Freshman Year / First Semester

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books: Alexis Leon, Mathew Leon, Fundamentals of Information Technology, Leon Tech World

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 computers systems, Anatomy of a digital Computer, Computer Architecture, Memory system, Memory Units, Auxiliary Storage devices, Input 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 Telecommunication, 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 Warehouse and Data Marts, Data Mining, Geographical Information System.

Unit 6. Application 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.

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books:
1. Byron Gottfried: “Programming with C”, Second Edition, McGraw Hill Education.
2. Herbert Schildt, C The Complete Reference, Fourth Edition, Osborne/McGraw- Hill Publication.

Reference Books:
1. Paul Deitel, Harvey Deitel, C: How to Program, Eighth Edition, Pearson Publication.
2. Al Kelley, Ira Pohl: “A Book on C”, Fourth Edition, Pearson Education.
3. Brian W. Keringhan, Dennis M. Ritchiem, The C programming Language, Second Edition, PHI Publication.
4. Ajay Mittal, Programming in C: A Practical Approach, Pearson Publication.
5. Stephen G. Kochan, Programming in C, CBS publishers & distributors.
6. E. Balagurusamy, Programming in ANSI C, Third Edition, TMH publishing.

Course Synopsis: This course covers the concepts of structured programming using C programming language.

Goal: This course is designed to familiarize students with 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 Standards( ANSI C and C99), C Character Set, C Tokens, Escape sequence, Delimiters, Variables, Data types (Basic, Derived, and User Defined), Structure of a C program, Executing a C program, Constants/ Literals, Expressions, Statements, and Comments.

Unit 3: Input and Output (2 Hrs.)
Conversion specification, Reading a character, Writing a character, I/O operations, 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, Conditional operator, Special Operators(sizeof and comma), Evaluation of Expression, Operator Precedence and Associativity.

Unit 5: Control Statement (4 Hrs.)
Conditional Statements, Decision Making and Branching, Decision Making and Looping, Exit function, Break and Continue.

Unit 6: Arrays (6 Hrs.)
Introduction to Array, Types of Array (Single Dimensional and Multidimensional), Declaration and Memory Representation of Array, Initialization of array, Character Array and Strings, Reading and Writing Strings, Null Character, String Library Functions( string length, string copy, string concatenation, string compare)

Unit 7: Functions (5 Hrs.)
Library Functions, User-defined functions, Function prototype, Function call, and Function Definition, Nested and Recursive Function, Function Arguments and Return Types, Passing, Arrays to Function, Passing Strings to Function, Passing Arguments by Value, Passing Arguments by Address, Scope visibility and lifetime of a variable, Local and Global Variable.

Unit 8: 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 9: Pointers (6 Hrs.)
Introduction, The & and * operator, Declaration of pointer, Chain of Pointers, Pointer Arithmetic, Pointers and Arrays, Pointers and Character Strings, Array of Pointers, Pointers as Function Arguments, Function Returning pointers, Pointers and Structures, Dynamic Memory Allocation

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 output operations, perform character input and output operations.
  • Perform logical operations, create decision making programs, create loops to repeat task.
  • Create user-defined functions, 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.

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books:
1. Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists, 3rd Edition, India: Academic Press, 2005.

Reference Books:
1. Richard A. Johnson, Miller and Freund’s probability and Statistics for Engineers
2. 6th Edition, Indian reprint: Pearson Education, 2001, Ronald E. Walpole, R.H. Myers, S.L. Myers, and K. Ye
3. Probability and Statistics for Engineers and Scientists, 7th Edition, Indian reprint: Pearson Education, 2005.

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

Note:This course requires a lot of programming practices. Each topic must be followed by a practical session. Some practical sessions include programming to:

  • 1Theory 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.

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books:
homas 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.

Reference Books:
1. E.W. Swokowski, Calculus with Analytical Geometry, Second Alter Edition. Sneddan Ian- Elements of Partial Differential Equations.

Course Synopsis: Preliminaries revision of differentiation and integration; Techniques of integration infinite series; Vectors and analytical geometry in space (differential geometry). Vector valued functions. Multi variable 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
2.4 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 center 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.


Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books:
1. Michael Baron (2013). Probability and Statistics for Computer Scientists. 2nd Ed., CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
2. Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, & Keying Ye (2012). Probability & Statistics for Engineers & Scientists. 9th Ed., Printice Hall

Reference Books: 1. Douglas C. Montgomery & George C. Ranger (2003). Applied Statistics and Probability for Engineers. 3rd Ed., John Willey and Sons, Inc.

2. Richard A. Johnson (2001). Probability and Statistics for Engineers. 6th Ed., Pearson Education, India

Course Synopsis: This course contains basics of statistics, descriptive statistics, probability, sampling, random variables and mathematical expectations, probability distribution, correlation and regression.

Goal: The main objective of this course is to impart the knowledge of descriptive statistics, correlation, regression, sampling, theoretical as well as applied knowledge of probability and some probability distributions.

Course Contents:

Unit 1: Introduction (4 Hrs.)
Basic concept of statistics; Application of Statistics in the field of Computer Science & Information technology; Scales of measurement; Variables; Types of Data; Notion of a statistical population

Unit 2: Descriptive Statistics (6 Hrs.)
Measures of central tendency; Measures of dispersion; Measures of skewness; Measures of kurtosis; Moments; Steam and leaf display; five number summary; box plot Problems and illustrative examples related to computer Science and IT

Unit 3: Introduction to Probability (8 Hrs.)
Concepts of probability; Definitions of probability; Laws of probability; Bayes theorem; prior and posterior probabilities Problems and illustrative examples related to computer Science and IT

Unit 4: Sampling (3 Hrs.)
Definitions of population; sample survey vs. census survey; sampling error and non-sampling error; Types of sampling

Unit 5: Random Variables and Mathematical Expectation (5 Hrs.)
Concept of a random variable; Types of random variables; Probability distribution of a random variable; Mathematical expectation of a random variable; Addition and multiplicative theorems of expectation
Problems and illustrative examples related to computer Science and IT

Unit 6: Probability Distributions (12 Hrs.)
Probability distribution function, Joint probability distribution of two random variables; Discrete distributions: Bernoulli trial, Binomial and Poisson distributions; Continuous distribution: Normal distributions; Standardization of normal distribution; Normal distribution as an approximation of Binomial and Poisson distribution; Exponential, Gamma distribution Problems and illustrative examples related to computer Science and IT

Unit 7: Correlation and Linear Regression (7 Hrs.)
Bivariate data; Bivariate frequency distribution; Correlation between two variables; Karl Pearson’s coefficient of correlation(r); Spearman’s rank correlation; Regression Analysis: Fitting of lines of regression by the least squares method; coefficient of determination Problems and illustrative examples related to computer Science and IT

Laboratory Works:
The laboratory work includes using any statistical software such as Microsoft Excel, SPSS, STATA etc. whichever convenient using Practical problems to be covered in the Computerized Statistics laboratory

Freshman Year / Second Semester

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Text Books:
1. M. Morris Mano, “Digital Logic & Computer Design”

Reference Books:
1. Brain Holdsworth, “Digital Logic Design”, Elsevier Science.
2. John Patrick Hayes, “Introduction to Digital Logic Design”, Addison-Wesley.
3. M. Morris Mano and Charles Kime, “Logic and Computer Design Fundamentals”, Pearson New International.

Course Synopsis: This course covers the concepts of digital logic and switching networks. The course includes the fundamental concepts of boolean algebra and its application for circuit analysis, multilevel gates networks, flip-flops, counters logic devices and synchronous and asynchronous sequential logic and digital integrated circuits.

Goal: The main objective of this course is to introduce the basic tools for the design of digital circuits and introducing methods and procedures suitable for a variety of digital design applications.

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: Boolean algebra and Logic Gates (5 Hrs.)
Basic and Axiomatic definitions of Boolean algebra, Basic Theorems and properties of Boolean Algebra, Boolean Functions, Logic Operations, Logic Gates, Integrated Circuits

Unit 3: Simplification of Boolean Functions (5 Hrs.)
K-map, Two and Three variable maps, Four variable maps, product of sum simplification, NAND and NOR implementation, Don’t Care conditions, Determinant and selection of Prime Implicants

Unit 4: Combinational Logic (5 Hrs.)
Design Procedure, Adders, Subtractors, Code Conversions, Analysis Procedure, Multilevel NAND and NOR Circuits, Exclusive-OR Circuits

Unit 5: Combinational Logic with MSI and LSI (8 Hrs.)
Binary Parallel Adder and Subtractor, Decimal Adder, Magnitude Comparator, Decoders and Encoders, Multiplexers, Read-only-Memory (ROM), Programmable Logic Array (PLA), Programmable Array Logic (PAL)

Unit 6: Synchronous and Asynchronous Sequential Logic (10 Hrs.)
Flip-Flops, Triggering of flip-flops, Analysis of clocked sequential circuits, Design with state equations and state reduction table, Introduction to Asynchronous circuits, Circuits with latches.

Unit 7: Registers and Counters (6 Hrs.)
Library Functions, User-defined functions, Function prototype, Function call, and Function Definition, Nested and Recursive Function, Function Arguments and Return Types, Passing, Arrays to Function, Passing Strings to Function, Passing Arguments by Value, Passing Arguments by Address, Scope visibility and lifetime of a variable, Local and Global Variable.

Unit 8: Structure and Union (5 Hrs.)
Registers, Shift registers, Ripple Counters, Synchronous Counters, Timing Sequences, The memory

Laboratory works: Students should be able to realize following digital logic circuits as a part of laboratory work.

  • Familiarizations with logic gates
  • Combinatorial Circuits
  • Code Converters
  • Design with Multiplexers
  • Adders and Subtractors
  • Flip-Flops
  • Sequential Circuits
  • Counters
  • Clock Pulse Generator

Nature of Course: Theory (3 Hrs)

Text Books:
1. Kenneth H. Rosen, Discrete mathematics and its applications, Seventh Edition McGraw Hill Publication, 2012.
2. Bernard Kolman, Robert Busby, Sharon C. Ross, Discrete Mathematical Structures, Sixth Edition Pearson Publications, 2015
3. Joe L Mott, Abraham Kandel, Theodore P Baker, Discrete Mathematics for Computer Scientists and Mathematicians, Printice Hall of India, Second Edition, 2008

Reference Books:
1. Ken Bogart, Scot Drysdale, Cliff Stein, Discrete Mathematics for Computer Scientists, First Edition Addison-Wesley, 2010

Course Synopsis: The course covers fundamental concepts of discrete structure like introduce logic, proofs, sets, relations, functions, counting, and probability, with an emphasis on applications in computer science.

Goal: After completing this course, the largest student will gain knowledge in discrete mathematics and finite state automata in an algorithmic approach. It helps the target student in gaining fundamental and conceptual clarity in the area of logic, Reasoning, Algorithms, Recurrence Relation and Graph Theory.

Course Contents:

Unit 1: Basic Discrete Structures (7 Hrs.)
1.1 Sets: Sets and Subsets, Power Set, Cartesian Product, Set Operations, Venn Diagram, Inclusion-Exclusion Principle, Computer Representation of Sets

1.2 Functions: Basic Concept, Injective and Bijective Functions, Inverse and Composite Functions, Graph of Functions, Functions for Computer Science (Ceiling Function, Floor Function, Boolean Function, Exponential Function), Fuzzy Sets and Membership Functions, Fuzzy Set Operations

1.3 Sequences and Summations: Basic Concept of Sequences, Geometric and Arithmetic Progression, Single and Double Summation

Unit 2: Integers and Matrices (6 Hrs.)
2.1. Integers: Integers and Division, Primes and Greatest Common Divisor, Extended Euclidean Algorithm, Integers and Algorithms, Applications of Number Theory (Linear Congruencies, Chinese Remainder Theorem, Computer Arithmetic with Large Integers)

2.2. Matrices: Zero-One Matrices, Boolean Matrix Operations

Unit 3: Logic and Proof Methods (6 Hrs.)
3.1. Logic: Propositional Logic, Propositional Equivalences, Predicates and Quantifiers, Negation of Quantified Statements, Proof of quantified statements, Nested Quantifiers, Rules of Inferences

3.2. Proof Methods: Basic Terminologies, Proof Methods (Direct Proof, Indirect Proof, Proof by Contradiction, Proof By Contraposition, Exhaustive Proofs and Proof by Cases), Mistakes in Proof

Unit 4: Induction and Recursion (5 Hrs.)
4.1. Induction: mathematical Induction, Strong Induction and Well-Ordering, Induction in General

4.2. Recursive Definitions and Structural Induction, Recursive Algorithms, Proving Correctness of Recursive Algorithms

Unit 5: Counting and Discrete Probability (9 Hrs.)
5.1. Counting: Basics of Counting, Pigeonhole Principle, Permutations and Combinations, Two Element Subsets, Counting Subsets of a Set, Binomial Coefficients, Generalized Permutations and Combinations, Generating Permutations and Combinations

5.2. Discrete Probability: Introduction to Discrete Probability, Probability Theory, Probability Calculation in Hashing, Expected Value and Variance, Randomized Algorithms

5.3. Advanced Counting: Recurrence Relations, Solving Recurrence Relations (Homogeneous and Non-Homogeneous equations), Introduction to Divide and Conquer Recurrence Relations

Unit 6: Relations and Graphs (12 Hrs.)
6.1. Relations: Relations and their Properties, N-ary Relations with Applications, Representing Relations, Closure of Relations, Equivalence Relations, Partial Ordering

6.2. Graphs: Graphs Basics, Graph Types, Graph Models, Graph Representation, Graph Isomorphism, Connectivity in Graphs, Euler and Hamiltonian Path and Circuits, Matching Theory, Shortest Path Algorithm (Dijkstra’s Algorithm), Travelling Salesman Problem, Graph Coloring

6.3. Trees: Introduction and Applications, Tree Traversals, Spanning Trees, Minimum Spanning Trees (Kruskal’s Algorithm)

6.4. Network Flows: Graph as Models of Flow of Commodities, Flows, Maximal Flows and Minimal Cuts, The Max Flow-Min Cut Theorem

Laboratory Works:
The laboratory work consists of implementing the algorithms and concepts discussed in the class. Student should implement problems with following concepts;

  • Set Operations and Boolean Matrix Operations
  • Primility Testing, Number Theory Algorithms, and Operations on Integers
  • Counting and Some Recursive Algorithms
  • Algorithms for Relations, Graphs

Nature of Course: Theory (3 Hrs)+ Lab (3 Hrs)

Text Books:
1. Ramesh S. Gaonkar, Microprocessor Architecture, Programming, and Applications with 8085, Prentice Hall

Reference Books:
1. A.P.Malvino and J.A.Brown, Digital Computer Electronics, 3rd Edition, Tata McGraw Hill D.V.Hall, Microprocessors and Interfacingv – Programming and Hardware, McGraw Hill

2. 8000 to 8085 Introduction to 8085 Microprocessor for Engineers and Scientists, A.K.Gosh, Prentice Hall

Course Synopsis: This course contains fundamental concepts of computer organization, basic I/O interfaces and Interrupts operations.

Goal: The course objective is to introduce the operation, programming, and application of microprocessor

Course Contents:

Unit1: Introduction (4 Hrs.)
Introduction to Microprocessor, Components of a Microprocessor: Registers, ALU and control & timing, System bus (data, address and control bus), Microprocessor systems with bus organization

Unit 2: Basic Architecture (7 Hrs.)
Microprocessor Architecture and Operations, Memory, I/O devices, Memory and I/O operations, 8085 Microprocessor Architecture, Address, Data And Control Buses, 8085 Pin Functions, Demultiplexing of Buses, Generation Of Control Signals

Unit 3: Instruction Cycle (3 Hrs.)
Fetch Operation and Timing Diagram; Execute Operation and Timing Diagram, Instruction Cycle, Machine Cycle, T-States, T-States, Memory Interfacing

Unit 4: Assembly Language Programming (10 Hrs.)
Assembly instruction format, Instruction Types, Mnemonics, Operands, Macro assemblers, Linking, Assembler directives, Addressing Modes, Simple sequence programs, Flags, Branch, Jumps, While-Do, Repeat-Until, If-Then-Else and Multiple If-then Programs, Debugging

Unit 5: Basic I/O, Memory R/W and Interrupt Operations (6 Hrs.)
Memory Read, Memory Write, I/O Read, I/O Write, Direct Memory Access, Interrupt, Types, Interrupt Masking

Unit 6: Input/ Output Interfaces (6 Hrs.)
Interfacing Concepts, Ports, Interfacing Of I/O Devices, Interrupts In 8085, Programmable Interrupt Controller 8259A, Programmable Peripheral Interface 8255A

Unit 7: Advanced Microprocessors (9 Hrs.)
8086: logical block diagram and segments, 80286: Architecture, Registers, (Real/Protected mode), Privilege levels, descriptor cache, Memory access in GDT and LDT, multitasking, addressing modes, flag register 80386: Architecture, Register organization, Memory access in protected mode, Paging

Laboratory Works:
The laboratory work includes Assembly language programming using 8085/8086/8088 trainer kit. The programming should include: Arithmetic operation, base conversion, conditional branching etc. The lab work list may include following concepts:

  • Assembly language program using 8085 microprocessor kit.
  • Use of all types of instructions and addressing modes.
  • Arrays and the concept of Multiplications and Division operations on Microprocessor.
  • Assembly language programming, using any types of Assembler, including the different functions of Int 10h, and 12h

Nature of Course: Theory (3 Hrs)

Text Books:
1. Y Langsam, MJ Augenstein and A.M, Tanenbaum Data Structures using C and C++, Prentice Hall India, Second Edition 2015

Reference Books: 1. Leen Ammeral, Programmes and Data Structures in C, Wiley Professional Computing
2. G.W Rowe, Introduction to Data Structure and Algroithms with C and C++, Prentice Hall India
3. R.L Kruse, B.P. Leung, C.L. Tondo, Data Structure and Program Design in C Prentice-Hall India

Course Synopsis: This course includes the basic foundations in of data structures and algorithms. This course covers concepts of various data structures like stack, queue, list, tree and graph. Additionally, the course includes idea of sorting and searching.


  • To introduce data abstraction and data representation in memory
  • To describe, design and use of elementary data structures such as stack, queue, linked list, tree and graph
  • To discuss decomposition of complex programming problems into manageable sub-problems
  • To introduce algorithms and their complexity

Course Contents:

Unit 1: Introduction to Data Structures & Algorithms (4 Hrs.)
Data types, Data structure and Abstract date type, Dynamic memory allocation in C, Introduction to Algorithms, Asymptotic notations and common functions

Unit 2: Stack (4 Hrs.)
Basic Concept of Stack, Stack as an ADT, Stack Operations, Stack Applications, Conversion from infix to postfix/prefix expression, Evaluation of postfix/ prefix expressions

Unit 3: Queue (4 Hrs.)
Basic Concept of Queue, Queue as an ADT, Primitive Operations in Queue, Linear Queue, Circular Queue, Priority Queue, Queue Applications

Unit 4: Recursion (3 Hrs.)
Principle of Recursion, Comparison between Recursion and Iteration, Tail Recursion, Factorial, Fibonacci Sequence, GCD, Tower of Hanoi(TOH), Applications and Efficiency of Recursion

Unit 5: Lists (8 Hrs.)
Basic Concept, List and ADT, Array Implementation of Lists, Linked List, Types of Linked List: Singly Linked List, Doubly Linked List, Circular Linked List., Basic operations in Linked List: Node Creation, Node Insertion and Deletion from Beginning, End and Specified Position, Stack and Queue as Linked List

Unit 6: Sorting (8 Hrs.)
Introduction and Types of sorting: Internal and External sort, Comparison Sorting Algorithms: Bubble, Selection and Insertion Sort, Shell Sort, Divide and Conquer Sorting: Merge, Quick and Heap Sort, Efficiency of Sorting Algorithms

Unit 7: Searching and Hashing (6 Hrs.)
Introduction to Searching, Search Algorithms: Sequential Search, Binary Search, Efficiency of Search Algorithms, Hashing : Hash Function and Hash Tables, Collision Resolution Techniques

Unit 8: Trees and Graphs (8 Hrs.)
Concept and Definitions, Basic Operations in Binary Tree, Tree Height, Level and Depth, Binary Search Tree, Insertion, Deletion, Traversals, Search in BST, AVL tree and Balancing algorithm, Applications of Treesm, Definition and Representation of Graphs, Graph Traversal, Minimum Spanning Trees: Kruskal and Prims Algorithm, Shortest Path Algorithms: Dijksrtra Algorithm

Laboratory Works:
The laboratory work consists of implementing the algorithms and data structures studied in the course. Student should implement at least following concepts;

  • Dynamic memory allocation and deallocation strategies
  • Stack operations and Queue operations
  • Array and Linked List implementation of List
  • Linked List implementation of Stack and Queues
  • Sorting, Searching and Hashing algorithms
  • Binary Search Trees and AVL Tress
  • Graph Representation, Spanning Tree and Shortest Path Algorithms

Nature of Course: Theory (3 Hrs) + Lab (3 Hrs)

Reference Books:
David c. lay: Linear Algebra and its applications, 3rd edition, Pearson Education

Reference Books:
Kolman, Bernard, Introductory Linear Algebra with Application. 7th edition. Pearson, Gilbert Strang; linear Algebra and its Application. 3rd edition, Kreszig, E. “advanced Engineering Mathematics.” 5th edition, . Wiley

Course Synopsis: Linear equations in linear algebra, matrix algebra, Determinants, Vector spaces, Eigen values and Eigen vectors. Orthogonality and least squares. Symmetric matrices and quadratic forms.

Goal: This course provides students with the knowledge of fundamental linear algebra and the theory of matrices. On completion of this course the student will master the basic concepts and acquires skills in solving problems in linearbalgebra.

Course Contents:

Unit 1: Linear equations in linear Algebra (10 Hrs)
1.1 Systems of linear equations
1.2 Row reduction and Echelon Forms
1.3 Vector equations
1.4 The matrix equations Ax = b
1.5 Solution sets of linear systems
1.6 Linear independence
1.7 Introduction Liner Transformation
1.8 The matrix of the Linear Transformation

Unit 2: Matrix Algebra (8 Hrs)
2.1 Matrix operations
2.2 The inverse of matrix
2.3 Characterization of invertible matrices
2.4 Partitioned Matrices
2.5 The Leontief Input- output models
2.6 Application to Computer graphics

Unit 3: Determinants (4 Hrs)
3.1 Introduction of determinants
3.2 Properties of determinants
3.3 Cramer’s rule value and linear transformations

Unit 4: Vector spaces (8 Hrs)
4.1 Vector spaces and sub polar
4.2 Null spaces, Column spaces and linear transformation
4.3 Linearly Independent sets; Bases
4.4 Coordinate system
4.5 The dimension of a vector space
4.6 Rank
4.7 Change of basis

Unit 5: Eigen values and Eigen vectors (7 Hrs)
5.1 Eigen vectors and Eigen values
5.2 The characteristics equations
5.3 Diagonolization
5.4 Eigen vectors and Linear Transformation
5.5 complex Eigen values
5.6 Discrete Dynamical values

Unit 6: Orthogonality and Least squares (8 Hrs)
6.1 Linear products, length and Orthogonality
6.2 Orthogonal sets
6.3 orthogonal Projections
6.4. The Gram- Schmidt process
6.5 Least square problems
6.6 Applications to Linear models

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