Topic outline

  • Welcome to Object-Oriented Programming II - Lab

    Object-Oriented Programming II Lab

    Course Code: CSE234  ||  Credits: 2 

     

    Welcome my dear students to the course of Object-Oriented Programming-II Lab(CSE-234). I am here to support you every step of the way. I encourage you to make the most of your time here. Remember to make it a great year. You will find all the necessary materials for learning to start with right here on this page. Let's get started!

          

    Instructor Information:
      Course Teacher: Majidur Rahman
      Designation: Lecturer
      Contact: +8801975291437
      Email: majidur.cse@diu.edu.bd
      Web Profile: https://faculty.daffodilvarsity.edu.bd/profile/cse/majidur.html
      Office Address: Room #903, Daffodil Tower-05, 4/2, Sobhanbag, Dhanmondi, Dhaka-1207
      Appointment in Google Calendar: Click Here
      Click Here to See the Counseling Routine

    Course Description (from syllabus)/Rational:

    Content will be based on upcoming popular and modern programming languages having demand in jobs for local and international markets at the time of offering. In the Fall 2020 semester, the course rationale is defined from the context of Python-based Object-Oriented Programming with the basic skills of programming with Python. Introduction to Python programming; Control Statements and Program Development; Functions; Lists and Tuples; Dictionaries and Sets; Using Numpy for numerical computation; Using String; File and Exception Handling; Object-Oriented Programming: Introduction, Using Class and Method, Inheritance, Operator Overloading, Name Space and Scopes, Polymorphism; Named Tuples, Design Case Study.

    Course Learning Outcome:

    CLO1
    Able to solve the computational problem using Python programming
    CLO2
    Able to develop an object-oriented solution using Python
    CLO3
    Able to apply OOP and Python knowledge in solving a problem

    Teaching and Learning Activities (TLA):

    TLA1
    Interactive discussion using Online/multimedia or whiteboard.
    TLA2
    Group presentation regarding related problems and assigned tasks.
    TLA3
    Evaluation of class performances to reach each student in a class for
    every topic.

    Text Books:

    1. Intro to Python for Computer Science and Data Science, Daitel & Daitel, Pearson 2020
    Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud | 1st edition | Pearson
    Reference Books:

    1. Programming with Python, T.R. Padmanabhan, Springer, 2016
    2. Python for Data Analysis, Wes McKenny, O’Reilly, 2018 

    Online LAB

    An Absolute Beginner's Guide To Google Colaboratory | by digitaldina | Medium

    Course Outline of CSE 234 (Fall-2020)

  • Topic 1

     

    Lesson-1: 

    • Introduction to Python;
    • Variable; Arithmetic; Using print;
    • Input from User; Objects and
    • Dynamic Typing. (Ref. Text, 50-70)

    Lab 01: 

    • Working with Jupyter
    • Notebook and Google Colab (using Online editors)

    Assessment and Mapping with CLO1

    Course Content Link:

  • Topic 2

    Lesson-2:  

    • Operators;
    • Control structures;
    • Program development;
    • Built-in functions;
    • Augmented assignments. (Ref. Text, 74-108)

    Lab 02:

    • Problem-solving using Python-based on the discussion.
    Course Content Link:


    Assessment and Mapping with CLO1

  • Topic 3

    Lesson-3:

    • Functions: define and using the function,
    • Python standard library,
    • Scope rules,
    • The default parameter value. (Ref. Text, 120-148),
    • Discussion on Course Projects.

    Lab 03:

    • Working with functions 

    Course Content Link:


    Assessment and Mapping with CLO1

  • Topic 4

    Lesson-4:

    • Sequences: List and Tuples: Lists,
    • Tuples,
    • Unpacking Sequences,
    • Sequence Slicing,
    • Sorting List,
    • Searching Sequences,
    • Example Cases (Ref. Text, 156-175)

    Lab 04:

    • Working with Sequences using Google Colab

    Course Content Link:

    Assessment and Mapping with CLO1

  • Topic 5

    Lesson-5:

    • Sequences: List and Tuples: Stack with List, 
    • List comprehensions,
    • Expression,
    • Filter,
    • Map and Reduce,
    • Sequence processing function,
    • 2-D lists (Ref. Text, 176-193)

    Lab 05:

    • Working with Sequences using Google Colab

    Course Content Link:

    Assessment and Mapping with CLO1

  • Topic 7


    Topics: Week 3 – Week 6

    • Topic 8

      Lesson 7:

      • OOP Using Python: defines class and object,
      • encapsulation and data hiding,
      • controlling access to attributes,
      • properties for data access,
      • example cases (Ref. Text, 356-370)

      Lab 08:

      • Working with OOP using Python in Google Colab/ Jupyter notebook

      Course Content Link:


      Assessment and Mapping with CLO1 , CLO2

    • Topic 9

      Lesson 8:

      • OOP using Python: Inheritance in Python,
      • Design Case Study,
      • Design inheritance based on a real-life problem (Ref. Text, 370-391)

      Lab 08:

      • Working with OOP using Python in Google Colab/ Jupyter notebook

      Course Content Link:


      Assessment and Mapping with CLO1, CLO2

    • Topic 10

      Lesson 9:

      • OOP using Python: Operator overloading,
      • Polymorphism,
      • Handling exception,
      • Named tuples,
      • Using Card data types,
      • Design case study (Ref. Text, 390-410)

      Lab 09:

      • Working with OOP using Python in Google Colab/ Jupyter notebook

      Course Content Link:


      Assessment and Mapping with CLO1 , CLO2

    • This topic

      Topic 11

      Lab 12:

      • Lab Performance Test 


      Assessment and Mapping with CLO1 , CLO2, CLO3

    • Topic 12

      • CSE 234 - Lab Project Submission Assignment

        Dear Student,

        You are required to submit the project considering the following things:

        • You should submit the code file of the project.
        • You should submit the video presentation file of the project as a group through Google Meet Recording.
        • Only one member of the group should submit the files.
        • Maintain the deadline(15 December 2020, 11:59 PM) strictly.