GE8151-Problem Solving and Python Programming Syllabus 2017 Regulation

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GE8151-Problem Solving and Python Programming Syllabus 2017 Regulation

GE8151                           PROBLEM SOLVING AND PYTHON PROGRAMMING                                                                                                                                          L T P C                                                                                                                            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 –- lists, tuples, dictionaries.
  • To do input/output with files in Python.

 

UNIT I               ALGORITHMIC PROBLEM SOLVING                                                                         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 II            DATA, EXPRESSIONS, STATEMENTS                                                                        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 III            CONTROL FLOW, FUNCTIONS                                                                                   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 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.

 

 

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:

  1. Allen B. Downey, “Think Python: How to Think Like a Computer Scientist‘‘, 2nd edition, Updated for Python 3, Shroff/O‘Reilly Publishers, 2016  (http://greenteapress.com/wp/think- python/)
  2. Guido van Rossum and Fred L. Drake Jr, ―An Introduction to Python – Revised and updated for Python 3.2, Network Theory Ltd., 2011.

 

REFERENCES:

  1. John V Guttag, ―Introduction to Computation and Programming Using Python‘‘, Revised and

expanded Edition, MIT Press , 2013

  1. Robert Sedgewick, Kevin Wayne, Robert Dondero, ―Introduction to Programming in Python:

An Inter-disciplinary Approach, Pearson India Education Services Pvt. Ltd., 2016.

  1. Timothy A. Budd, ―Exploring Python‖, Mc-Graw Hill Education (India) Private Ltd.,, 2015.
  2. Kenneth A. Lambert, ―Fundamentals of Python: First Programs‖, CENGAGE Learning, 2012.
  3. Charles Dierbach, ―Introduction to Computer Science using Python: A Computational Problem- Solving Focus, Wiley India Edition, 2013.
  4. Paul Gries, Jennifer Campbell and Jason Montojo, ―Practical Programming: An Introduction to

Computer Science using Python 3‖, Second edition, Pragmatic Programmers, LLC, 2013.

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