to repeat task, sue different looping method. • Create user-defined factions, create recursive functions, work with automatic, global and static variables, create manipulate arrays and matrices (single and multi-dimensional), work with pointes, dynamically allocate de-allocate storage space during runtime, manipulate strings (character arrays) using various string handling functions. • create and use structures an files to keep record of students, employees etc References: • Deitel, C.: How to Program, 2/e (With CD), Pearson Education. • Al Kelley, Ira Pohl: "A Book on C", Pearson Education. • Brian W. Keringhan & Dennis M. Ritchie: "The C programming Language", PHI • Bryons S. Gotterfried: "Programming with C," TMH • Stephen G. Kochan: "Programming in C", CBS publishers & distributors.
  • 4. • Yashavant Kanetkar: "Let us C", BPB Publications
  • 5. Course Title: Probability and Statistics Course no: STA-103 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: Concept of descriptive statistics, probability, probability distributions, inferential statistics and their applications. Goal: This course enhances the ability of students in computing and understanding summary statistics; understanding the concept of probability and probability distributions with their applications in statistics. Finally, students will develop their ability of using inferential statistics in decision-making processes. Course Contents: Unit 1. Introduction 2 Hrs. Scopes and limitations of statistics in empirical research; Role of probability theory in statistics; Role of computer technology in statistics Unit 2. Descriptive Statistics 6 Hrs. Measures of location: mean, median, mode, partition values and their properties; Measures of dispersion: absolute and relative measure of variation; range, quartile deviation, standard deviation; Other measures: Coefficient of variation; Measures of skewness and kurtosis. Unit 3. Probability 5 Hrs. Introduction of probability: Basic terminology in probability: sample space, events, random experiment, trial, mutually exclusive events, equally likely events, independent events; Definitions of probability: Classical, statistical, axiomatic definitions; Basic principles of counting; Laws of probability: Additive and multiplicative; Conditional probability; Bayes' Theorem. Unit 4. Random Variable and Expectation 2 Hrs. Random Variables: Discrete and continuous random Variables; Probability distribution of random variables; Expected value of discrete & continuous random Variable. Unit 5. Jointly Distributed Random Variables and Probability Distributions 4 Hrs. Joint Probability Distribution of two random variables: Joint probability mass functions and density functions; Marginal probability mass and density functions; Mean, variance, covariance and correlation of random variables; Independent random variables; Illustrative numerical problems.
  • 6. Unit 6. Discrete Probability Distributions 5 Hrs. Bernoulli and binomial random variable and their distributions and moments; Computing binomial probabilities; Fitting of binomial distribution; Poisson random variable and its distribution and moments; Computing Poisson probabilities; Fitting of Poisson distribution. Unit 7. Continuous Probability Distributions 6 Hrs. Normal distribution and its moments; Standardization of normally distributed random variable; Measurement of areas under the normal curve; Negative exponential distribution and its moments; Concept of hazard rate function. Unit 8. Chi-square, t and F Distribution 4 Hrs. Characteristics function of normal random variable; Distribution of sum and mean of n independent normal random variables; Canonical definitions of chi-square, t and F random variables and their distributions; Joint distribution of X and S2 in case of normal distribution. Unit 9. Inferential Statistics 7 Hrs. Simple random sampling method and random sample; Sampling distribution and standard error; Distinction between descriptive and inferential statistics; General concept of point and interval estimation; Criteria for good estimator; Maximum likelihood method of estimation; Estimation of mean and variance in normal distribution; Estimation of proportion in binomial distribution; Confidential interval of mean in normal distribution; Concept of hypothesis testing; Level of significance and power of a test; Tests concerning the mean of a normal distribution case – when variance is known (Ζ-test) and unknown (t-test) Unit 10. Correlation and Linear Regression 4 Hrs. Simple Correlation: Scatter diagram; Karl Pearson's correlation coefficient and its properties, Simple Linear Regression: Model and assumptions of simple linear regression; Least square estimators of regression coefficients; Tests of significance of regression coefficients; Coefficient of determination Text Books: Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists, 3rd Edition, India: Academic Press, 2005. References: • Richard A. Johnson, Miller and Freund's probability and Statistics for Engineers, 6th Edition, Indian reprint: Pearson Education, 2001. • Ronald E. Walpole, R.H. Myers, S.L. Myers, and K. Ye, Probability and Statistics for Engineers and Scientists, 7th Edition, Indian reprint: Pearson Education, 2005.
  • 7. Note: 1. Theory and practice should go side by side. 2. It is recommended 45 hours for lectures and 15 additional hours for tutorial class for completion of the course in the semester. 3. SPSS software should be used for data analysis. 4. Students should have intermediate knowledge of Mathematics. 5. Home works and assignments covering the lecture materials will be given throughout the semester.
  • 8. Course Title: Calculus and Analytical Geometry Course no: MTH-104 Full Marks: 90+10 Credit hours: 3 P.M: 36+4 Nature of Course: Theory Course Synopsis: Preliminaries revision of differentiation and integration; Techniques of integration infinite series; Vectors and analytical geometry in space (differential geometry). Vector valued functions. Multivariable functions and partial derivatives. Multiple integrals and integration in vector fields. Partial derivatives; Equations of First Partial Derivatives. Goal: This course aims at providing students with some advanced topics in undergraduate calculus and fundamental concepts of partial differentiation and P.D.E of second order. It is assured that a student who has done Certificate Level papers in mathematics will be able to study this course. Course Contents: Unit 1. Topics in Differential Calculus and Integral Calculus 8 Hrs. 1.1 Functions and Graphs 1.2 Extreme values of functions; graphing of derivatives 1.3 Mean value integers 1.4 Definite integers, Properties and application, Mean value theory for definite integers 1.5 Fundamental theory of Integral Calculus and application, Improper integrals Unit 2. Infinite Series 5 Hrs. 2.1 Infinite sequence and sequence of convergence and divergence 2.2 Integral test, comparison test, ratio and root test 2.3 Absolute and conditional convergence 1.4 Power series, Taylor and Maclaurin series, convergence of Taylor series Unit 3. Conic Section 3 Hrs. 3.1 Classifying conic sections by eccentricity 3.2 Plane curves, parametric and polar equations, integration in polar coordinates Unit 4. Vectors and Vectors Valued Functions 6 Hrs. 4.1 Vectors in the space 4.2 Lines and planes in space 4.3 Cylinders and Quadric surfaces 4.4 Cylindrical and Spherical Coordinates 4.5 Vector valued functions and space curves 4.6 Unit tangent vector, curvature and torsion and TNB system
  • 9. Unit 5. Multiple Integrals 5 Hrs. 5.1 Double integrals in rectangular polar coordinates 5.2 Finding areas, moments and centre of mass 5.3 Triple integrals in rectangular coordinates and application 5.4 Substitutes in multiple integrals Unit 6. Multivariate Calculus 9 Hrs. 6.1 Functions, limits and continuity of two or more variables 6.2 Partial derivatives 6.3 Differentiability, Differentials, Total Differential Coefficients 6.4 Directional derivatives and gradient vectors 6.5 Extreme values 6.6 Lagrange Multiplies Unit 7. Partial Differential Equations 9 Hrs. 7.1 Review of Ordinary Differential Equations 7.2 Analysis of P.D.E of 1st and 2nd order 7.3 Linear equations of the 1st order and the general solutions 7.4 P.D.E of 2nd order, its derivation and basic concepts 7.5 Solution of general P.D.E with constant coefficients, complimentary solution and integral solution 7.6 Wave equations and heat equations and their solutions (Chapter II, Section 11.1, 11.2, 11.4, 11.5). Erwin and Kreyszig. 8th edition, John-Wiley Publications. Text Books Thomas and Fenns: Calculus and Analytical Geometry, 9th Edition, 2004. (Thomas, Jr. G. B., and Finney, Ross L. Publisher: Pearson Education Pvt. Ltd. Kreyszig, Erwin, Advanced Engineering Mathematics, John- Wiley & Sons (1991). 5th Edition. References E.W. Swokowski, Calculus with Analytical Geometry, Second Alter Edition. Sneddan Ian- Elements of Partial Differential Equations.
  • 10. Course Title: Physics I Course no: PHY-105 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: The course deals with related topics in Mechanics and Electrodynamics. Mechanics: Non Relativistic Particle dynamics, conservation laws, harmonic Oscillator, dynamics of rigid body, strength of materials, hydrodynamics. Electrodynamics: Electrostatics, dielectrics, Electrostatic and magnetic energy, Maxwell's equation, propagation of electromagnetic wave. Laboratory works are designed to complement and supplement the theory course. Goal: The course aims at introducing the concepts and methods of physics needed for application in various branch of modern science and technology. Course Content: Mechanics Unit 1. Newton's Law of Motion and Galilean Invariance 4 Hrs. 1.1 Newton's laws of motion 1.2 Reference frame, Galilean transformation, Galilean Invariance 1.3 Transformation equations 1.4 Non inertial frames of reference fictious forces - Centrifugal and coriolis forces Unit 2. Non Relativistic Particle Dynamics 4 Hrs. 2.1 Equation of motion of uncharged and charged particles, Charged particles in constant and alternating electric field 2.2 Charged particles in a fields, magnetic field- cyclotron, magnetic focusing 2.3 Charge particles in combined electric and magnetic field Unit 3. Conservation Laws 7 Hrs. 3.1 Laws of conservation of momentum and energy. 3.2 Conservative forces, potential energy, 3.3 Potential energy in electric and gravitational fields. 3.4 Non conservative forces, General laws of conservation of energy. 3.5 Collision in three dimensions, lab and cm. frames of reference, final velocities after collision, scattering angle, 3.6 Law of conservation of angular momentum - rotational invariance of potential energy 3.7 Example - motion of a planet, Kepler's laws
  • 11. Unit 4.Harmonic Oscillator 6 Hrs. 4.1 Harmonic oscillator, energy, example: diatomic molecule. 4.2 An harmonic oscillator - pendulum with large oscillation 4.3 Damped oscillations, power factor, Q - factor 4.4 Driven oscillations, resonance, phase and half width 4.5 LCR and parallel resonance circuits. Unit 5. Viscosity 2 Hrs. 5.1 Viscosity, Newton's law of viscous force, analogy between current flow and viscous flow 5.2 Motion of a body in a viscous medium. Electrodynamics Unit 6. Electrostatics 7 Hrs. 6.1 Electric field and electric potential 6.2 Divergence of E and Gauss's law, applications 6.3 Solution of electrostatic problems, Poisson's and Lap lace's equations 6.4 Solution of Lap laces equations in spherical cylindrical coordinates and rectangular coordinates 6.5 Examples conducting sphere in a uniform E field, method of images, point charge and a conducting sphere, line charge and line images, systems of conductors. 6.6 Solution of Poisson's equation Unit 7.Dielectrics 4 Hrs. 7.1 Electric field in a dielectric media - Polarization, field inside and outside a dielectric gauss's law in a dielectric medium-displacement vector, electric susceptibility and dielectric constant - Boundary conditions on field vectors, boundary value problems in a dielectric medium, dielectric sphere in a uniform el. field. 7.2 Molecular theory of dielectrics, induced dipoles Unit 8.Electrostatic Energy 1 Hr. 8.1 Potential energy of a group of charges and charge distributions, energy density. 8.2 energy of a system of charged conductors Unit 9. Magnetic Field Energy 1 Hr. 9.1 Vector potential, and magnetic field 9.2 Energy density in the magnetic field, magnetic energy of coupled circuits.
  • 12. Unit 10. Slowly Varying Current 3 Hrs. 10.1 Transient and steady state behavior 10.2 Series and parallel connection of impedances 10.3 Power, power factor, Resonance. Unit 11. Maxwell's Equation 6 Hrs. 11.1 Maxwell's equations - displacement current 11.2 Electromagnetic energy 11.3 Wave equations without and with source, boundary conditions Laboratory Works: • To draw I-V characteristics of Ohmic and non Ohmic resisters and find voltage current ration. • To study the junction diode and LED characteristics. • To study the temperature dependence of resistance of a given semiconductors • To determine the moment of inertia of a fly wheel. • To determine the modulus of rigidity for the material of a rod by using the horizontal pattern of the twisting apparatus. • To determine the terminal velocity and find coefficient of viscosity by Stoke's method. • To determine the surface tension of work with a capillary tube. • To determine the impedance of a given LCR circuit. • To study characteristics of NPN transistor. • To determine dielectric constant by using Lissagous pattern. • To construct CE amplifier for the determination of the voltage gain of the amplifier. • To study the characteristic of a Zener a diode (Switches) and use it to regulate power supply. • To construct and study the working of NOT-AND-OR, NAND and NOR gates. • To construct and study the working of OR, NAN and NOR gates. Text books: (1) D.S. Mathur, Mechanics, S. Chand and Company Ltd (2) John R. Ritz, Frederick J. Milford and Robert W. Christy, Foundations of Electromagnetic Theory, Narosa Publishing House References: (1) David J Griffith, Introduction to Electrodynamics, 2nd Edition, Prentice Hall of India, 1994. Prerequisite: Calculus based introductory physics Note: Home work assignments: Several numerical problems to be given every week.
  • 13. Course Title: Biology I Course no: BIO-106 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: Living System and their properties, major biological molecules, basic physiological processes, introduction of genetics, basic concepts of diversity and evolution. Goal: The course is aimed at providing the introduction of biological system with respect to nature, behavior and functioning of the cell. Course Contents: Unit 1. 5 Hrs. 1.1 Introduction: Brief introduction to all aspects of Biology 1.2 Bio-molecular: Carbohydrates, Lipids, Proteins and Nucleic acid Unit 2. 19 Hrs. 2.1 Cell structure and functions: Cell theory, cell membrane, transport system across the membrane, organelles composed of membranes, nonmenbranous organelles, nuclear components and major cell types 2.2 Enzymes: Nomenclature, biocatalysis, action of enzymes, environmental factors, co-enzymes, enzyme activation and inhibition. 2.3 Biochemical Pathways: Introduction, cellular respiration, glycolysis, TCA Cycle, ETC, ATP calculation, fermentation, protein and fat metabolism, photosynthesis-C3 and C4 pathways, photorespiration, chemosynthesis, transpiration. Unit 3. 7 Hrs. 3.1 Genetics: Laws of inheritance, linkage and crossing over 3.2 Diversity within species: Gene pool concept, genetic variety, role of natural selection in evolution, factors influencing natural selection, Hardy-Weinberg equilibrium concept and application Unit 4. 6 Hrs. 4.1 Material exchange in the body: Basic principle, blood circulation, pulmonary and systemic, nature of blood and role of heart, gas exchange, respiratory anatomy, lung function, digestive system, kidney structure and function Unit 5. 8 Hrs. 5.1 Body's control mechanism: Nerve impulse, synapse, CNS organization, endocrine system, sensory input and output coordination
  • 14. 5.2 Immune system: Defense mechanism, humeral and cell mediated immune responses, vaccines and monoclonal antibody. Laboratory Works: 1. Identification of biomolecules: cellulose, Lignin, Lipid, Protein. 2. Analysis of amino acids in protein by paper chromatography and paper electrophoresis. 3. Separation of photo synthetic pigments by paper chromatography. 4. Determination of value of RQ of different respiratory substrates. 5. Study of different types of plant and anima cells in temporary preparation. Text Books: E.D. Enger & F.C. Ross, Concepts in Biology, 9th Edition, Tata McGraw Hill Reference Book: P.H. Reven et.al, Biology, 5th Ed. WBC McGraw Hill.
  • 15. Course Title: Geology I Course no: GEO-107 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: Fundamental concepts of contemporary earth and environmental science and engineering with increasing computer application. Goal: This course aims at providing general understanding of Earth and environmental science and engineering Course Contents: Unit 1. 10 Hrs. 1.1 New Global Tectonic framework of the earth: Continental margins, earthquakes, volcanoes and mountain ranges. 1.2 Crystal, minerals and rocks: rock types and rock systematic Unit 2. 10 Hrs. 2.1 Mineral deposits and mineral mining: technologies, reserves, economics and environment 2.2 Engineering geology: construction and stability of structures and natural and artificial face stability Unit 3. 10 Hrs. 3.1 Climate changes and natural disasters: Landslides, Floods and Desertification. 3.2 Natural resources depletion: Hydrocarbons, metals and new sources of energy and materials. Unit 4. 10 Hrs. 4.1 Geographic Information system (GIS): Vectors and raster and remote sensing database management. 4.2 Computer aided data management: remote sensing data acquisition, storage, processing and interpretation. 4.3 GIS and RS packages: ERDAS, ER Mapper, ArcView and other operating systems and capabilities Laboratory works: Mineral / Rock identification, Soil types, Reserve calculation, Slope stability calculation, Rock Mass Ratings, ER Mapper, ArcView, ILWIS tour, RS data analysis, Digitization, practice and Geographic locking, GIS Layers shows and illustrations, GIS assignment with digital RS data.
  • 16. Practical: • To identify elements of symmetry of a cube. • To identify 5 oxides and 5 sulphide minerals. • To calculate reserve of a ore deposit. • To calculate cost - benefit analysis of a mining enterprise • To calculate the stability of natural slope • To calculate and interpret precipitation data • To calculate rock mass rating form data • To perform digitization and geographic locking in computer • GIS assignment with RS data. Text Books: No specific text book covering all materials but a working manual could be easily prepared. Reference: Homework: Homework assignments covering lecture materials and primary numerical exercises. Assignments: Given throughout the semester. Computer Usage: MS-WINDOWS (WINDOWS 98/XP) base PC of workstation Prerequisites: Basic IT literacy Category contents: Science Aspect: 50% Engineering Aspect: 50%
  • 17. Course Title: Statistics I Course no: STA-108 Full Marks: 70+10+20 Credit hours: 3 Pass Marks: 28+4+8 Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.) Course Synopsis: Concept of Applied Statistical Techniques and its Applications Goal: This course makes students able to understand Applied Statistical Techniques and their applications in the allied areas. Course Contents: Unit 1: Sampling Techniques 10 Hrs. Types of Sampling; Simple Random Sampling with and without Replacement; Stratified Random Sampling; Ratio and Regression Method of Estimation under Simple and Stratified Random Sampling; Systematic Sampling; Multistage Sampling; Estimation of population total and its Variance. Unit 2: Non Parametric Test 16 Hrs. Chi-square test: Test of goodness of fit; Test for independence (Categorical Data). Definition of Order Statistics; Run Test; Sign Test; Wilcoxon Matched Pairs Signed Ranks Test; Mann-Whitney U Test; Median Test; Kolmogorov Smirnov Test (One Sample Case); Cochran Q Test; Kruskl Wallis One way ANOVA Test; Friedman Two way ANOVA Test. Unit 3: Correlation and Regression Analysis 19 Hrs. Partial and Multiple Correlations; Multiple Linear Regressions: Assumptions; Coefficient Estimation, and Significance Test; Coefficient of Determination; Cobb- Dauglas Production Function; Growth Model; Logistic Regression; Autoregressive Model of order One, and Appraisal of Linear Models (Heteroscedasticity, Multicolinearity, Autocorrelation). Note: 1. Theory and practice should go side by side. 2. It is recommended 45 hours for lectures and 15 additional hours for tutorial class for completion of the course in the semester. 3. SPSS Software should be used for data analysis. 4. Home works and assignments covering the lecture materials will be given throughout the semester.
  • 18. Text Books: • Draper, N. and H. Smith, Applied Regression Analysis, 2nd edition, New York: John Wiley & Sons, 1981. • Hogg & Tanis, Probability & Statistical Inference, 6th edition, First Indian Reprint, 2002. • Gujaratii, D. Basic Econometrics, International edition, 1995. • Gibbons, J.D. Nonparametric Statistical Inference. International Student Edition. • Siegel, S. Nonparametric Statistics for the Behavioural Sciences. McGraw- Hill, New York. References: • Hollander, M. & Wolfe, Nonparametric Statistical Methods. Johns Wiley & Sons, New York.