Syllabus of B. Tech. III Sem AIDS (RGPV)

Syllabus of B. Tech. III Sem AIDS (RGPV)

  • Syllabus of AD-301 Technical Communication
  • Syllabus of AD-302 Probability and Statistics for Data Science
  • Syllabus of AD-303 Data Structures
  • Syllabus of AD-304 Artificial Intelligence
  • Syllabus of AD-305 Object Oriented Programming & Methodology
  • Syllabus of AD-306 Computer Workshop/Introduction to Python-I

Syllabus of AD-301 (Technical Communication)

Source: (rgpv.ac.in)

UNIT-1 : Technical Communication Skills

  • Understanding the process and scope of Communication
  • Relevance & Importance of Communication in a Globalized world
  • Forms of Communication
  • Role of Unity
  • Brevity and Clarity in various forms of communication.

UNIT-2 : Types of Communication

  • Verbal & Non-verbal Communication
  • Classification of NVC
  • Barriers to Communication
  • Communicating Globally Culture and Communication.
  • Soft Skills: Interpersonal Communication Listening Persuasion Negotiation
  • Communicating bad news/messages
  • communicating in a global world.

UNIT-3 : Writing Skills

  • Traits of Technical Writing
  • Principles of Business Writing
  • Style of Writing
  • Writing Memos Letters
  • Reports and Types of technical reports
  • Characteristics
  • format and structure of technical reports
  • Writing Research Papers.
  • Speaking Skills: Audience-awareness
  • Voice Vocabulary and Paralanguage
  • Group Discussion
  • Combating Nervousness
  • Speaking to one and to one Mock Presentations.

UNIT-4 : Job Interviews

  • Preparing for interviews
  • assessing yourself
  • Drafting Effective Resume
  • Dress decorum and Delivery techniques
  • Techniques of handling interviews
  • Use of Nonverbals during Interviews
  • Handling turbulence during interviews.
  • Group Discussion: Objective Method Focus
  • Content Style and Argumentation skills.
  • Professional Presentations: Individual Presentations.
  • (Audience Awareness Body Language Delivery and Content of Presentation.)

UNIT-5 : Grammar & Linguistic ability: Basics of grammar

  • common error in writing and speaking
  • Study of advanced grammar
  • Vocabulary Pronunciation Etiquette
  • Syllables Vowel sounds Consonant sounds
  • Tone: Rising tone Falling Tone
  • Flow in Speaking Speaking with a purpose
  • Speech & personality Professional Personality Attributes.

Source: (rgpv.ac.in)

Unit-1 : Data Science

  • Introduction Data Science Life Cycle
  • Statistics: Descriptive and Inferential Statistics
  • Measures of central tendency: Arithmetic Mean Median and Mode.
  • Geometric mean Harmonic Mean and Partition values.
  • Measures of dispersion: Dispersion Range Quartile Deviation Mean deviation
  • Standard Deviation Variance and Coefficient of Dispersion.

UNIT-2 : Theory of probability and Probability

  • Skewness Kurtosis Moments Measure of skewness and kurtosis.
  • Theory of probability: Introduction and definition of Probability
  • Event Sample Space Law of addition and multiplication of Probabilities and Conditional
  • Probability. Independent and Dependent events Bayes’ theorem
  • Mathematical Expectations and Moment generating functions.

UNIT-3 : Theoretical Distribution and Curve fitting

  • Discrete Distribution- Binomial Distribution and Poisson Distribution.
  • Continuous Distribution –Rectangular and Normal distribution.
  • Curve fitting: Curve fitting and Methods of Least square
  • fitting a Straight line and a Parabola.

UNIT-4 : Correlation and Regression

  • Correlation Coefficient of Correlation Rank Correlation
  • Lines of Regression.
  • Multiple and Partial Correlation.

UNIT-5 : Testing of hypothesis

  • Null and Alternative hypothesis two types of errors
  • level of significance and power of the test.
  • Tests of significance: Chi-square distribution
  • test of popular variance and test of goodness of fit. t F Z distribution and tests based on them.

Source: (rgpv.ac.in)

Unit-1 : 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.

UNIT-2 : 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.

UNIT-3 : 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.

UNIT-4 : 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.

UNIT-5 : 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.

Source: (rgpv.ac.in)

Unit-1 :

  • 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.

UNIT-2 :

  • 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.

UNIT-3 :

  • Probabilistic reasoning Baye’s theorem
  • semantic networks scripts
  • schemas frames conceptual dependency
  • forward and backward reasoning.

UNIT-4 :

  • 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.

UNIT-5 :

  • 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.

Source: (rgpv.ac.in)

Unit-1 : 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.

UNIT-2 : Encapsulation and Data Abstraction

  • Concept of Objects: State Behavior & Identity of an object;
  • Classes: identifying classes and candidates for Classes Attributes and Services
  • modifiers Static members of a Class Instances
  • Message passing and Construction and destruction of Objects.

UNIT-3 : Relationships

  • Inheritance: purpose and its types ‘is a’ relationship;
  • Association Aggregation.
  • Concept of interfaces and Abstract classes.

UNIT-4 :

  • Polymorphism: Introduction Method Overriding & Overloading
  • static and runtime Polymorphism.
  • Virtual Function friend function Static function friend class.

UNIT-5 :

  • Strings Exceptional handling
  • Introduction of Multi-threading and Data collections.
  • Case study like: ATM Library management system.

Source: (rgpv.ac.in)

Module-1 :

  • Introduction to python language
  • Basic syntax Literal Constants Numbers
  • Variable and Basic data types String Escape Sequences
  • Operators and Expressions Evaluation Order Indentation
  • Input Output Functions Comments.

Module-2 :

  • Data Structure: List Tuples Dictionary
  • Data Frame and Sets constructing
  • indexing slicing and content manipulation.

Module-3 :

  • Control Flow: Conditional Statements – If If-else
  • Nested If-else.
  • Iterative Statement – For While Nested Loops.
  • Control statements – Break
  • Continue Pass.

Module-4

  • Object oriented programming: Class and Object Attributes
  • Methods Scopes and Namespaces
  • Inheritance Overloading Overriding
  • Data hiding
  • Exception: Exception Handling Except clause
  • Try finally clause User Defined Exceptions.

Module-5 :

  • Modules and Packages: Standard Libraries: File I/0
  • Sys logging Regular expression
  • Date and Time Network programming
  • multi-processing and multi threading.