- To understand the problem solving approaches.
- To learn the basic programming constructs in Python.
- To practice various computing strategies for Python-based solutions to real world problems.
- To use Python data structures - lists, tuples, dictionaries.
- To do input/output with files in Python.
EXPERIMENTS:
Note: The examples suggested in each experiment are only indicative. The lab instructor is
expected to design other problems on similar lines. The Examination shall not be restricted
to the sample experiments listed here.
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, weight of 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).
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).
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).
8. Implementing programs using written modules and Python Standard Libraries (pandas,
numpy. Matplotlib, 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).
11. Exploring Pygame tool.
12. Developing a game activity using Pygame like bouncing ball, car race etc.
COURSE OUTCOMES:
CO1: Develop algorithmic solutions to simple computational problems
CO2: Develop and execute simple Python programs.
CO3: Implement programs in Python using conditionals and loops for solving problems..
CO4: Deploy functions to decompose a Python program.
CO5: Process compound data using Python data structures.
CO6: Utilize Python packages in developing software applications.
Click Here to Download Question Paper- Apr/May 2017
Click Here to Download Question Paper- Apr/May 2018
Click Here to Download Question Paper- Nov/Dec 2017
Click Here to Download Anna University Syllabus
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