This is the Python Programming syllabus prescribed for 3rd Semester Undergraduate Computer Science and Engineering Programme starting from the year 2019 at Dr.Ambedkar Institute of Technology (Dr.AIT), Bengaluru, Karnataka, India.


Sub Title: PYTHON PROGRAMMING
Sub Code: 18CS35
Exam Duration: 3 hours
No. of Credits: 4= 4: 0: 0 (L: T: P)
No. of lecture hours/week: 4 Hours
Total No. of Contact Hours: 52 Hours


Course objectives:

  1. Describe the core syntax and semantics of Python programming language.
  2. Discover the need for working with the strings and functions.
  3. Illustrate the process of structuring the data using lists, dictionaries, tuples and sets.
  4. Indicate the use of regular expressions and built-in functions to navigate the file system.
  5. Infer the Object-oriented Programming concepts in Python.


UNIT No Syllabus Content No. of Hours
1 Parts of Python Programming Language, Identifiers, Keywords, Statements and Expressions, Variables, Operators, Precedence and Associativity, Data Types, Indentation, Comments, Reading Input, Print Output, Type Conversions, The type() Function and Is Operator, Dynamic and Strongly Typed Language, Control Flow Statements, The if  Decision Control Flow Statement, The if…else Decision Control Flow Statement, The if…elif…else Decision Control Statement, Nested if Statement, The while Loop, The for Loop, The continue and break Statements, Catching Exceptions Using try and except Statement, Functions, Built-In Functions, Commonly Used Modules, Function Definition and Calling the Function, The return Statement and void Function, Scope and Lifetime of Variables, Default Parameters, Keyword Arguments, *args and **kwargs, Command Line Arguments. 11
2 Strings, Creating and Storing Strings, Basic String Operations, Accessing Characters in String by Index Number, String Slicing and Joining, String Methods, Formatting Strings, Lists, Creating Lists, Basic List Operations, Indexing and Slicing in Lists, Built-In Functions Used on Lists, List Methods, The del Statement. 10
3 Dictionaries, Creating Dictionary, Accessing and Modifying key:value Pairs in Dictionaries, Built-In Functions Used on Dictionaries, Dictionary Methods, The del Statement, Tuples and Sets, Creating Tuples, Basic Tuple Operations, Indexing and Slicing in Tuples, Built-In Functions Used on Tuples, Relation between Tuples and Lists, Relation between Tuples and Dictionaries, Tuple Methods, Using zip() Function, Sets, Set Methods, Traversing of Sets, Frozenset. 10
4 Files, Types of Files, Creating and Reading Text Data, File Methods to Read and Write Data, Reading and Writing Binary Files, The Pickle Module, Reading and Writing CSV Files, Python os and os.path Modules, Regular Expression Operations, Using Special Characters, Regular Expression Methods, Named Groups in Python Regular Expressions, Regular Expression with glob Module. 10
5 Object-Oriented Programming, Classes and Objects, Creating Classes in Python, Creating Objects in Python, The Constructor Method, Classes with Multiple Objects, Class Attributes versus Data Attributes, Encapsulation, Inheritance, The Polymorphism 11


Course Outcomes:

COs Statements Bloom’s Level
CO1 Interpret the fundamental Python syntax and semantics and be fluent in the use of Python control flow statements. L2
CO2 Express proficiency in the handling of strings and functions. L2
CO3 Determine the methods to create and manipulate Python programs by utilizing the data structures like lists, dictionaries, tuples and sets. L3
CO4 Identify the commonly used operations involving file systems and regular expressions. L2
CO5 Articulate the Object-Oriented Programming concepts such as encapsulation, inheritance and polymorphism as used in Python. L3


Course Articulation Matrix (CO-PO Mapping)

COs POs PSOs
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3
CO1 3 3 2 1 3 - - - - - - - 1 2 -
CO2 2 2 2 1 3 - - - - - - - 1 2 -
CO3 3 3 2 2 3 - - - - - - - 2 3 -
CO4 2 2 1 1 3 - - - - - - - 1 2 -
CO5 3 3 2 2 3 - - - - - - - 2 3 -


TEXT BOOK

  1. Gowrishankar S, Veena A, “Introduction to Python Programming”, 1st Edition, CRC Press/Taylor & Francis, 2018. ISBN-13: 978-0815394372


REFERENCE BOOKS / WEBLINKS:

  1. Jake VanderPlas, “Python Data Science Handbook: Essential Tools for Working with Data”, 1st Edition, O'Reilly Media, 2016. ISBN-13: 978-1491912058
  2. Aurelien Geron, Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems”, 1st Edition,O'Reilly Media, 2017. ISBN – 13: 978-1491962299.
  3. Wesley J Chun, “Core Python Applications Programming”, 3rd Edition, Pearson Education India, 2015. ISBN-13: 978-9332555365
  4. Miguel Grinberg, “Flask Web Development: Developing Web Applications with Python”, 2nd Edition, O'Reilly Media, 2018. ISBN-13: 978-1491991732.

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