Professional Certification in Data Engineering & GenAI

Introduction to Python & Its Objects

• What is Python?
• History of Python and creator Guido van Rossum
• Why Python is popular
• Applications of Python (Data Science, AI, Web, Automation)
• Python vs other languages
• Writing the first program (Hello World)
• Python syntax basics
• Comments in Python
• Indentation rules
• Variables in Python
• Naming rules
• Basic data types – int, float, str, list, dict, tuple, set, None, Bool

Operators in Python – 1

• Arithmetic operators
• Comparison operators
• Assignment operators
• Membership and identity operators
• Data Handling in int, Str
• Indexing & Slicing in strings

Operators in Python – 2

• Basic operations on list
• Complex List Handling
• Basic operations on tuple
• Complex tuple Handling
• Basic operations on dict
• Complex Dict Handling

Python Built-in functions

• Introduction to Set, None and Bool Objects
• Built-in functions in Python
• input(), len(), type(), abs(), pow(), min(), max(), sum(), range(),
• enumerate(), zip(), map(), filter(), sorted(), reversed(), all(), any(), id(), help(), dir(), isinstance().

Conditonal Statement in Python

• Introduction to Conditional Statements
• if Statement
• if-else Statement
• if-elif-else Statement
• Nested if Statements
• Comparison Operators in Conditions
• Logical Operators (and, or, not)
• Practical Examples of Conditional Statements

Loops in Python – While

• Introduction to while Loop
• Syntax of while Loop
• Flow of Execution in a while Loop
• Using Conditions in while Loop
• Infinite while Loop
• Using break with while Loop
• Using continue with while Loop
• Using pass in while Loop
• While Loop with else Statement
• Nested while Loops

Loops in Python – for

• Introduction to for Loop
• Syntax of for Loop
• Iterating Over a Sequence
• Using range() with for Loop
• Iterating Over Strings
• Iterating Over Lists, Tuples, and Sets
• Iterating Over Dictionaries
• Nested for Loops
• Using break with for Loop
• Using continue with for Loop
• Using pass with for Loop
• Else with for Loop

Comprehension in Python

• Introduction to Comprehensions
• List Comprehension
• Syntax of List Comprehension
• Conditional List Comprehension
• Nested List Comprehension
• Dictionary Comprehension
• Set Comprehension
• Generator Expressions

User Defined Function

• Introduction to User Defined Functions
• Defining a Function using def
• Calling a Function
• Function Parameters and Arguments
• Default Parameters
• Keyword Arguments
• Return Statement
• Multiple Return Values
• Scope of Variables (Local vs Global)
• lambda function

Python object functions

• str – lower(), upper(), strip(), replace(), split(), join(), find(), startswith(), endswith(), count(), capitalize(), title(), swapcase(), isdigit(), isalpha(), isalnum()
• list -m append(), extend(), insert(), remove(), pop(), clear(), index(), count(), sort(), reverse()
• tuple – count(), index()
• dict – keys(), values(), items(), get()

File Handling in Python

• Introduction to File Handling
• Opening a File (open())
• File Modes (r, w, a)
• Reading from a File (read(), readline(), readlines())
• Writing to a File (write(), writelines())
• Closing a File (close())
• Using with Statement for File Handling
• Working with Text Files

Object Oriented Python – 1

• Introduction to Object-Oriented Programming
• Classes and Objects
• Creating a Class & Objects
• __init__() Constructor Method
• Instance Variables and Methods
• Class Variables and Methods
• Encapsulation & Abstraction

Object Oriented Python – 2

• Inheritance
• Method Overriding
• Polymorphism
• Special (Magic/Dunder) Methods
• Exception Handling using try and Except

Python Built in Modules

• Introduction to Python Built-in Modules
• Importing Modules (import, from, as)
• Exploring Modules using dir()
• The math Module
• The datetime Module
• The os Module
• The logging Module

Data Handling with Python (numpy)

• Introduction to NumPy
• Installing and Importing NumPy
• Creating NumPy Arrays
• Array Attributes (shape, size, dtype)
• Indexing and Slicing Arrays
• Array Operations and Arithmetic
• Broadcasting in NumPy
• Reshaping Arrays (reshape(), resize())
• Aggregation Functions (sum(), mean(), min(), max())
• Mathematical Functions in NumPy
• Random Number Generation
• Working with Multi-dimensional Arrays
• Saving and Loading NumPy Arrays

Data Handling with Python (pandas) – 1

• Introduction to Pandas
• Installing and Importing Pandas
• Pandas Series
• Handling Pandas Series
• Pandas DataFrame
• Handling Pandas DataFrane
• Accessing Dataframes
• Reading Data from CSV, Excel, and JSON Files
• Writing Data to Files

Data Handling with Python (pandas) – 2

• Data Selection and Filtering
• Handling Missing Values
• Data Cleaning and Transformation
• Sorting and Ranking Data
• Grouping and Aggregation (groupby())
• Merging and Joining DataFrames
• Basic Data Analysis and Summary Statistics

Data Analysis with Python (matplotlib)

• Introduction to Matplotlib
• Installing and Importing Matplotlib
• Understanding pyplot Module
• Creating Basic Plots
• Line Plot
• Bar Chart
• Histogram
• Scatter Plot
• Pie Chart
• Customizing Plots (Title, Labels, Legends)
• Formatting Axes and Ticks
• Multiple Plots in One Figure
• Subplots
• Grid and Style Customization