Overview of Python and its applications in engineering-Basic Syntax and Data Type: Variables, data types,
and basic operations- Conditional statements and loop.
1. Identification and solving of simple real life or scientific or technical problems, and developing flow charts for the same. (Electricity Billing, Retail shop billing, Sin series, weightof a motorbike, Weight of a steel bar, compute Electrical Current in Three Phase AC Circuit,etc.)
2. Python programming using simple statements and expressions (exchange the values of two variables, circulate the values of n variables, distance between two points).
3. Scientific problems using Conditionals and Iterative loops. (Number series, Number Patterns, pyramid pattern)
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.
6. Implementing programs using Functions. (Factorial, largest number in a list, area of shape
7. Implementing programs using Strings. (reverse, palindrome, character count, replacing characters)
LISTS, TUPLES, DICTIONARIES
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.
4. Implementing real-time/technical applications using Lists, Tuples. (Items present in a library/
Components of a car/ Materials required for construction of a building –operations of list & tuples)
5. Implementing real-time/technical applications using Sets, Dictionaries. (Language, components of
an automobile, Elements of a civil structure, etc.- operations of Sets &Dictionaries)
Files and exceptions: 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).
8. Implementing programs using written modules and Python Standard Libraries (pandas, numpy. Mat
plot lib, scipy)
9. Implementing real-time/technical applications using File handling. (copy from one file to another,
word count, longest word)
10. Implementing real-time/technical applications using Exception handling. (divide by zero error,
voter’s age validity, student mark range validation)
NumPy: Introduction to NumPy arrays and operations- Data manipulation with Pandas-Data visualization
using Matplotlib.-Data Import and Export: Handling CSV, Excel, and other data formats.
11. Exploring Pygame tool.
12. Developing a game activity using Pygame like bouncing ball, car race etc.
Reference Book:
1. Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition,2021.
2. G Venkatesh and MadhavanMukund, “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.
Text Book:
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.
