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@dhanachavan
Last active December 1, 2025 14:31
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A comprehensive list of resources to get started with GitHub Copilot for students and educators

🆕 Latest GitHub Copilot Resources (2025)

Tutorials

🧠 Agent Mode & Coding Agent

Custom Agents

🔐 Security & Open Source

🧰 Tools & Learning

📝 Blog Posts

🎥 Videos

Industry Case Studies

Mercedes Benz and GitHub - https://youtu.be/pmoG7pLpAAU?si=1pymg2jpADtHh_YI

🧑‍💻 Open Source Contribution Prompt

Prompt Copilot: “I am a X level developer passionate about X. Find a list of good first issues in open source projects for me to contribute to.”

How GitHub Copilot Helps with Programming Challenges

Challenge How GitHub Copilot Helps Sample GitHub Copilot Prompt
Learning new programming languages Autocompletes language syntax, suggests idiomatic examples, and explains code snippets in comments. "Explain how memory management works in C, including malloc, calloc, realloc, and free"
Keeping up with new libraries, frameworks, or APIs Suggests up-to-date usage patterns, code samples, and best practices for the latest libraries or APIs. "Show how to use the latest version of Pandas to merge two DataFrames on a common column."
Prototyping new algorithms or testing different research approaches Generates boilerplate code for algorithms, helps rapidly test different approaches, and accelerates iteration. "Implement k-means clustering in Python and plot the results using matplotlib."
Collaboration Difficulties Suggests code comments, docstrings, and documentation to improve clarity and team communication. "Generate a usage example for this API to help new lab members onboard quickly”
Repetitive tasks like data cleaning, formatting etc Automates repetitive data wrangling, formatting, and processing tasks, saving time and reducing errors. "Write a Python function to remove duplicate rows and fill missing values in a CSV file using Pandas."
Obtaining suitable, high-quality datasets for research and development GitHub Copilot can automatically generate scripts to create realistic synthetic datasets in various formats (e.g., CSV, JSON), tailored to research needs (such as healthcare, finance, or engineering). It can consider constraints like plausible value ranges, unique identifiers, time periods, and categorical distributions, saving time and reducing manual coding errors. This accelerates experimentation and enhances the quality and relevance of research outcomes. “Generate a sample CSV file with realistic test data for a healthcare system. The CSV should include PatientID, Name, Age, Gender, Diagnosis, AdmissionDate, DischargeDate, and TreatmentCost. Generate 100 test patient records with IDs like P000001, realistic Bangalore names, ages 18-90, random genders, common diagnoses, 2025 admission dates, 1-30 day stays, and costs 50,000–10,00,000 INR.”
Improving Code Quality and Documentation Provides suggestions for type hints, refactoring, better naming, and writing clear documentation. "Refactor this function to improve readability and add type hints and docstrings in Python."
@amit09-bot
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Brilliant explaintion and best way to understand the code easily by the usage of Copilot

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