GE8151-Problem Solving and Python Programming Syllabus 2017 Regulation
GE8151Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â PROBLEM SOLVING AND PYTHON PROGRAMMING Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â L T P C Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 3 0 0 3
OBJECTIVES:
- To know the basics of algorithmic problem solving
- To read and write simple Python programs.
- To develop Python programs with conditionals and loops.
- To define Python functions and call them.
- To use Python data structures â- lists, tuples, dictionaries.
- To do input/output with files in Python.
UNIT IÂ Â Â Â Â Â Â Â Â Â Â Â Â Â ALGORITHMIC PROBLEM SOLVINGÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 9
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 IIÂ Â Â Â Â Â Â Â Â Â Â DATA, EXPRESSIONS, STATEMENTSÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 9
Python  interpreter  and  interactive  mode;  values  and  types:  int,  float,  boolean,  string,  and list; variables, expressions,  statements, tuple assignment, precedence of operators, comments; modules and functions, function definition and use, flow of execution, parameters and arguments;  Illustrative programs: exchange the values of two variables, circulate the values of n variables, distance between two points.
UNIT IIIÂ Â Â Â Â Â Â Â Â Â Â CONTROL FLOW, FUNCTIONSÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 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: selection sort, insertion sort, mergesort, histogram.
UNIT VÂ Â Â Â Â Â Â Â Â Â FILES, MODULES, PACKAGESÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 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.
OUTCOMES:
Upon completion of the course, students will be able to
- Develop algorithmic solutions to simple computational problems
- Read, write, execute by hand simple Python programs.
- Structure simple Python programs for solving problems.
- Decompose a Python program into functions.
- Represent compound data using Python lists, tuples, dictionaries.
- Read and write data from/to files in Python Programs.
TOTAL : 45 PERIODS
TEXT BOOKS:
- Allen B. Downey, “Think Python: How to Think Like a Computer Scientistââ, 2nd edition, Updated for Python 3, Shroff/OâReilly Publishers, 2016 Â (http://greenteapress.com/wp/think- python/)
- Guido van Rossum and Fred L. Drake Jr, âAn Introduction to Python â Revised and updated for Python 3.2, Network Theory Ltd., 2011.
REFERENCES:
- John V Guttag, âIntroduction to Computation and Programming Using Pythonââ, Revised and
expanded Edition, MIT Press , 2013
- Robert Sedgewick, Kevin Wayne, Robert Dondero, âIntroduction to Programming in Python:
An Inter-disciplinary Approach, Pearson India Education Services Pvt. Ltd., 2016.
- Timothy A. Budd, âExploring Pythonâ, Mc-Graw Hill Education (India) Private Ltd.,, 2015.
- Kenneth A. Lambert, âFundamentals of Python: First Programsâ, CENGAGE Learning, 2012.
- Charles Dierbach, âIntroduction to Computer Science using Python: A Computational Problem- Solving Focus, Wiley India Edition, 2013.
- Paul Gries, Jennifer Campbell and Jason Montojo, âPractical Programming: An Introduction to
Computer Science using Python 3â, Second edition, Pragmatic Programmers, LLC, 2013.
