Introduction to Information Technology (CSC 101)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Introduction to Information Technology
Course no: CSC-101 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+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
Fundamentals of Computer Programming (CSC-102)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Fundamentals of Computer Programming
Course no: CSC-102 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+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 and files to keep record of students, employees etc
References:
1. Deitel, C.: How to Program, 2/e (With CD), Pearson Education.
2. Al Kelley, Ira Pohl: "A Book on C", Pearson Education.
3. Brian W. Keringhan & Dennis M. Ritchie: "The C programming Language", PHI
4. Bryons S. Gotterfried: "Programming with C," TMH
5. Stephen G. Kochan: "Programming in C", CBS publishers & distributors.
6. Yashavant Kanetkar: "Let us C", BPB Publications
Probability and Statistics (STA-103)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Probability and Statistics
Course no: STA-103 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+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 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 (Z-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:
• Theory and practice should go side by side.
• It is recommended 45 hours for lectures and 15 additional hours for tutorial class for completion of the course in the semester.
• SPSS software should be used for data analysis.
• Students should have intermediate knowledge of Mathematics.
• Home works and assignments covering the lecture materials will be given throughout the semester.
Calculus and Analytical Geometry (MTH 104)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Calculus and Analytical Geometry
Course no: MTH-104 Full Marks: 80+20
Credit hours: 3 P.M: 32+8
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 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:
1. Thomas and Fenns: Calculus and Analytical Geometry, 9th Edition, 2004. (Thomas, Jr. G. B., and Finney, Ross L. Publisher: Pearson Education Pvt. Ltd.
2. Kreyszig, Erwin, Advanced Engineering Mathematics, John- Wiley & Sons (1991). 5th Edition.
References
1. E.W. Swokowski, Calculus with Analytical Geometry, Second Alter Edition.
2. Sneddan Ian- Elements of Partial Differential Equations.
Physics II (PHY 156)
Tribhuvan University
Bachelor of Science in Computer Science and Information Technology
Course Title: Physics II
Course no: PHY-156 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis:
a) Basic concepts of probability, entropy, classical and quantum statistics.
b) Simple concepts of quantum mechanics leading to Schrödinger equation and its application to simple cases.
c) Methods of solid state physics - crystal structure, band theory of solids, free electron theory of metals and band theory of semiconductors.
Goal: The course aims at providing fundamental physical concepts needed to understand information processing and related devices.
Course Contents:
Unit 1. Statistical Physics 9 Hrs.
1.1 Macroscopic and microscopic description of a thermodynamic system; ensemble, phase space.
1.2 Thermodynamic probability, fundamental postulates of stat. physics.
1.3 Entropy and probability Bolltzmann theorem, statistical equilibrium
1.4 Maxwell-Boltzmann distribution for ideal gas
1.5 Quantum Statistics:
1.5.1 Bose-Einstein statistics-Photon Gas, Planck's law for Black Body Radiation
1.5.2 Fermi - Dirac statistics- application to electron gas
Unit 2. Modern Physics 23 Hrs.
2.1 Introduction to Quantum mechanics
2.1.1 Wave particle duality, de Broglie's matter Waves, phase-velocity and group velocity
2.1.2 Heisenberg's uncertainty principle.
2.1.3 Basic postulates of q m
- dynamical variable - linear operator
- eigen values of linear hermitian operator
- measurement of a dynamical variable
- Schrödinger equation
- interpretation of wave function
2.1.4 Simple applications of Schrödinger equation
- particle in a box, infinite potential well
- barrier penetration
- square potential well
- linear harmonic oscillator
- hydrogen atom
- rigid rotator
2.2 Band Theory of Solids
2.2.1 Crystalline structure of solids, Bravais lattice miller indices, reciprocal lattice, examples
2.2.2 Band theory of solids: origin of Bands
2.2.3 Classification of solid conductor, insulator and semi conductors
2.2.4 Free electron theory of metal: Fermi energy, electron energy distribution, thermo ionic emission Schottky effect, contact potential.
Unit 3. Semi Conductors 13 Hrs.
3.1 Band structure of semiconductors, energy gap
3.2 Electrons and holes, electric conduction in semiconductors, effective mass, extrinsic and extrinsic semiconductors
3.3 n-type and p-type semiconductors, carrier concentration, mobility, temperature dependence.
3.4 p-n junction
3.5 Metal semiconductor junction, Schottky junction, Ohmic contact.
Laboratory works:
• To determine inter planer spacing of given crystal by electron diffraction method.
• To determine the band gap of given sample
• To determine the nature of charge carrier of a given simple by hall apparatus
• Study NOT, AND, OR, NAND, NOR, EX-OR, EX-NOR gates
• To study the temperature dependency of a given sample.
• To study the characteristic of simple and zener diode
• To construct and study CE amplifier
• To construct and study CC amplifier
• To construct and study CB amplifier
• To study output input and transfer characteristics of NPN transistor.
Text books:
1. Thermal physics: C. Kittel
2. Modern Physics: Murgeshan
3. Introduction to solid state physics: C. Kittel.
References books:
1. Elementary Solid State Physics - M.A. Omar Addison-Wesley
2. Heat, Thermodynamics and Statistical Physics:- Singhal, Agrawal and Satya Prakash, Pragati Prakashan, Meerut, India
Home work: Several problems every week.
Prerequisites: Calculus based introductory physics and physics I
Biology II (BIO 157)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Biology II
Course no: BIO-157 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Cell Division, DNA structure and function, RNA, transcription and translation process, mutation, gene regulation, recombinant DNA technology.
Goal: The course is aimed at knowing the living organism at the molecular level. It also focused on techniques for gene manipulation by using recombinant DNA technology.
Course Contents:
Unit 1. 5 Hrs.
Cell division: Mitosis, meiosis, mechanism of crossing over, non-disjunction, ell cycle, abnormal cell division, basis of oncology
Unit 2. 9 Hrs.
DNA: Structure of DNA, replication of DNA, Organization of DNA in chromosomes, forms of DNA
Unit 3. 11 Hrs.
3.1 RNA: Overview of gene expression, transcription-synthesis of RNA, process, structure of mRNA
3.2 Protein synthesis: Decoding the message, tRNA, ribosomal rNA, role of ribosome in protein synthesis
3.3 Genetic code: Introduction of genetic code, wooble hypothesis
Unit 4. 6 Hrs.
Mutation and DNA repair: Introduction, types of mutation, reversion, mechanism of DNA repair.
Unit 5. 6 Hrs.
5.1 Gene regulation in prokaryotes: Operon concept, transcriptional control of protein synthesis, post transcriptional gene control
5.2 Eukaryotic gene control: Control of transcription, post transcriptional gene control, splicing.
Unit 6. 8 Hrs.
Recombinant DNA technology; introduction, tools for cloning, vectors and restriction endonucleases, gene cloning and expression, application of recombinant DNA in healthcare and agriculture industry
Laboratory Assignments:
• Observation of stages of mitosis by cytological slide preparation from root tip of onion.
• Observation of stages of meiosis by cytological slide preparation from anthers.
• Preparation of models of DNA, RNA and protein synthesis
• Testing for DNA with Geulgen stain.
• Testing fro DNA and RNA with Methyl Green Pyronin stain.
• Counting of WBC and RBC in human blood.
Text Books:
Biology by Villee, Solomon, Martin, Martion, Gerg, Davis 2nd Edition, Saunders college publishing, USA.
Reference Book:
Concepts in Biology by E.D. Enger & F.C. Ross, 9th Ed. Tata McGraw Hill
Biology by P.H. Reven et.al, 5th Ed. WBC McGraw Hill.
Laboratory Manual: Biology; A functional approach; Student's Manual / By M.B.V.
Roberts and T.J. King (second edition - ELBS / Nelson, 1988)
Statistics I (STA 108)
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Statistics ICourse no: STA-108 Full Marks: 60+20+20
Credit hours: 3 Pass Marks: 24+8+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:
• Theory and practice should go side by side.
• It is recommended 45 hours for lectures and 15 additional hours for tutorial class for completion of the course in the semester.
• SPSS Software should be used for data analysis.
• Home works and assignments covering the lecture materials will be given throughout the semester.
Text Books:
1. Draper, N. and H. Smith, Applied Regression Analysis, 2nd edition, New York: John Wiley & Sons, 1981.
2. Hogg & Tanis, Probability & Statistical Inference, 6th edition, First Indian Reprint, 2002.
3. Gujaratii, D. Basic Econometrics, International edition, 1995.
4. Gibbons, J.D. Nonparametric Statistical Inference. International Student Edition.
5. Siegel, S. Nonparametric Statistics for the Behavioural Sciences. McGraw-Hill, New York.
References:
Hollander, M. & Wolfe, Nonparametric Statistical Methods. Johns Wiley & Sons, New York.
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