
Python 3 Programming Course outline, Versions of Python, History, features and applications of Python, Python Jobs
Installing Python 3, Interactive Mode Programming with Interpreter and Reference book.
Integrated Development Environment, Python's IDLE, IDLE for Interactive Programming, Arithmetic operations, Script mode programming,Program Execution steps in IDLE
Reference book, Interpreters and Compilers, Interpretation process, Python Virtual Machine
Batteries Included Philosophy, Maths Funcions, Colour Coding by IDLE, Other Built-in Functions, Memory administration in Python, Type Checking, Dynamic typing, Frozen Binaries Executables, Python Files, Python Implementations
Tokens, Identifier, Keywords, Constants and Variables, Python Literals, Numeric data types, Arithmetic Operations, Scientific Notation, Complex Numbers, Dot operator, Type Boolean, Operator Precedence with examples, Augmented Assignment Operators, Type conversion
Console Input, Getting any number of inputs from the user, split function, eval() and Type conversion, Random Number Generation, Bit-wise Operators
Unicode code points, Unicode Transformation Format (UTF), UTF-8, UTF-16
Printing strings, string concatenation, The str function, Multiline String, Escaping Quote, Escape Sequences, Index in a string, Negative Index
Syntax of Console Output, Use of comma as separator, Other separators, Formatted Printing, Formatting in scientific notation
% preceded by a format specifier, Justification while printing, Formatted Printing of Integers, Formatting Strings, Use of %s as a place holder, Sequence Types
Using str.format method, Passing variables to the placeholder,
Positional Arguments, Using Python string module and Template class, Using fstring, Checking whether a string is a palindrome or anagram
Structured Programming, Selection and loops, Relational operators, Logical Operators, The and operator, The or operator, The not operator, Selection Constructs, Syntax and Rules, Finding whether a Number is Positive, Toggle case, Finding largest of 3 numbers with nested if-else, Ternary Operator
The while loop, Finding whether a given number is prime, Rules of the for loop, Variations in Range function, Finding largest and smallest numbers in list, break and continue, Generate multiplication tables, The Pass Statement
Function Types, User defined functions, General Form of Function, Calling Functions Multiple Times, if __name__=='__main__':, Calling More Functions in a Program, The void function, Finding distance between two points, Finding Square Root without Math function
Fruitful functions, Multiple return statements, Function calling another function, Run time Stack, Boolean function, Local and Global Scope of Variables, Positional Arguments, Default arguments, Variable Length Arguments, Keyword and Non-keyword arguments
Euclid GCD Recursive Algorithm and Program, Recursive Algorithm and Program for finding the factorial, Finding exponentiation of a number with recursion, Towers of Hanoi algorithm and Program
Popular Containers, List-examples, Properties and operations, Slicing to get substring, List Concatenation, Nesting of lists, Built-in Functions, Difference between Functions and Methods, Use of keyword in
Loops and List, Use of while, list comprehension, Creating Pythagorean triplets, looping with list comprehension, Aliasing List, Cloning lists, Arrays, Getting Python keywords online
Linear Search Algorithm and program, binary search algorithm and program, Finding Transpose of a Matrix, Circulate the Values of n Variables, Caution about Tabs
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Differences between lists and tuples, Built-in Functions, Creating tuple from other container types, additional operations on lists, Tuple as Return Value
Sets, major differences from the list, Set properties, Type set, The set Function, Built-in Functions, Methods of class set, Mathematical Operations, Set Comprehension
Dictionary example, Iterations over dictionaries - 4 Methods, Dictionary operations, Dictionary Methods, Dictionary comprehension, Nesting Dictionary
Data Integrity, Principles of Object-Oriented Programming - Encapsulation, Inheritance, Polymorphism- Class and significance of self, Objects of library classes
Access Control, Object Initializer, Destruction of object, Usage of init and del, The Id function and type function, Class variables and Instance variables
Magic Methods Supported and operator overloading, Overloaded minus operator, == operator, Documentation Strings
Reusability, Inheritance, Containership, Inheritance Types, Single Inheritance, Access Types
Multi-level Inheritance, Multiple Inheritance, The class object, The __str__method, Diamond Problem, Rule for Method overriding, isinstance method
Polymorphism, Abstract class, Application Program Interface (API), Dynamic Binding, Hierarchical Inheritance, super(), Hybrid Inheritance
Iterators, Iterable, User-defined Iterators, Iterator protocol, Generators, reversing a string, Salient features of a generator function, Generator Expressions
Open file for writing, Checking existence of a given file, writing to a file, Reading from a File, The readline() method, The readlines() method, Implicit method for reading, How the read method worked
Text and Binary Files, File Mode parameters, 5 operations in file handling, The with for File Close, Counting Occurrence of each word in a Text File, Counting Occurrence of alphabets in a Text File
The seek method, Writing to a binary file and reading, Different Programs
Java Script Object Notation (JSON), Serialization and Deserialization, Serializing JSON, Deserializing JSON, writing and then reading a list using JSON, writing and then reading a tuple using JSON, writing and then reading a dictionary using json, writing to a string and then reading from it, The Pickle Solution, advantages and disadvantages
Reading CSV files, Command Line Arguments, File copy from Source to Destination
Exception, Type of standard Exception classes, Custom exceptions, How to Handle Exceptions? Keywords for exception handling, syntax for exception handling, Reading File with exception handling, The finally Keyword, Use of finally, Exception handling in word count program
Catch all, Multiple except program, Use of else, ValueError, using raise for exception, Custom Exception, To know the cause of the Error
Lambda Functions, Parts of lambda functions, Syntax and Examples, Function Expression, Examples of Lambda functions
Module sum.py, Module swap_case, Using interpreter for execution, Module tup_max.py, importing a math function, The main module, Importing multiple modules
Datetime module, Classes to manipulate Date and Time, date today,Date and Time now, To find the day of the week of today in interpreter, strftime function, Finding Elapsed Time, • Perf_counter function, process_time function, perf_counter to find CPU time, Repeated with process_time function
Functional Programming, Filtering elements in containers, Filtering a set, map() function, reduce() function, Features of first class functions, Assigning functions to variables, Function passed as parameters to other functions, Define functions inside other functions - Inner Function
Decorator Function, Example program, Decorator Function with arguments, Case Study, Finding execution time with decorator, Built-in Decorators, Namespace, The hierarchy of namespaces in Python, Example Package, Understanding packages, Creating a package, New program in the old package
Data Structures, Stack example, Stack program, pop from the stack, Queue, simulate queue using deque, read from queue, Case Study - •Exception Handling in Queue,
Algorithm Analysis, Big Oh notation, CASE STUDY - Bubble Sort, Time Complexity of Bubble Sort, CASE STUDY - Selection Sort, How it works? Time Complexity of Selection Sort, CASE STUDY -Insertion Sort, status of the list during Insertion sort at every pass, Time Complexity of Insertion Sort, CASE STUDY - Merge Sort, Example Merge Sort, Time Complexity of Merge Sort, Reply of ChatGPT to my Inquiry
What is Data? Importance of Data, Why Data Collection & Analysis is Important? How Data is used? Data Visualization, Advantages of Data Visualization, Python Libraries for Data Visualization, File formats, Dataset, DataFrame, pandas, Installing pandas, Jupyter Notebook which is part of Anaconda Explorer
Pandas, Reading head() and Tail of csv file, Line Chart, Bar Chart, Bar Chart stacked horizontal, histogram, Box Plot, scatter plot
Three Data Visualization Libraries in Python 3- pandas, matplotlib, seaborn-Finding Tail and column headers, Installing Matplotlib, Scatter Plot using matplotlib, Scatter plot – R&D Spend and Profit, histogram using pandas using wines data, bar chart using pandas and matplotlib using wines data, Installing seaborn, Scatter plot using Seaborn, Countplot and barplot in Seaborn, barplot using seaborn
This comprehensive Python 3 (Core) course is designed to take you from fundamentals to advanced programming through hands-on learning. It includes hundreds of tested programs, 5 practical assignments, and real-world case studies to ensure deep understanding and application.
You will actively code using industry-relevant tools such as IDLE and Jupyter Notebook within Anaconda, enabling you to learn by doing, not just watching.
The course provides in-depth coverage of core programming concepts, including functions, recursion, and tail recursion, along with powerful Python data structures such as lists, tuples, sets, and dictionaries—explained in a clear, engaging, and practical manner.
You will master essential concepts like Unicode (UTF-8), strings, decision-making, and iteration, reinforced through executable examples. The course also demonstrates building a Python-based calculator and using mathematical and standard libraries effectively.
As an object-oriented language, Python enables scalable software development. You will gain a strong understanding of OOP concepts such as inheritance and polymorphism, helping you write reusable and maintainable code.
Robust software must handle unexpected situations. Through practical examples and case studies, you will learn how to manage runtime issues using Python’s exception handling mechanisms.
Discover the true power of Python through its “hidden gems”—including lambda functions, decorators, first-class functions, and function objects—concepts that elevate you from a programmer to a proficient developer.
The course also introduces fundamental data structures, including stacks and queues, along with key sorting techniques widely used in real-world applications.
In today’s data-driven world, visualization is essential. You will learn how to create meaningful insights using libraries like pandas, matplotlib, and seaborn, enabling both descriptive and predictive analysis.
Learning Approach
This course follows a step-by-step, program-driven methodology, where each concept is introduced through carefully designed examples. This ensures that you learn one concept at a time without overload, making even complex topics easy to grasp.
Why This Course?
Learn by writing and executing real programs
Strong focus on clarity + depth
Covers both fundamentals and advanced concepts
deal for students, engineers, and working professionals
Builds a foundation for AI, data science, and software development