Python AI Bootcamp

Course Schedule

Total Duration: 30 hours (6 Weeks, 5 days in a week, 1 hour per day)

Available Class Languages: English, Tamil

Online Class Top 1% community learn from anywhere

Batch Timings: 7AM-8AM or 7PM-8PM

Limited seats: (8–12) | Focused Expert-Led Training

Certification available

Live Session Recording will not be provided

Course Contents

Prerequisites

• → Need a Laptop/Desktop with an internet access
• → Any web browser (Preferably Google chrome web browser)
• → Valid Email ID (Preferably Gmail ID)
• → Notebook and Pen (mandatory)
• → Basic programming language is good to have (Not mandatory)

Session 1: Introduction

• → Why do we need Python?
• → Development Environment setup (python and IDE Installation)
• → Program structure and Execution steps
• → Interactive Shell and Executable or script files
• → User Interface or IDE walk-through, project setup
• → Virtual environment setup

Session 2: Data Types and Operations

• → Numbers
• → Strings
• → List
• → Tuple
• → Dictionary
• → Object creation and deletion
• → Object properties
• → Other Core Types
• → operators (assignment, comparison, bitwise and logical operations)

Session 3: Conditional Statements and Loops

• → Assignments, Expressions, and prints
• → Conditional statement and Syntax Rules (Indentation)
• → While and For Loops
• → Iterations and Comprehension

Session 4: File Operations

• → Opening a file (from and with keyword)
• → Using Files and File Modes
• → context manager

Session 5: Functions

• → Function definition and argument passing
• → Function Scope
• → Function arguments
• → Function Objects
• → Anonymous Functions

Session 6: Classes and Object Oriented Programming (OOPS)

• → Introduction to object oriented programming
• → Classes and instances
• → Classes method calls
• → Inheritance
• → Polymorphism

Session 7: Exception Handling

• → Default Exception Handler
• → Catching Exceptions
• → Raise an exception
• → User defined exception

Session 8: Introduction to Artificial Intelligence

• → Introduction to AI
• → Types of AI and its other categories of AI
• → Computer Vision
• → Machine Learning
• → Deep learning
• → Reinforcement learning
• → chatGPT & Prompting
• → Gen AI - Large language models (LLM)
• → Generate the code using chatGPT

Session 9: Data Science

• → Introduction to data science
• → cleaning and preparing data
• → Statistics in python
• → Understanding data visualization
• → EDA steps
• → Data formatting
• → Data frames
• → Scaling & Data scaling
• → univariate, variable and multivariate analysis

Session 10: Regression, Classification, Clustering Modeling

• → What is regression
• → Multivariate regression
• → Regression evaluation matrix, linear regression
• → Classification modeling and logistic regression

Session 11: NLP, Data Visualization, Feature Selection and Data Fine Tuning

• → What is NLP
• → Data visualization
• → Feature selection and data fine tuning

Session 12: Industry Talk

• → About tech industry and what do they expect from Engineer like you
• → Tech Industry Professional Standards

Session 13: Practical Projects (Activity Happens Throughout The Course)

• → Real time project (Design to implementation)