Sharon Gerson and Steven Gerson. Technical Writing: Process and Product (8th Edition), London: Longman, 2013
Rentz, Kathryn, Marie E. Flatley& Paula Lentz. Lesikar’s Business Communication Connecting in a Digital world, McGraw-Hill, Irwin.2012
Allan & Barbara Pease. The Definitive Book of Body Language,New York, Bantam,2004
Jones, Daniel. The Pronunciation of English, New Delhi, Universal Book Stall.2010
Sharma, Sangeeta& Mishra, Binod. Communication Skills for Engineers and Scientists, New Delhi: PHI Learning, 2009, rpt 2012
Probability spaces, conditional probability, independence; Discrete random variables, Independent random variables, the multinomial distribution, Poisson approximation to the binomial distribution, infinite sequences of Bernoulli trials, sums of independent random variables; Expectation of Discrete Random Variables, Moments, Variance of a sum, Correlation coefficient, Chebyshev's Inequality.
Continuous random varibales and their properties, distribution functions and densities, normal, exponential and gamma densities.
Bivariate distributions and their properties, distribution of sums and quotients, conditional densities, Bayes' rule.
Measures of Central tendency: Moments, skewness and Kurtosis - Probability distributions: Binomial, Poisson and Normal - evaluation of statistical parameters for these three distributions, Correlation and regression – Rank correlation.
Curve fitting by the method of least squares- fitting of straight lines, second degree parabolas and more general curves. Test of significance: Large sample test for single proportion, difference of proportions, single mean, difference of means, and difference of standard deviations.
Test for single mean, difference of means and correlation coefficients, test for ratio of variances
Chi-square test for goodness of fit and independence of attributes.
Erwin Kreyszig, Advanced Engineering Mathematics, 9th Edition, John Wiley & Sons, 2006.
P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book Stall, 2003 (Reprint).
S. Ross, A First Course in Probability, 6th Ed., Pearson Education India, 2002.
W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd
Ed., Wiley, 1968.
N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi Publications, Reprint, 2010.
B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000.
Veerarajan T., Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi, 2010.
Introduction to Data Structure: Concepts of Data and Information, Classification of Data structures, Abstract Data Types, Implementation aspects: Memory representation. Data structures operations and its cost estimation. Introduction to linear data structures- Arrays, Linked List: Representation of linked list in memory, different implementation of linked list. Circular linked list, doubly linked list, etc. Application of linked list: polynomial manipulation using linked list, etc.
Stacks and Queue: Stacks as ADT, Different implementation of stack, multiple stacks. Application of Stack: Conversion of infix to postfix notation using stack, evaluation of postfix expression, Recursion. Queues: Queues as ADT, Different implementation of queue, Circular queue, Concept of Dqueue and Priority Queue, Queue simulation, Application of queues.
Tree: Definitions - Height, depth, order, degree etc. Binary Search Tree - Operations, Traversal, Search. AVL Tree, Heap, Applications and comparison of various types of tree; Introduction to forest, multi-way Tree, B tree, B+ tree, B* tree and red-black tree.
Graphs: Introduction, Classification of graph: Directed and Undirected graphs, etc, Representation, Graph Traversal: Depth First Search (DFS), Breadth First Search (BFS), Graph algorithm: Minimum Spanning Tree (MST)-Kruskal, Prim’s algorithms. Dijkstra’s shortest path algorithm; Comparison between different graph algorithms. Application of graphs.
Sorting: Introduction, Sort methods like: Bubble Sort, Quick sort. Selection sort, Heap sort, Insertion sort, Shell sort, Merge sort and Radix sort; comparison of various sorting techniques. Searching: Basic Search Techniques: Sequential search, Binary search, Comparison of search methods. Hashing & Indexing. Case Study: Application of various data structures in operating system, DBMS etc.
AM Tanenbaum, Y Langsam& MJ Augustein, “Data structure using C and C++”, Prentice Hall India.
Robert Kruse, Bruse Leung, “Data structures & Program Design in C”, Pearson Education.
Aho, Hopcroft, Ullman, “Data Structures and Algorithms”, Pearson Education.
N. Wirth, “Algorithms + Data Structure = Programs”, Prentice Hall.
Jean – Paul Trembly , Paul Sorenson, “An Introduction to Data Structure with application”, TMH.
Richard, GilbergBehrouz, Forouzan ,“Data structure – A Pseudocode Approach with C”, Thomson press.
Fundamental of Artificial Intelligence, history, motivation and need of AI, Production systems, Characteristics of production systems , goals and contribution of AI to modern technology, search space, different search techniques: hill Climbing, Best first Search, heuristic search algorithm, A* and AO* search techniques etc.
Knowledge Representation, Problems in representing knowledge, knowledge representation using propositional and predicate logic, comparison of propositional and predicate logic, Resolution, refutation, deduction, theorem proving, inferencing, monotonic and non-monotonic reasoning.
Probabilistic reasoning, Baye's theorem, semantic networks, scripts, schemas, frames, conceptual dependency, forward and backward reasoning.
Game playing techniques like minimax procedure, alpha-beta cut-offs etc, planning, Study of the block world problem in robotics, Introduction to understanding, natural language processing (NLP), Components of NLP, application of NLP to design expert systems.
Expert systems (ES) and its Characteristics, requirements of ES, components and capability of expert systems, Inference Engine Forward & backward Chaining, Expert Systems Limitation, Expert System Development Environment, technology, Benefits of Expert Systems.
TEXT BOOKS:
Russel,S., and Norvig,P., “Artificial Intelligence: A Modern Approach”, 4th Edition, 2020, Pearson.
Elaine Rich, Kevin Knight,Shivashankar B. Nair, “Artificial Intelligence”, McGraw-Hill International.
Nils J. Nilsson, “Artificial Intelligence: A New Synthesis”, Morgan-Kauffman.
REFERENCE BOOKS:
Janakiraman, K.Sarukesi, ‘Foundations of Artificial Intelligence and Expert Systems’, Macmillan Series in Computer Science.
W. Patterson, ‘Introduction to Artificial Intelligence and Expert Systems’, Prentice Hall of India.
Introduction to Object Oriented Thinking & Object Oriented Programming: Comparison with Procedural Programming, features of Object oriented paradigm– Merits and demerits of OO methodology; Object model; Elements of OOPS, IO processing, Data Type, Type Conversion, Control Statement, Loops, Arrays.
Encapsulation and Data Abstraction- Concept of Objects: State, Behavior & Identity of an object; Classes: identifying classes and candidates for Classes Attributes and Services, Access modifiers, Static members of a Class, Instances, Message passing, and Construction and destruction of Objects.
Relationships – Inheritance: purpose and its types, ‘is a’ relationship; Association, Aggregation. Concept of interfaces and Abstract classes.
Polymorphism: Introduction, Method Overriding & Overloading, static and run time Polymorphism. Virtual Function, friend function, Static function, friend class.
Strings, Exceptional handling, Introduction of Multi-threading and Data collections. Case study like: ATM, Library management system.
Timothy Budd, “An Introduction to Object-Oriented Programming”, AddisonWesley Publication, 3rd Edition.
Cay S. Horstmann and Gary Cornell, “Core Java: Volume I, Fundamentals”, Prentice Hall publication.
G. Booch, “Object Oriented Analysis& Design”, Addison Wesley.
James Martin, “Principles of Object Oriented Analysis and Design”, Prentice Hall/PTR.
Peter Coad and Edward Yourdon, “Object Oriented Design”, Prentice Hall/PTR.
Herbert Schildt, “Java 2: The Complete Reference”, McGraw-Hill Osborne Media.
To write a Python program to find GCD of two numbers.
To write a Python Program to find the square root of a number by Newton’s Method.
To write a Python program to find the exponentiation of a number.
To write a Python Program to find the maximum from a list of numbers.
To write a Python Program to perform Linear Search
To write a Python Program to perform binary search.
To write a Python Program to perform selection sort.
To write a Python Program to perform insertion sort.
To write a Python Program to perform Merge sort.
To write a Python program to find first n prime numbers.
To write a Python program to multiply matrices.
To write a Python program for command line arguments.
To write a Python program to find the most frequent words in a text read from a file.
To write a Python program to simulate elliptical orbits in Pygame.
To write a Python program to bouncing ball in Pygame.
Sharon Gerson and Steven Gerson. Technical Writing: Process and Product (8th Edition), London: Longman, 2013
Rentz, Kathryn, Marie E. Flatley& Paula Lentz. Lesikar’s Business Communication Connecting in a Digital world, McGraw-Hill, Irwin.2012
Allan & Barbara Pease. The Definitive Book of Body Language,New York, Bantam,2004
Jones, Daniel. The Pronunciation of English, New Delhi, Universal Book Stall.2010
Sharma, Sangeeta& Mishra, Binod. Communication Skills for Engineers and Scientists, New Delhi: PHI Learning, 2009, rpt 2012
Probability spaces, conditional probability, independence; Discrete random variables, Independent random variables, the multinomial distribution, Poisson approximation to the binomial distribution, infinite sequences of Bernoulli trials, sums of independent random variables; Expectation of Discrete Random Variables, Moments, Variance of a sum, Correlation coefficient, Chebyshev's Inequality.
Continuous random varibales and their properties, distribution functions and densities, normal, exponential and gamma densities.
Bivariate distributions and their properties, distribution of sums and quotients, conditional densities, Bayes' rule.
Measures of Central tendency: Moments, skewness and Kurtosis - Probability distributions: Binomial, Poisson and Normal - evaluation of statistical parameters for these three distributions, Correlation and regression – Rank correlation.
Curve fitting by the method of least squares- fitting of straight lines, second degree parabolas and more general curves. Test of significance: Large sample test for single proportion, difference of proportions, single mean, difference of means, and difference of standard deviations.
Test for single mean, difference of means and correlation coefficients, test for ratio of variances
Chi-square test for goodness of fit and independence of attributes.
Erwin Kreyszig, Advanced Engineering Mathematics, 9th Edition, John Wiley & Sons, 2006.
P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book Stall, 2003 (Reprint).
S. Ross, A First Course in Probability, 6th Ed., Pearson Education India, 2002.
W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd
Ed., Wiley, 1968.
N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi Publications, Reprint, 2010.
B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000.
Veerarajan T., Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi, 2010.
Introduction to Data Structure: Concepts of Data and Information, Classification of Data structures, Abstract Data Types, Implementation aspects: Memory representation. Data structures operations and its cost estimation. Introduction to linear data structures- Arrays, Linked List: Representation of linked list in memory, different implementation of linked list. Circular linked list, doubly linked list, etc. Application of linked list: polynomial manipulation using linked list, etc.
Stacks and Queue: Stacks as ADT, Different implementation of stack, multiple stacks. Application of Stack: Conversion of infix to postfix notation using stack, evaluation of postfix expression, Recursion. Queues: Queues as ADT, Different implementation of queue, Circular queue, Concept of Dqueue and Priority Queue, Queue simulation, Application of queues.
Tree: Definitions - Height, depth, order, degree etc. Binary Search Tree - Operations, Traversal, Search. AVL Tree, Heap, Applications and comparison of various types of tree; Introduction to forest, multi-way Tree, B tree, B+ tree, B* tree and red-black tree.
Graphs: Introduction, Classification of graph: Directed and Undirected graphs, etc, Representation, Graph Traversal: Depth First Search (DFS), Breadth First Search (BFS), Graph algorithm: Minimum Spanning Tree (MST)-Kruskal, Prim’s algorithms. Dijkstra’s shortest path algorithm; Comparison between different graph algorithms. Application of graphs.
Sorting: Introduction, Sort methods like: Bubble Sort, Quick sort. Selection sort, Heap sort, Insertion sort, Shell sort, Merge sort and Radix sort; comparison of various sorting techniques. Searching: Basic Search Techniques: Sequential search, Binary search, Comparison of search methods. Hashing & Indexing. Case Study: Application of various data structures in operating system, DBMS etc.
AM Tanenbaum, Y Langsam& MJ Augustein, “Data structure using C and C++”, Prentice Hall India.
Robert Kruse, Bruse Leung, “Data structures & Program Design in C”, Pearson Education.
Aho, Hopcroft, Ullman, “Data Structures and Algorithms”, Pearson Education.
N. Wirth, “Algorithms + Data Structure = Programs”, Prentice Hall.
Jean – Paul Trembly , Paul Sorenson, “An Introduction to Data Structure with application”, TMH.
Richard, GilbergBehrouz, Forouzan ,“Data structure – A Pseudocode Approach with C”, Thomson press.
Fundamental of Artificial Intelligence, history, motivation and need of AI, Production systems, Characteristics of production systems , goals and contribution of AI to modern technology, search space, different search techniques: hill Climbing, Best first Search, heuristic search algorithm, A* and AO* search techniques etc.
Knowledge Representation, Problems in representing knowledge, knowledge representation using propositional and predicate logic, comparison of propositional and predicate logic, Resolution, refutation, deduction, theorem proving, inferencing, monotonic and non-monotonic reasoning.
Probabilistic reasoning, Baye's theorem, semantic networks, scripts, schemas, frames, conceptual dependency, forward and backward reasoning.
Game playing techniques like minimax procedure, alpha-beta cut-offs etc, planning, Study of the block world problem in robotics, Introduction to understanding, natural language processing (NLP), Components of NLP, application of NLP to design expert systems.
Expert systems (ES) and its Characteristics, requirements of ES, components and capability of expert systems, Inference Engine Forward & backward Chaining, Expert Systems Limitation, Expert System Development Environment, technology, Benefits of Expert Systems.
TEXT BOOKS:
Russel,S., and Norvig,P., “Artificial Intelligence: A Modern Approach”, 4th Edition, 2020, Pearson.
Elaine Rich, Kevin Knight,Shivashankar B. Nair, “Artificial Intelligence”, McGraw-Hill International.
Nils J. Nilsson, “Artificial Intelligence: A New Synthesis”, Morgan-Kauffman.
REFERENCE BOOKS:
Janakiraman, K.Sarukesi, ‘Foundations of Artificial Intelligence and Expert Systems’, Macmillan Series in Computer Science.
W. Patterson, ‘Introduction to Artificial Intelligence and Expert Systems’, Prentice Hall of India.
Introduction to Object Oriented Thinking & Object Oriented Programming: Comparison with Procedural Programming, features of Object oriented paradigm– Merits and demerits of OO methodology; Object model; Elements of OOPS, IO processing, Data Type, Type Conversion, Control Statement, Loops, Arrays.
Encapsulation and Data Abstraction- Concept of Objects: State, Behavior & Identity of an object; Classes: identifying classes and candidates for Classes Attributes and Services, Access modifiers, Static members of a Class, Instances, Message passing, and Construction and destruction of Objects.
Relationships – Inheritance: purpose and its types, ‘is a’ relationship; Association, Aggregation. Concept of interfaces and Abstract classes.
Polymorphism: Introduction, Method Overriding & Overloading, static and run time Polymorphism. Virtual Function, friend function, Static function, friend class.
Strings, Exceptional handling, Introduction of Multi-threading and Data collections. Case study like: ATM, Library management system.
Timothy Budd, “An Introduction to Object-Oriented Programming”, AddisonWesley Publication, 3rd Edition.
Cay S. Horstmann and Gary Cornell, “Core Java: Volume I, Fundamentals”, Prentice Hall publication.
G. Booch, “Object Oriented Analysis& Design”, Addison Wesley.
James Martin, “Principles of Object Oriented Analysis and Design”, Prentice Hall/PTR.
Peter Coad and Edward Yourdon, “Object Oriented Design”, Prentice Hall/PTR.
Herbert Schildt, “Java 2: The Complete Reference”, McGraw-Hill Osborne Media.
To write a Python program to find GCD of two numbers.
To write a Python Program to find the square root of a number by Newton’s Method.
To write a Python program to find the exponentiation of a number.
To write a Python Program to find the maximum from a list of numbers.
To write a Python Program to perform Linear Search
To write a Python Program to perform binary search.
To write a Python Program to perform selection sort.
To write a Python Program to perform insertion sort.
To write a Python Program to perform Merge sort.
To write a Python program to find first n prime numbers.
To write a Python program to multiply matrices.
To write a Python program for command line arguments.
To write a Python program to find the most frequent words in a text read from a file.
To write a Python program to simulate elliptical orbits in Pygame.
To write a Python program to bouncing ball in Pygame.