MCA 3rd Semester Syllabus

The MCA 3rd Semester syllabus consists of important subjects such as Artificial Intelligence, Web Technology, Software Engineering, etc. Here is the complete table of the MCA syllabus for Semester 3rd:

Subject List	Detailed Subject-wise Syllabus
Artificial Intelligence	Artificial Intelligence Unit 1 Introduction to Artificial Intelligence Types and structure of intelligent agent Computer Vision Natural language processing Unit 2 Searching Techniques Uniformed searching techniques Informed searching techniques Alpha-Beta pruning Unit 3 Knowledge Representation and Reasoning Propositional logic Predicate logic Clause form conversion Forward chaining and Backward chaining Bayesian network Unit 4 Machine Learning Types and application areas Decision trees Statistical learning methods EM algorithm Reinforcement learning Unit 5 Pattern Recognition Introduction and design principles Principle component analysis Nearest neighbor rule K-means clustering Support vector machine
Software Engineering	Software Engineering Unit 1 Introduction to Software Engineering Software Components Software Crisis Software Development Life Cycle(SDLC) Waterfall Model Prototype Model Spiral Model Evolutionary Models Iterative Waterfall Models Unit 2 Software Requirement Specifications(SRS) Requirement Engineering Process Elicitation Analysis Feasibility Study Data Flow Diagrams Entity Relationship Diagrams Decision Tables SRS Document Verification and Validation ISO 9000 Models Unit 3 Basic Concept of Software Design Coupling and Cohesion Measures Function Oriented Design Object oriented Design Function Point(FP) Based Measures Unit 4 Software Testing Unit Testing Integration Testing Acceptance Testing Regression Testing Structural Testing (White Box Testing) Functional Testing (Black Box Testing) Unit 5 Software Maintenance Software Project Management Software Evolution Software Re- Engineering Reverse Engineering Constructive Cost Models (COCOMO) Resource Allocation Models Software Risk Analysis and Management
Compiler Design	Compiler Design Unit 1 Introduction to Compiler Finite state machines and regular expressions and their applications to lexical analysis Formal grammars and their application to syntax analysis Context free grammars Derivation and parse trees Unit 2 Basic Parsing Techniques Shift reduce parsing Top down parsing Constructing SLR parsing tables Constructing LALR parsing tables Implementation of LR parsing tables Unit 3 Syntax-directed Translation Parse trees & syntax trees Three address code Working with top down parser Unit 4 Symbol Tables Implementation of simple stack allocation scheme Error Detection & Recovery Lexical Phase errors Syntactic phase errors Semantic errors Unit 5 Code Generation Target Code Generation Basic Blocks and Flow Graphs Code optimization Loop optimization DAG representation of basic blocks Global Data-Flow analysis
Data Analytics	Data Analytics Unit 1 Introduction to Data Analytics Classification of data Introduction to Big Data platform Uses of data analytics Various phases of data analytics lifecycle Unit 2 Bayesian modeling Support vector Machine Principal component analysis Neural Networks fuzzy decision trees Unit 3 Introduction to streams concepts Stream data model and architecture Real-time Analytics Platform ( RTAP) applications Unit 4 Frequent Itemsets and Clustering Market based modelling Apriori algorithm Hierarchical clustering K-means clustering CLIQUE Algorithm Projected Clustering in data analytics Frequent pattern based clustering Unit 5 MapReduce Hadoop Hadoop Distributed File Systems Visual data analysis techniques Introduction to R
Web Technology	Web Technology Unit 1 Introduction to Web Development Strategies History of Web and Internet HTML Introduction Introduction of CSS Unit 2 Introduction to JavaScript Creating Variables in JavaScript Creating Functions in JavaScript Looping in JavaScript Manipulating HTML Elements with JavaScript Unit 3 Servlet Overview and Architecture Interface Servlet and the Servlet Life Cycle Handling HTTP get Requests Handling HTTP post Requests Session Tracking with Http Session Java Server Pages (JSP) Unit 4 Spring Core Basics Introduction to Design patterns Strategy Design pattern Session Application WebSocket Bean Configuration styles Unit 5 Spring Boot Spring Boot Configuration Spring Boot Annotations Spring Boot Actuator Spring Boot Build Systems Building Restful Web Services

Note: Elective subjects may be added to the semester in addition to the main or core subjects that depends on the specialization like Artificial Intelligence, Data Science, Cyber Security etc to allow students to concentrate on a specific area of interest. One essential aspect of the semester is the practical application of the theoretical subjects. To help with this, a variety of labs and projects are planned to increase problem- solving skills of the students.

MCA 3rd Semester Syllabus 2024

MCA stands for Master of Computer Applications, and it is a college postgraduate degree that focuses on computer science, preparing students for jobs in software development, programming, and related fields.

The MCA 3rd Semester Syllabus provided here is well-structured and regularly updated, encompassing all subjects taught in Semester 3 of the MCA program. It offers a comprehensive list of topics for each subject, making it a valuable resource for students studying in various universities across India that offer the MCA program. This study material can serve as both an exam preparation tool and a syllabus guide for Semester 3.

For students who are new to the MCA Course or wish to revisit the topics covered in the 1st and 2nd semesters, it is recommended to explore the syllabus and study material for Semester 1 and Semester 2 respectively:

MCA 3rd Semester Syllabus

MCA 3rd Semester Syllabus 2024

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MCA 3rd Semester Syllabus

MCA 3rd Semester Syllabus 2024

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