GE3151 PSPP Syllabus Problem Solving and Python Programming – Ist Sem

GE3151 PSPP SYLLABUS

We are providing the GE3151 Problem Solving and Python Programming Syllabus below for your examination success. use our Materials to score good marks in the examination. Best of Luck.

Regulation	2021
Subject Code	GE3151
Subject Name	PROBLEM SOLVING AND PYTHON PROGRAMMING
Semester	I

OBJECTIVES:

 To understand the basics of algorithmic problem solving.
 To learn to solve problems using Python conditionals and loops.
 To define Python functions and use function calls to solve problems.
 To use Python data structures – lists, tuples, dictionaries to represent complex data.
 To do input/output with files in Python.

UNIT I COMPUTATIONAL THINKING AND PROBLEM SOLVING 9

Fundamentals of Computing – Identification of Computational Problems -Algorithms, building
blocks of algorithms (statements, state, control flow, functions), notation (pseudo code, flow chart, programming language), algorithmic problem solving, simple strategies for developing algorithms(iteration, recursion). Illustrative problems: find minimum in a list, insert a card in a list of sorted cards, guess an integer number in a range, Towers of Hanoi.

UNIT II DATA TYPES, EXPRESSIONS, STATEMENTS 9

Python interpreter and interactive mode, debugging; values and types: int, float, boolean, string, and list; variables, expressions, statements, tuple assignment, precedence of operators,
comments; Illustrative programs: exchange the values of two variables, circulate the values of n variables, distance between two points.

UNIT III CONTROL FLOW, FUNCTIONS, STRINGS 9

Conditionals: Boolean values and operators, conditional (if), alternative (if-else), chained
conditional (if-elif-else); Iteration: state, while, for, break, continue, pass; Fruitful functions: return values, parameters, local and global scope, function composition, recursion; Strings: string slices, immutability, string functions and methods, string module; Lists as arrays. Illustrative programs: square root, gcd, exponentiation, sum an array of numbers, linear search, binary search.

UNIT IV LISTS, TUPLES, DICTIONARIES 9

Lists: list operations, list slices, list methods, list loop, mutability, aliasing, cloning lists, list
parameters; Tuples: tuple assignment, tuple as return value; Dictionaries: operations and methods; advanced list processing – list comprehension; Illustrative programs: simple sorting, histogram, Students marks statement, Retail bill preparation.

UNIT V FILES, MODULES, PACKAGES 9

Files and exception: text files, reading and writing files, format operator; command line arguments, errors and exceptions, handling exceptions, modules, packages; Illustrative programs: word count, copy file, Voter’s age validation, Marks range validation (0-100).
TOTAL : 45 PERIODS

OUTCOMES:

Upon completion of the course, students will be able to
CO1: Develop algorithmic solutions to simple computational problems.
CO2: Develop and execute simple Python programs.
CO3: Write simple Python programs using conditionals and looping for solving problems.
CO4: Decompose a Python program into functions.
CO5: Represent compound data using Python lists, tuples, dictionaries etc.
CO6: Read and write data from/to files in Python programs.

TEXT BOOKS:

1. Allen B. Downey, “Think Python : How to Think like a Computer Scientist”, 2nd Edition,
   O’Reilly Publishers, 2016.
2. Karl Beecher, “Computational Thinking: A Beginner’s Guide to Problem Solving and
   programming”, 1st Edition, BCS Learning & Development Limited, 2017.

REFERENCES:

1. Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition,
   2021.
2. G Venkatesh and Madhavan Mukund, “Computational Thinking: A Primer for Programmers
   and Data Scientists”, 1st Edition, Notion Press, 2021.
3. John V Guttag, “Introduction to Computation and Programming Using Python: With
   Applications to Computational Modeling and Understanding Data‘‘, Third Edition, MIT Press
   2021
4. Eric Matthes, “Python Crash Course, A Hands – on Project Based Introduction to
   Programming”, 2nd Edition, No Starch Press, 2019.
5. https://www.python.org/
6. Martin C. Brown, “Python: The Complete Reference”, 4th Edition, Mc-Graw Hill,2018.

Useful Links :

GE3151 Problem Solving and Python Programming Syllabus	Click Here
GE3151 Problem Solving and Python Programming Question Papers	Click Here
GE3151 Problem Solving and Python Programming Lecture Notes	Click Here
GE3151 Problem Solving and Python Programming Two Mark Questions	Click Here
GE3151 Problem Solving and Python Programming Question Bank	Click here

Search Terms :

GE3151 Program Solving and Python Programming Syllabus, GE3151 PSPP Syllabus