About the course

Python For AI: is a complete, end-to-end learning program designed to transform you into a high-demand Python coding which is a Pre-requisite for learning AI.

This course is built for beginners, intermediate learners, and working professionals who want to gain hands-on expertise in Coding and also planning to learn AI in future.

Across 9 Weekends, you will learn everything from foundational Programming skills to advanced level including the min-projects and final Major projects, which are mandatory before learning AI.

Here is the Detailed Agenda:

W1 - SAT - The Digital Translator:

The Origin Story

The Legend of Guido van Rossum: How a "hobby" project became the world's #1 language.

Why AI chose Python: The bridge between human thought and machine action.

Setting up the Lab:

Installing the Engine: Python & VS Code/Jupyter Notebook setup.

Your first "Hello World": Breaking the silence between you and the computer.

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W1 - SUN - The Memory Bank (Variables & Data):

Labeling the World

Variables: How Python "remembers" things (The Box Analogy).

Data Types: Distinguishing between Words (Strings), Numbers (Int/Float), and Truths (Booleans).

Conversing with the User

input() and print(): Making your code interactive.

Mini Project #1 : The Personal Profile Generator (Creating a digital business card).

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W2 - SAT - The Rules of Arithmetic:

Digital Math

Arithmetic Operators: Python as your highspeed calculator.

Comparison Operators: Asking the computer "Is this equal?" or "Is that bigger?"

Building Tools

String Formatting: Making outputs look professional.

Mini Project #2 : The Smart Calculator (Handling basic math via user input).

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W2 - SUN - The Crossroads (Decisions):

The if Statement

Making Choices: Helping the program decide which path to take.

Nested Conditions: Decisions within decisions (The "Security Guard" logic).

Real-World Logic

Logical Operators (and, or, not): Complex decision-making.

Mini Project #3 : The ATM Decision System (Verifying PIN and Balance).

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W3 - SAT - The Infinite Assistant (Loops): 

The for Loop

Iteration: How to do a task 100 times without breaking a sweat.

Range & Lists: Stepping through a sequence.

The while Loop

Conditional Repetition: Running until a specific goal is met.

Break & Continue: How to interrupt a cycle.

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W3 - SUN - Automation in Action: 

Practical Automation

Automating Attendance: Processing a list of names.

Salary Slip Generation: Calculating monthly pay for multiple employees.

Project Lab

Mini Project #4 : The Attendance Automator (Looping through students to mark presence).

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W4 - SAT - The Magic Spells (Functions): 

Defining Actions

Creating your own "Commands": Reusable blocks of code.

Parameters: Passing information into your "Magic Spell."

Giving Back

The return keyword: Getting results back from a function.

Scope: Why some variables stay "private" inside functions.

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W4 - SUN - Advanced Functionality: 

Efficiency Hacks

Lambda Functions: The "Short-hand" way of coding logic.

Built-in Functions: Leveraging Python's secret library of tools.

Project Lab

Mini Project #5 : The Universal Utility App (Tax calculation and Discount functions).

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W5 - SAT - Collection Mastery (Lists & Tuples):

The List

Indexing & Slicing: Grabbing specific items from a group.

List Methods: Adding, removing, and sorting your data.

The Tuple

Immutable Data: When you want to lock your data in place.

Packing & Unpacking data.

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W5 - SUN - The Data Vault (Dictionaries & Sets): 

Key-Value Pairs

Dictionaries: Mapping "Name" to "Phone Number" or "Product" to "Price."

Sets: Handling unique items and removing duplicates.

Project Lab

Mini Project #6 : Student Management System (Storing and retrieving details using Dictionaries).

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W6 - SAT - Persistent Memory (File Handling):

Reading & Writing

The open() function: Interacting with .txt files.

Saving Progress: Writing user data to a permanent file.

Structured Data

Introduction to CSVs: The bridge between Python and Excel.

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W6 - SUN - The Safety Net (Exception Handling):

Managing Errors

try and except: Preventing your app from "crashing."

Handling Missing Files: What to do when a file isn't there.

Project Lab

Mini Project #7 : Employee Record Storage (Saving records to a file with error protection).

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W7 - SAT - NumPy - Power in Numbers:

The Matrix Era

Why NumPy? Moving beyond standard lists to high-speed arrays.

Creating Arrays: 1D, 2D, and beyond.

Array Operations

Vectorization: Doing math on 1,000 numbers at once.

Statistical Functions: Mean, Median, and Standard Deviation.

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W7 - SUN - Data as Dimensions:

Slicing the Matrix

Advanced indexing for AI data.

Reshaping Data: Preparing data for Machine Learning.

Project Lab

Mini Project #8 : Student Marks Analyzer (Performance statistics for a whole class).

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W8 - SAT - Pandas: - The Spreadsheet Killer:

The DataFrame

Loading Reality: Importing CSV and Excel files into Python.

Inspection: Looking at the "Head," "Tail," and "Info" of your data.

Data Cleaning

Filtering: Finding specific rows (e.g., "All sales > $500").

Sorting and Selecting columns.

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W8 - SUN - Wrangling Data:

Grouping & Aggregating

Pivot tables in Python: groupby() and sum().

Handling Missing Values: Filling the gaps in messy data.

Project Lab

Mini Project #9 : Sales Data Dashboard (Analyzing monthly trends and best products).

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W9 - SAT - Visualizing the Truth:

The Canvas (Matplotlib)

Line Charts and Bar Graphs: Visualizing growth.

Pie Charts and Histograms: Visualizing distribution.

Beautiful Insights (Seaborn)

Heatmaps: Seeing patterns in data "temperature."

Customizing Plots: Adding colors, labels, and legends.

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W9 - SUN - The Grand Finale:

The Graduation Project:

Business Growth Report: A full-end-toend analysis from a CSV file to a visual presentation.

The AI Frontier

Where to go next? (Scikit-Learn, Deep Learning, and Career paths).

Certification & Wrap-up.

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