Course | Raihan Tanvir

CSE 3201 : Introduction to Computer Networks

Mon, 01 Jan 2024 00:00:00 +0000

An introduction to computer networking concepts, protocols, architectures, and practical networking skills.

Course Overview

CSE 3201: Introduction to Computer Networks covers the fundamental principles of computer networking, including network architectures, protocols, and practical skills for designing and managing networks.

Sessions Conducted:

Spring 2024 (CSE 3201 & CSE 3202 Sessional)

Syllabus Highlights

Introduction to Computer Networks
- Network models and architectures (OSI, TCP/IP)
- Types of networks: LAN, WAN, MAN, PAN
Physical Layer
- Transmission media and switching
- Data encoding and modulation
Data Link Layer
- Framing, error detection, and correction
- MAC protocols and Ethernet
Network Layer
- IP addressing and subnetting
- Routing algorithms and protocols
Transport Layer
- TCP, UDP, and port management
- Flow and congestion control
Application Layer
- Common protocols (HTTP, FTP, DNS, SMTP)
- Network applications and services
Network Security Basics
- Encryption, authentication, and firewalls
Laboratory/Sessional (CSE 3202)
- Hands-on configuration of network devices
- Packet analysis and network troubleshooting
- Simulation tools (e.g., Cisco Packet Tracer, Wireshark)

CSE 4138 : Soft Computing Lab

Mon, 01 Jan 2024 00:00:00 +0000

Soft computing covers fuzzy sets, artificial neural networks, probabilistic reasoning, genetic algorithms, and combined approaches for computing applications.

Course Overview

CSE 4138: Soft Computing Lab explores computational techniques that model and solve complex real-world problems using soft computing paradigms.

Sessions Conducted:

Fall 2023, Spring 2024

Syllabus Highlights

Fuzzy Sets and Logic
- Concepts and properties of fuzzy sets
- Mathematical and logical implications of fuzzy sets
- Fuzzy relations
- Applications in information processing, decision making, and control systems
Artificial Neural Networks (ANNs)
- Fundamental ideas and concepts of ANNs
- Types: Feed-Forward, Recurrent, and others
- Training rules and methodologies
- Learning algorithms: error backpropagation, recurrent backpropagation
Probabilistic Reasoning
- Bayesian inference models and Bayesian networks
- Dempster–Shafer theory
- Probabilistic decision support systems
Genetic Algorithms (GAs)
- Principles and fundamental operators of GAs
- GA-based search, optimization, learning, and control
Combined Approaches
- Introduction to neuro-fuzzy-probabilistic-genetic combined approaches in computing applications

CSE 2207 : Algorithms

Sun, 01 Jan 2023 00:00:00 +0000

Topics include algorithmic complexity analysis, design methods (divide and conquer, greedy, dynamic programming, backtracking), and understanding intractable problems.

Course Overview

CSE 2207: Algorithms covers foundational and advanced topics in algorithm design and analysis, including complexity analysis, various design paradigms, and intractable problems.

Sessions Conducted:

Spring 2023 (CSE 2207)
Fall 2022, Spring 2023, Fall 2023 (CSE 2208 Sessional)
with .

Syllabus Highlights

Algorithmic Complexity Analysis
- Efficiency scaling with input size
- Time and space complexity
- Big O notation and other measures
Design Methods for Efficient Algorithms
- Divide and Conquer: Merge sort, quicksort
- Greedy Method: Huffman coding, Dijkstra’s algorithm
- Dynamic Programming: Fibonacci sequence, shortest path problems
- Backtracking: N-queens problem, Sudoku
- Branch and Bound: Traveling salesman problem, 0/1 knapsack
- Polynomial Evaluation: Horner’s method
- Lower Bound Theory: Minimum resources required for problems
- Intractable Problems: NP-hard, NP-complete

CSE 3207 : Artificial Intelligence

Sat, 01 Jan 2022 00:00:00 +0000

Covers AI concepts, knowledge representation, reasoning, organization, perception, knowledge-based systems, and basic machine learning algorithms.

Course Overview

CSE 3207: Artificial Intelligence introduces foundational AI concepts, knowledge representation, reasoning, perception, and basic machine learning.

Sessions Conducted:

CSE 3207 (Spring 2022)
CSE 3208 Sessional (Spring 2022, Fall 2022)
with .

Syllabus Highlights

Survey of Basic AI Concepts and Controversies
Knowledge Representation and Reasoning
- Propositional and first-order predicate logic
- Handling inconsistencies and uncertainties
- Structured representation
Knowledge Organization and Manipulation
- Search and control strategies
- Game playing
- Planning
- Decision making
Perception and Communication
- Natural language processing
- Visual image understanding
Knowledge Acquisition (Machine Learning)
Introduction to Knowledge-Based Systems (Expert Systems)
Basic Machine Learning Algorithms
- Backpropagation technique
- Linear classifiers
- Clustering algorithms