OOP (II)

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  General

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  Object-Oriented Programming II and Lab
  

  Course Code: CSE233 & CSE234  ||  Credits: 1+2  || CIE Marks: 60 ||  SEE Marks: 40

  
  

  
  

   

   
  

  
  

  Dear Students,

  Welcome to Data Structure Course . I am Thaharim Khan, Lecturer, Department of Computer Science and Engineering (CSE) and I am your instructor in this  Course. In addition to welcoming you to the course, I would like to say "Online courses provide a different way to study and place different skills from students". I will provide you the necessary support during the course to successfully complete this course.

  
  

  
  
  

  Course Learning Outcome:

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

  
  

  Teaching and Learning Activities (TLA)

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

  
  

  
  

  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 rational 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. 
  
  

  Text Books:
  1. Intro to Python for Computer Science and Data Science, Daitel & Daitel, Pearson 2020
  

  
  

  
  

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

  
  

  Course Content Google Drive Link

  
  

  Online LAB

  
  

  
  

  Course Outline

  
  

  
  

  Course Instructor Details

  Thaharim Khan

  Office: Level 1, Room : 103  Daffodil Tower 
  Telephone : +8801750984224
  Email: thaharim.cse0276.c.cse@diu.edu.bd
  
  

  
  
  
  

  
  

  
  
  

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  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:

  • Theory Material Link + LAB Material Link

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  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 discussion.
  
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  
  Assessment and Mapping with CLO1
  
  

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    Assignment 1

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    Problem solving using Python

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  Topic 3

  Lesson-3: Functions: define and using the function, Python standard library, Scope rules, Default parameter value. (Ref. Text, 120-148)

  Discussion on Course Projects.

  Lab 03: Working with functions
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1
  

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  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:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1
  
  
  Class recording SEC A
  

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  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:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1
  

  • Select activity Class recording

    

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  Topic 6

  Lesson 6: Dictionaries and Sets: Create dictionary, Dictionary operations, Dictionary methods keys and values, Working with Set, Dynamic visualization (Ref. Text, 210-231)

  Lab 06: Working with Dictionaries and Sets using Google Colab/ Jupyter notebook
  

  
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1
  

  • Select activity Assignment 2

    

    Assignment 2

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    Assignment 2

    • Sequences and Tuples
    • Dictionaries and Sets

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    Project Concept Assignment

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    Presentation by Team

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• Select section Topic 7

  Topic 7

  
  

  
  

  Open book exam guideline 

  Answer template 
• Select section Topic 8

  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 07: Working with OOP using Python in Google Colab/ Jupyter notebook
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1 , CLO2
  

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  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:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1 , CLO2
  

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• Select section Topic 10

  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:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1 , CLO2
  

  • Select activity Class recording Sec G

    

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• Select section Topic 11

  Topic 11

  Lesson 10: Using NumPy: Array from existing data, array attributes, attay Operators, NumPy methods, Shallow copies, Deep copies, Examples (Ref. Text, 240-256)

  Lab 10: Working with NumPy using Python in Google Colab/ Jupyter notebook
  

  
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1
  

  • Select activity Class Test# 3

    

    Class Test# 3 Quiz

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• Select section Topic 12

  Topic 12

  Lesson 11: Using NumPy: Universal functions, Indexing and slicing, Reshaping and transposing, Examples (Ref. Text, 252-267)

  Lab 11: Group Project Presentation Sharing by Team Lead on behalf of the team
  

  
  

  Course Content Link:

  • Theory Material Link + LAB Material Link

  
  Assessment and Mapping with CLO1 , CLO3
  

  • Select activity Project Implementation

    

    Project Implementation Assignment

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    Presentation by Team

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  Topic 13

  Lesson 12: Review class on topics discussed of Wk 8, Wk 9 and Wk 10 for preparing for the final exam

  Lab 12: Lab Performance Test and Project based assessment of course projects
  
  
  Assessment and Mapping with CLO1 , CLO2, CLO3
  

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    Lab Assessment Test (based on course project presentation and final test)

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  Presentation & Report SEC : G

  
  

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