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Python Course

Skillama course

Python Course

Learn Python from scratch with AI-powered guidance.

Overview

This course introduces learners to Python programming through hands-on instruction covering essential language constructs, data types, and control flow. It progresses into more advanced topics such as data structures, object-oriented programming, and integration with popular scientific and data analysis libraries. Learners will gain practical experience through exercises and a final project involving a vehicle rental system.

Objectives

  • Understand Python fundamentals including variables, data types, operators, and control flow structures.
  • Work with core data structures such as lists, tuples, sets, and dictionaries effectively.
  • Apply object-oriented programming principles like classes, objects, and inheritance.
  • Use libraries like NumPy, Pandas, SciPy, and Matplotlib for scientific computing and data visualization.

Key topics

  • Python Language Basic Constructs
  • Control Flow and Looping
  • Data Structures (Lists, Tuples, Sets, Dictionaries)
  • Object-Oriented Programming Concepts
  • File Handling and Exception Management
  • NumPy, SciPy, Pandas, and Matplotlib for Data Science

Expected outcomes

  • Write and execute basic Python scripts that manipulate data and perform calculations.
  • Create and manage structured data using lists, tuples, sets, and dictionaries.
  • Build simple programs using loops, conditionals, functions, and file handling techniques.
  • Develop a functional mini-project demonstrating knowledge of Python concepts and libraries.

How the AI Tutor can help

How the Skillama AI Tutor helps with the listed lectures: explanations, follow-up questions, and running or debugging practice code.

Who this is for

This course is for beginners who want to learn Python programming from the ground up.

Curriculum

  1. 1. Python Environment Setup & Essentials

    • Introduction to Python
    • Features & Advantages of Python

  2. 2. Python Language Basic Constructs

    • Running Python Scripts (commenting)
    • Built-in Data Types (int, float, str, bool, list, tuple, dict, set)
    • Variables & Constants
    • Type Casting & Type Checking
    • Working with Strings (str operations, slicing, formatting)
    • Python Predefined function

  3. 3. Operators in Python

    • Arithmetic Operators
    • Comparison Operators
    • Assignment Operators
    • Logical Operators
    • Bitwise Operators
    • Membership Operators
    • Identity Operators

  4. 4. Lists in Python

    • Introduction to Lists
    • Creating the list with int,str,float
    • Append
    • append 2nd example
    • Extend
    • del
    • pop
    • In
    • not in
    • reverse
    • sorting
    • sorting 2nd example
    • list slicing
    • indexing
    • List Slicing & Comprehension
    • List extending using “+”.
    • list count
    • Iterating through Lists
    • List looping
    • List Comprehensions
    • 2nd example on list comprehension
    • With comprehension
    • List Methods and Functions

  5. 5. Tuples in Python

    • Introduction to Tuples
    • Creating and Accessing Tuples
    • Creating the tuple
    • Tuple Unpacking
    • Tuple Operations
    • Nested tuple
    • tuple is immutable
    • tuple updation by converting it into list
    • string element is also immutable
    • concatenation in tuple
    • repeat the element in tuple using operator
    • Tuple deletion
    • Tuple count
    • Tuple indexing
    • Tuple membership (in)
    • Tuple length
    • Tuple sort
    • max

  6. 6. Sets & Frozen Sets

    • Introduction to Sets and Frozensets
    • Creating Sets and Frozensets
    • Set Operations (union, intersection, difference)
    • it does not hold duplicate record
    • Create the set from list
    • creating the set using set method
    • add & update in set
    • Update the set based on index
    • Discard
    • 2nd example on discard
    • Pop function in set
    • clear
    • Union, intersection and difference
    • symmetric operation
    • issubset, issuperset
    • Frozen Sets

  7. 7. Dictionaries in Python

    • Introduction to Dictionaries
    • Dictionary Methods
    • Nested Dictionaries
    • Iterating over Dictionaries
    • Creating the empty dictionary
    • creating the dict with unique key element
    • 2nd example on creating the dict
    • creating the dictionary using dict function
    • Get method
    • Add or modify the data
    • Delete or remove data
    • Pop item
    • Delete operation
    • Clear operation
    • 2nd example on delete operation
    • Copy function
    • Dict.fromkeys
    • Item function
    • Key function
    • Value function

  8. 8. Program Control Flow

    • Conditional Statements (if, if-else, if-elif-else)
    • If statement
    • 2nd example on if statement
    • Else statement
    • Even or odd number
    • If,elif,else statement
    • 2nd example on elif statement
    • Nested if statement
    • Using logical operator
    • Looping Constructs
    • For loop
    • 2nd example on for loop
    • Getting the range values using for loop
    • 2nd example on range values using for loop
    • For loop with else
    • Prime number using for loop
    • While loop
    • 2nd example on while loop
    • Prime number using while loop
    • break, continue, and pass Statements
    • Break statement
    • Prime no. using break statement
    • Pass statement
    • Continue statement
    • Printing even number using continue statement
    • Looping with range()

  9. 9. NumPy for Mathematical Computing

    • Introduction to NumPy Arrays
    • Creating and Modifying Arrays
    • Mathematical Operations with NumPy
    • Array Indexing, Slicing, and Reshaping
    • Importing numpy and creating array
    • Creating the array
    • Print dimension
    • Multidimensional
    • Using array function
    • ones array
    • eye
    • 2nd example on eye
    • diag
    • arange function
    • 2nd example on arange function
    • complex data types
    • Boolean data type
    • indexing
    • for multidimensional arrays indexing

  10. 10. SciPy for Scientific Computing

    • Introduction to SciPy
    • Functions Built on NumPy
    • Linear Algebra (linalg), Signal Processing, Optimization
    • Applying Bayes’ Theorem with SciPy

  11. 11. Matplotlib for Data Visualization

    • Introduction to Matplotlib
    • Different types of plot (plot(), bar(), hist())
    • Customizing Graphs (Labels, Titles, Legends)
    • Subplots and Multi-plotting
    • Special Plot Types & Styling
    • plot
    • Bar plot
    • Hist
    • Customizing Graphs: Labels, Titles, and Legends
    • Subplots and Multi-plotting

  12. 12. Pandas for Data Analysis & Machine Learning

    • Introduction to Pandas DataFrames
    • Importing Data from JSON, CSV, Excel, SQL Databases
    • Data Cleaning & Transformation
    • Data Aggregation & Grouping
    • Importing pandas
    • NaN
    • describe()
    • Max
    • min

  13. 13. Object-Oriented Programming (OOP)

    • Introduction to OOP in Python
    • Classes and Objects
    • Constructors (__init__ method)
    • Inheritance (Single, Multiple, Multilevel)
    • Creating function
    • formal arguments
    • 2nd example on formal arguments
    • 3rd example on formal arguments
    • 4th example on formal argument
    • Print statement
    • Return statement
    • Local variable
    • Global variable
    • Pass statement
    • Positional statement
    • Variable Length Arguments
    • Keyword Variable Length Arguments
    • Lamda
    • 2nd example on lamda
    • Creating child class
    • Inheritance
    • Multiple inheritance

  14. 14. File Handling in Python

    • Reading and Writing Files (open, read, write)
    • Working with CSV Files (csv module)
    • Handling JSON Files (json module)
    • Exception Handling (try-except-finally)
    • Open a file
    • Closing a file
    • Writing file
    • Reading file
    • 2nd example on reading file
    • seek
    • readline
    • rename
    • remove
    • to get the current directory
    • List of file and directory
    • Python Error & In built Exception Handling
    • Catching exception in python
    • Catching Specific Exception
    • Raising exception
    • try finally

  15. 15. Python Modules & Packages

    • Importing Built-in and External Modules
    • Creating Custom Modules
    • Using pip to Install Packages
    • Virtual Environments (venv, conda)
    • lib is set of module
    • math
    • datetime
    • Importing with rename

  16. 16. Project Control Flow

    • Writing Your First Python Program
    • Writing Functions (with and without Parameters)
    • Using Lambda Expressions
    • Creating a Class, Object, and Methods
    • Writing for Loops in Object-Oriented Programming

  17. 17. Mini Project

    • Vehicle Rental System
    • Customer Registration
    • Vehicle Management
    • Vehicle Booking
    • Rental & Return
    • Rental Charge Calculation
    • Bill Generation
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