**Description**

Python is easy to use, powerful and versatile, making it a great choice for developers. Python is used widely in different areas like building Raspberry Pi applications, writing script programs for desktop applications, configuring servers, developing machine learning & data analytics applications, and developing web applications.

**What will you learn**

- Draw flow charts for solving different problems
- Develop efficient algorithms for solving a problem
- Use the various constructs of Python viz. conditional, iteration
- Write programs making judicious use of Lists, Strings, Tuples, Dictionaries wherever required
- Manage data using Numpy
- Handle files and create Modules in Python

**Detailed Syllabus**

**(i) Introduction to Programming**

The basic model of computation, algorithms, flowcharts, Programming Languages, compilation, testing & Debugging, and documentation.

**(ii) Algorithms and Flowcharts to Solve Problems**

Flow Chart Symbols, Basic algorithms/flowcharts for sequential processing, decision-based processing, and iterative processing. Some examples like Exchanging values of two variables, summation of a set of numbers, Decimal Base to Binary Base conversion, Reversing digits of an integer, GCD (Greatest Common Division) of two numbers, Test whether a number is prime, factorial computation, Fibonacci sequence, Evaluate ‘sin x’ as the sum of a series, Reverse the order of elements of an array, Find the largest number in an array, Print elements of the upper triangular matrix, etc.

**(iii) Introduction to Python**

Python Introduction, Technical Strength of Python, Introduction to Python Interpreter and program execution, Using Comments, Literals, Constants, Python’s Built-in Data types, Numbers (Integers, Floats, Complex Numbers, Real, Sets), Strings (Slicing, Indexing, Concatenation, other operations on Strings), Accepting input from Console, printing statements, Simple ‘Python’ programs.

**(iv) Operators, Expressions, and Python Statements**

Assignment statement, expressions, Arithmetic, Relational, Logical, Bitwise operators and their precedence, Conditional statements: if, if-else, if-elif-else; simple programs, Notion of iterative computation and control flow –range function, While Statement, For loop, break statement, Continue Statement, Pass statement, else, assert.

**(v) Sequence Data Types **

Lists, tuples, and dictionary, (Slicing, Indexing, Concatenation, other operations on Sequence data type), the concept of mutability, Examples to include finding the maximum, minimum, mean; linear search on the list/tuple of numbers, and counting the frequency of elements in a list using a dictionary.

**(vi) Functions **

The top-down approach of problem-solving, Modular programming and functions, Function parameters, Local variables, the Return statement, DocStrings, global statement, Default argument values, keyword arguments, varargs parameters.

Library function-input(), eval(),print(), String Functions: count(), find(), rfind(), capitalize(), title(), lower(), upper(), swapcase(), islower(), isupper(), istitle(),replace(), strip(), lstrip(), rstrip(), aplit(), partition(), join(), isspace(), isalpha(), isdigit(), isalnum(), startswith(), endswith(), encode(), decode(), String: Slicing, Membership, Pattern Matching, Numeric Functions: eval(), max(), min(), pow(), round(), int(), random(), ceil(), floor(), sqrt(), Date & Time Functions, Recursion.

**(vii) File Processing **

Concept of Files, File opening in various modes and closing of a file, Reading from a file, Writing onto a file, File functions-open(), close(), read(), readline(),readlines(),write(), writelines(),tell(),seek(), Command Line arguments.

**(viii) Scope and Modules **

Scope of objects and Names, LEGB Rule Module Basics, Module Files as Namespaces, Import Model, Reloading Modules.

**(ix) NumPy Basics **

Introduction to NumPy,ndarray, data types, array attributes, array creation routines, Array From Existing Data, Array From Numerical Ranges, Indexing & Slicing.

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