Comprehensive Python installation guide across Windows, Linux, and Mac.

Setting up the environment path for seamless execution.

Key Python features: simplicity, versatility, cross-platform.

Declaring and managing variables effectively.

Mastering input/output methods and Python imports.

Why Python is essential in 2025 for automation, AI, and web development.

Industries and companies using Python today.

Introduction to core data types: integers, floats, strings, booleans, and complex numbers.

Advanced collections: tuples, lists, dictionaries, sets.

Arrays: importing and managing using Python's array module.

Manipulating strings and slices.

Handling dates, performing math, generating random values, and performing statistical operations.

Extracting data from PDFs.

Introduction to the CSV module for reading and writing.

Introduction and use cases for immutable tuples.

Tuple operations, slicing, and functions.

Tuple methods for practical data handling.

Creating dynamic Python lists.

List manipulation, sorting, appending, and slicing.

Built-in methods and functions for advanced list operations.

Introduction to unique data collections with sets.

Performing union, intersection, and difference.

Set methods for data comparison and filtering.

Conditional logic: if, else, elif.

Looping structures: for, while, break, continue, pass.

Efficient looping techniques with list comprehensions and enumerate.

Declaring functions and using return values.

Positional, keyword, and default arguments.

Anonymous and lambda functions.

Recursion, global/local scope, modules, and package creation.

Reading and writing text, CSV, and binary files.

Manipulating file pointers and handling file operations.

File attributes and working with directories.

Structured try, except, finally blocks.

Try-else constructs.

Creating and managing custom exceptions.

Real-world application of OOP in Python.

Classes, objects, and access specifiers.

Method overloading, overriding, inheritance, abstraction, and encapsulation.

Self-keyword and property decorators.

Leveraging the OS module for environment variables and paths.

File system interactions and date/time manipulations.

Creating threads using the threading module.

Synchronization and thread-safe operations.

Thread priorities and queues.

Mastering pattern matching and string searching.

Parsing logs and real-time data using regex.

Input validation using regular expressions.

Introduction to NumPy
Learn array creation, indexing, slicing, reshaping, and broadcasting for numerical computations.

Mathematical and Statistical Operations in NumPy
Perform operations like mean, median, standard deviation, and matrix operations.

Pandas Data Structures
Work with Series and DataFrames, essential for data manipulation and cleaning.

Reading/Writing Data using Pandas
Import and export data from CSV, Excel, JSON, and databases.

Data Cleaning and Preparation
Handle missing values, filter and sort data, merge and join datasets.

Data Aggregation and Grouping
Use groupby(), pivot_table(), and aggregation functions for summarizing datasets.

Time Series Analysis
Handle time-indexed data, resample and perform rolling statistics.

Introduction to Data Visualization
Understand the role of data visualization in exploratory data analysis.

Creating Basic Plots with Matplotlib
Learn to build line, bar, scatter, and histogram charts with customization options.

Advanced Visualization with Seaborn
Create statistical visualizations like box plots, heatmaps, violin plots, and pair plots.

Plot Customization
Enhance visual appeal with labels, legends, grids, and custom color palettes.

Saving and Exporting Charts
Save plots in different formats (PNG, PDF, SVG) for reports and dashboards.

Tableau Fundamentals
Introduction to Tableau dashboards, connecting to data sources, and creating visualizations.

Power BI Basics
Explore Power BI Desktop, work with Power Query, and create interactive reports and dashboards.

Excel for Data Analysis
Use formulas, pivot tables, charts, and conditional formatting for advanced Excel analytics.

Integrating Python with BI Tools
Learn how to use Python scripts within Power BI and Excel for advanced data processing and automation.