NOTE – SYLLABUS OF CSE AI, CSE AIML, CSE DS, CSE IOT, CSE ICB, CSE NET, CSE CS ARE TOTALLY SAME FOR 3RD SEMESTER
IPU B.Tech CSE (Specialisation) 3rd Semester Syllabus: Understanding the IPU Computer Science Engineering (Artificial Intelligence) 3rd Semester Syllabus
The syllabus for the 3rd semester of Computer Science Engineering with a specialization in Artificial Intelligence at IPU is designed to provide students with a robust foundation in both theoretical and practical aspects of AI and related technologies. Here’s a breakdown of the key subjects covered in this semester, explained in simple and easy-to-understand language.
Data Structures | IPU B.Tech CSE (Specialisation) 3rd Semester Syllabus
Objective: This course aims to teach students how to organize and manage data efficiently using various structures.
Key Topics:
Arrays and Linked Lists: Basics of storing data in arrays and linked lists, differences, and use-cases.
Stacks and Queues: Introduction to these linear data structures, their operations, and applications.
Trees: Understanding binary trees, binary search trees, AVL trees, and their significance in hierarchical data management.
Graphs: Basics of graph theory, types of graphs, and algorithms for graph traversal like BFS and DFS.
Hashing: Techniques for efficient data retrieval using hash tables.
Object-Oriented Programming (OOP)
IPU B.Tech CSE (Specialisation) 3rd Semester Syllabus Objective: To introduce the concepts of object-oriented programming and how it improves code reusability and scalability.
Key Topics:
Classes and Objects: Understanding the blueprint of objects and how they are instantiated.
Inheritance: Mechanism to derive new classes from existing ones to promote code reuse.
Polymorphism: Ability to redefine methods in derived classes to achieve flexibility.
Encapsulation: Hiding the internal state of an object and requiring all interaction to be performed through an object’s methods.
Abstraction: Simplifying complex systems by modeling classes appropriate to the problem.
Database Management Systems (DBMS)
Objective: This course covers the fundamentals of database systems and how they are used to store, retrieve, and manage data.
Key Topics:
Database Models: Overview of different database models with a focus on the relational model.
SQL: Learning Structured Query Language for database creation, manipulation, and management.
Normalization: Techniques to minimize redundancy and improve data integrity.
Transactions: Understanding ACID properties (Atomicity, Consistency, Isolation, Durability) to manage database transactions.
Discrete Mathematics
Objective: To provide mathematical foundations essential for computer science.
Key Topics:
Sets and Propositions: Basics of set theory and logic, operations on sets, and logical statements.
Relations and Functions: Understanding different types of relations and functions, their properties, and applications.
Graphs and Trees: Introduction to graph theory, tree structures, and their applications in computer science.
Counting Techniques: Principles of counting, permutations, combinations, and introduction to probability.
Principles of Artificial Intelligence
Objective: To introduce the fundamental concepts of AI and its various applications.
Key Topics:
Introduction to AI: Definition, history, and applications of AI.
Problem Solving: Techniques for problem-solving using AI, including search algorithms.
Knowledge Representation: Ways to represent knowledge in AI systems, like semantic networks and frames.
Machine Learning: Basics of machine learning, including supervised and unsupervised learning.
Digital Electronics
Objective: To understand the principles and applications of digital electronics.
Key Topics:
Boolean Algebra: Basics of Boolean algebra and logic gates.
Combinational Circuits: Design and analysis of combinational circuits like adders, subtractors, and multiplexers.
Sequential Circuits: Understanding flip-flops, counters, and shift registers.
Microprocessors: Basics of microprocessor architecture and programming.
Laboratory Work – IPU B.Tech CSE (Specialisation) 3rd Semester Syllabus
Objective: To provide hands-on experience and practical knowledge.
Key Topics:
Data Structures Lab: Implementing various data structures in programming languages.
OOP Lab: Writing programs to understand object-oriented concepts.
DBMS Lab: Practical sessions on SQL and database management.
AI Lab: Implementing basic AI algorithms and techniques.
Conclusion | IPU B.Tech CSE (Specialisation) 3rd Semester Syllabus
The 3rd semester syllabus for CSE (AI) at IPU is comprehensive, covering essential subjects that form the backbone of AI and computer science. By focusing on both theoretical knowledge and practical application, students are well-prepared to tackle advanced topics in subsequent semesters.
NOTE – SYLLABUS OF CSE AI, CSE AIML, CSE DS, CSE IOT, CSE ICB, CSE NET, CSE CS ARE TOTALLY SAME FOR 3RD SEMESTER
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