Course Schedule
Total Duration: 20 hours (4 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
Live Hands-on Coding & Debugging
Certification available
Live Session Recording will not be provided
Course Contents
⚠️ Important: This is NOT a beginner Python course. Participants should know basic Python syntax.
Target Audience
- → Working engineers (1-8 years experience)
- → Professionals who want to boost productivity with AI tools
- → Engineers preparing for modern AI-assisted interviews
Course Outcomes
By the end of 4 weeks, you will:
- → Write Python code 2× faster using AI tools
- → Debug and refactor confidently
- → Know how to explain AI-assisted code in interviews
- → Avoid common Copilot/ChatGPT mistakes
- → Stay relevant in an AI-assisted development world
Week 1 – Python Foundations (Fast Refresh, Interview Angle) & Problem Solving + AI Assistance
Goal: Remove weak basics that slow engineers down & Teach WHEN and HOW to use AI
Topics:
- → Writing clean Python (functions, loops, dict usage)
- → Common mistakes engineers still make
- → Thinking before coding (approach first)
Problems:
- → Frequency counting
- → String processing
- → Simple data transformations
AI Usage:
- → Using ChatGPT to review your logic
- → Asking AI for edge cases, not full solutions
- → Problem-solving patterns
- → Brute force vs optimized logic
- → Time complexity intuition
Problems:
- → Non-repeating character
- → Move zeros to end
- → Second largest element
AI Usage:
- → Prompting AI for approach validation
- → Asking AI to optimize your solution
- → Comparing human vs AI logic
Week 2 – AI Copilot for Daily Python Work & Debugging, Refactoring & Safety
Goal: Real productivity, not AI hype & Prevent blind AI dependency
Topics:
- → Using Copilot / ChatGPT for boilerplate code
- → Using Copilot / ChatGPT for refactoring
- → Using Copilot / ChatGPT for writing functions faster
- → Reading AI-generated code critically
Live Demos:
- → Convert requirement → code using AI
- → Clean messy code using AI suggestions
Key Rule: "AI suggests. YOU decide."
- → Debugging AI-generated code
- → Identifying wrong logic
- → Handling edge cases AI misses
- → Security & correctness basics
Problems:
- → Buggy scripts
- → Incorrect AI solutions (intentional traps)
Interview Angle: "How do you validate AI-generated code?"
Week 3 – Interview Readiness with AI
Goal: Use AI without getting rejected
Topics:
- → How interviewers view AI usage
- → Explaining your logic when AI helped
- → Writing code live without Copilot
Practice:
- → Solve problem manually
- → Improve with AI
- → Explain final solution confidently
Week 4 – Mock Interviews + Real-World Scenarios
Goal: Confidence + clarity
Activities:
- → Mock technical interviews
- → Resume-based Python discussion
Feedback on:
- → Clarity
- → Confidence
- → AI dependency level
Final Guidance: How to continue learning with AI responsibly
