GitHub Copilot & ChatGPT for Developers
1 Introduction to ChatGPT (Developer Perspective)
What ChatGPT Can Do
Generate code from natural language
Explain unfamiliar code
Debug errors
Refactor code
Write tests & documentation
What ChatGPT Cannot Reliably Do
Guarantee correctness
Replace design thinking
Understand hidden system context
📌 Tip: Emphasize AI as a co-pilot, not an autopilot
2 Prompt Engineering for Developers
Prompt Types
Instructional: “Write a Python function to…”
Contextual: “You are a backend engineer…”
Iterative: “Improve the previous solution by…”
Constraint-based: “Use only standard libraries…”
Prompt Components
Role
Task
Context
Constraints
Output format
Bad Prompt
Write code to sort data
Prompt 2: Write SQL query to select 10 records from products table
Good Prompt
You are a Python developer. Write a function to sort a list of dictionaries by price in descending order. Handle missing keys gracefully.
Ask questions before starting the work. do not assume anything implicitly
3 Hands-on: ChatGPT Coding Scenarios
Activity 1: Code Generation
Ask ChatGPT to:
Create a number guessing game
Build a REST API skeleton
Write a data validation function
Activity 2: Code Explanation
- Paste unfamiliar code
def process_numbers(numbers):
result = []
for n in numbers:
if n % 2 == 0:
result.append(n ** 2)
else:
result.append(n ** 3)
return result
Explain this Python code line by line.
Assume I am a beginner and also explain why this logic might be useful.
Activity 3: Debugging
def calculate_average(numbers):
total = 0
for i in range(len(numbers)):
total = total + numbers[i]
average = total / len(numbers)
return avg
The following Python code throws an error.
Identify the issue, explain why it happens, and provide the corrected code.
Follow-up prompt
Improve this code using Python best practices.
· ChatGPT as a code explainer
· ChatGPT as a debugging assistant
4 Free ChatGPT Alternatives
Google Gemini – reasoning + search
Microsoft Copilot – enterprise & M365
Claude – long context, safer responses
5 Introduction to GitHub Copilot
What Copilot Is
AI pair programmer inside IDE
Context-aware code completion
Capabilities
Inline suggestions
Comment-based prompting
Copilot Chat
Test generation
6 Prompting with GitHub Copilot
Inline Prompting
# Write a Python function to check if a number is prime
Comment-Driven Design
# Game: Player vs Computer
# Rules:
# - Guess a number between 1 and 100
# - Provide hints
7 Rules for Effective Prompts (Copilot & ChatGPT)
Be explicit
Add constraints
Describe intent, not syntax
Iterate, don’t expect perfection
Always review output
8 Hands-on: Game Scenario (Language-agnostic)
Task
Build a simple game:
- Guess the number / Tic-Tac-Toe / Dice game
Use:
ChatGPT for logic
Copilot for implementation
Outcome
Participants experience:
AI-assisted design
Faster coding
Reduced boilerplate work
9 Module 1 Takeaways
Prompt quality = output quality
ChatGPT excels at reasoning & explanation
GitHub Copilot excels at in-IDE productivity
Developers remain accountable for correctness
