SE 213 (MA-231)

Home Guidelines

Digital Electronics and Logic Design (Spring-23)

Instructors Md. Mamun Ali

Category SWE Spring 2023

FREE

Enrol Now

Updated 06 Mar 2023

Lessons 13

Enrolled 62

Language English ‎(en)‎

Skill Level Beginner

Course Overview

There is no content in this section.
To add content, click on the above link ‘Edit course text’

Course Content

Enrolment options

Digital Electronics and Logic Design (Spring-23)

Teacher: Md. Mamun Ali
Teacher: Md. Mamun Ali
Teacher: Md. Mamun Ali

Skill Level: Beginner

Related Courses

View All

Beginner

SWE Spring 2023

Algorithm Analysis and Design Lab (Spring-2024)

Musabbir Hasan Sammak

12 Lessons

Updated: Jan 2024

82 Enrolled

View Course

Beginner

SWE Spring 2023

Introduction To Data Science and Data Management & Analysis [DS Major] (Spring-2023)

This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, Linear regression, Logistic regression, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, K-mean algorithm). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications so that you'll also learn how to apply learning algorithms.Course Objectives The goal of this course is to introduce the students to the concept of modern Machine Learning approaches. The main objectives of this course are-To be introduced with the machine learning techniques and applications.To understand the basic machine learning theories (supervised and unsupervised).To demonstrate the machine learning techniques with the programming language. To be able to apply the techniques in real-life data and environments. Course Learning Outcomes (CLO)By the end of the semester, students should be able to:CLO1: relate the machine learning applications to the real world and surrounding environments. CLO2: understand the supervised and unsupervised learning methods in terms of Machine Learning.CLO3: implement the machine learning techniques (supervised and unsupervised) with python libraries. CLO4: present and defend technical aspects of modern Machine Learning approaches.

18 Lessons

Updated: Jun 2023

56 Enrolled

View Course

Beginner

SWE Spring 2023

Object Oriented Concepts (Spring 2023)

Esraq Humayun

Object-oriented programming is a programming paradigm, or classification, that organizes a group of data attributes with functions or methods into a unit, known as an object. Typically, OOP languages are class-based, meaning a class defines the data attributes and functions as a blueprint for creating objects, which are instances of the class. One class may represent multiple independent objects, which interact with each other in complex ways. Popular class-based programming languages include Java, Python and C++.For example, if a class represents a person, it may contain attributes to represent various data, such as the person's age, name and height. The class definition might also contain functions, such as a function to print the person's name on a screen. You could create a family by representing person objects from the class of each family member. Each person object contains different data attributes because every person is unique.

25 Lessons

Updated: Apr 2023

14 Enrolled

View Course

Beginner

SWE Spring 2023

Numerical Analysis (Spring-2023)

Ishrat Sultana

Hello Everyone!Welcome to SWE 422 (Numerical Analysis with Lab) !This course is an introduction to the numerical analysis. The primary objective of the course is to develop the basic understanding of numerical algorithms and skills to implement algorithms to solve mathematical problems on the computer. This course analyzed the basic techniques for the efficient numerical solution of problems in science and engineering. Topics spanned root finding, interpolation, approximation of functions, integration, differential equations, direct and iterative methods in linear algebra.

10 Lessons

Updated: Mar 2023

36 Enrolled

View Course