A Level: Programming and Problem Solving Through Python Language (A3 R5, NIELIT/DOEACC)

Online Interactive Classe: A Level: Programming and Problem Solving Through Python Language (A3-R5, NIELIT / DOEACC)
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A Level: Programming and Problem Solving Through Python Language (A3-R5, NIELIT / DOEACC): https://www.techinaut.com/course/a-level-programming-and-problem-solving-through-python-language-a3-r5-nielit-doeacc/
Mode of Course: Virtual Classroom / Online Classroom / Live Interactive Classes Or Online Tution
Duration Of Course: 3 Month (120 Hours – (Theory: 48hrs + Practical: 72 hrs))
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Syllabus:
Introduction
Python is easy to use, powerful, and versatile programming language, making it a great choice for developers. Python is used widely in different areas likes building Raspberry Pi applications, writing a script program for desktop applications, configuring servers, developing machine learning& data analytics applications, and developing web applications.

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 Divisor) 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 an 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-elseif-else; simple programs, Notion of iterative computation and control flow –range function, While Statement, For loop, break statement, Continue Statement, Pass statement, else, asserts.

(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(), write lines(),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, datatypes, array attributes, array creation routines, Array From Existing Data, Array From Numerical Ranges, Indexing & Slicing.