
Declare variables and manage data types such as integers, floats, booleans, and strings to store data during Python-based processing.
a sample code file "Arithmatic_practice.py" is also shared which can be used as a sample reference
Explore how to use escape characters in Python to include quotes and control string formatting, using backslashes for new lines, tabs, and other escapes like \n, \t, and \r.
Understand how the while loop runs until a condition is met, using a counter starting at zero, incrementing to print 0 through 4, and including an else clause after completion.
Explore how decorators in Python modify or extend function behavior, using a logger wrapper to log details and then call the original function.
Explore how a child class inherits attributes and methods from a parent class in Python. The example with the human and African human demonstrates a constructor and the speak method.
Define a Python module by saving code in a .py file and import it into other programs. Use PyCharm to create mymodule.py and access its objects with Mymodule.run.
Examine the basics of machine learning within artificial intelligence. See how input plus sample output guides predictions, data prep, and 80% training 20% validation with scikit learn.
Analyze daily attendance data, replace alphabets with numbers to enable machine learning, and split 80/20 for training and testing using pandas and scikit-learn components.
Learn to build a simple machine learning model using sklearn classification, fit and predict, and evaluate with mean absolute error and root mean square error to achieve about 67% accuracy.
This course is specially designed for students eager to learn the Python programming language and foundational concepts of machine learning . Whether you're a complete beginner or looking to strengthen your programming skills, this course provides a comprehensive introduction to Python and essentials of machine learning , offering practical experience, hands-on coding exercises, and the opportunity to develop a strong foundational understanding of key concepts to advance your learning journey.
What You'll Learn:
Python Programming Basics
Overview of Python Programming Language
Step-by-step Installation Guide for Beginners
Variable Declaration and Type Casting
Arithmetic Operations
String Operations
String Formation and Concatenation
Paragraph and Substrings
Case Conversion
Escape Characters
Control Flow: Conditional Statements:
If condition ,Elif condition ,Else condition
Data Structures: Python's Core Collection Objects:
Lists
Tuples
Sets
Dictionaries
Loops
For Loop
While Loops
Functions
Functions and Arguments
Advanced Functionality: Decorators
Object-Oriented Programming (OOP)
Classes and Objects
Inheritance and Multiple Inheritance
Modularity and Reusability
Creating and Using Modules
Machine Learning Essentials
Introduction to Machine Learning Concepts
Overview of Essential ML Libraries
Hands-on Coding Exercise with a Simple Dataset
This course provides a solid foundation in Python programming and a walkthrough of essential machine learning techniques and algorithms, empowering you to start building your own machine learning projects!