𝗛𝗼𝘄 𝘁𝗼 𝗽𝗿𝗼𝗺𝗽𝘁 𝗶𝗻 𝗖𝗵𝗮𝘁𝗚𝗣𝗧, 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝗮𝗻𝗱 𝗚𝗲𝗺𝗶𝗻𝗶 𝗶𝗻 𝟳 𝘀𝘁𝗲𝗽𝘀

1. Assign personas
2. Define your task
3. Set the tone
4. Break it down
5. Format and limits
6. Provide examples
7. Refine the prompt

The Ultimate ChatGPT Prompting Hack 🤯

This Ultimate Cheat Sheet Will Transform the Way You Use ChatGPT Forever.

Learn How to Act as Any Expert, Create Any Content, and Format It Perfectly.

💡 8 DeepSeek prompts for quick learning

Free Artificial Intelligence Courses
👇👇
https://academy.openai.com/public/content

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Here are 10 ChatGPT-4o Prompts you need to know to Dominate and Excel at any job interview:

1. Developing STAR Method Responses:

Help me craft a STAR (Situation, Task, Action, Result) response to the interview question: [INSERT QUESTION] for the [JOB TITLE] role. Ensure the response is clear, concise, and demonstrates my impact in previous roles.

2. Mock Interview Practice:

Create a mock interview scenario for the [JOB TITLE] role at [SPECIFIC COMPANY]. Include 5 common and challenging questions I might face, and provide guidance on how to answer each effectively.

3. Overcoming Weaknesses:

How should I address the common interview question: 'What is your greatest weakness?' in the context of a [JOB TITLE] role in [SPECIFIC INDUSTRY]? Provide a response that turns the weakness into a positive aspect.

4. Negotiating Salary:

How should I approach salary negotiations for a [JOB TITLE] role at [SPECIFIC COMPANY]? Please provide a script or key points to emphasize based on industry standards and my qualifications.

ChatGPT PROMPTS Series

5. Post-Interview Follow-Up:

What is the best way to follow up after an interview for the [JOB TITLE] role at [SPECIFIC COMPANY]? Based on our discussion about [specific project, skill, or topic discussed during the interview], draft a professional and personalized thank-you email that not only reiterates my enthusiasm for the role but also highlights how my experience in [specific relevant experience or achievement] can directly contribute to the success of [SPECIFIC COMPANY]

6. Showcasing Soft Skills:

How can I effectively highlight my soft skills, such as communication and teamwork, during an interview for the [JOB TITLE] role in [SPECIFIC INDUSTRY]? Please provide examples and scenarios that demonstrate these skills in action.

7. Dealing with Gaps in Employment:

What is the best way to follow up after an interview for the [JOB TITLE] role at [SPECIFIC COMPANY]? Considering our discussion on [specific topics discussed during the interview], craft a professional and thoughtful thank-you email that reiterates my interest, highlights key points from our conversation, and emphasizes how my background in [specific skills or experiences] aligns with the company’s needs.

8. Handling Behavioral Questions:

How can I best respond to behavioral interview questions for a [JOB TITLE] role? Given my experience in [specific past role or project], provide strategies and examples to answer questions about teamwork, conflict resolution, and leadership.

9. Dealing with Gaps in Employment:

How should I address gaps in my employment history during an interview for the [JOB TITLE] position in [SPECIFIC INDUSTRY]? Considering that during this period I [explain what you did: pursued education, volunteered, freelanced, etc.], provide a response that explains the gaps positively and focuses on what I’ve learned during that time.

10. Explaining Career Transitions:

How can I effectively explain a career transition to [JOB TITLE] in [SPECIFIC INDUSTRY] during an interview? Given my background in [previous industry or role] and my recent [relevant education, certification, experience], provide a narrative that connects my previous experiences to the new role, highlighting transferable skills and relevant achievements.

#ChatGPT

Python For Everything!🐍

Python, the versatile language, can be combined with various libraries to build amazing things:🚀

1. Python + Pandas = Data Manipulation
2. Python + Scikit-Learn = Machine Learning
3. Python + TensorFlow = Deep Learning
4. Python + Matplotlib = Data Visualization
5. Python + Seaborn = Advanced Visualization
6. Python + Flask = Web Development
7. Python + Pygame = Game Development
8. Python + Kivy = Mobile App Development

#Python

10 Python Libraries Every AI Developer Should Know

✅ NumPy – Foundation for numerical computing in Python
✅ Pandas – Data manipulation and analysis made easy
✅ Scikit-learn – Powerful library for classical ML models
✅ TensorFlow – End-to-end open-source ML platform by Google
✅ PyTorch – Deep learning framework loved by researchers
✅ Matplotlib – Create stunning data visualizations
✅ Seaborn – High-level interface for drawing statistical plots
✅ NLTK – Toolkit for working with human language data (NLP)
✅ OpenCV – Real-time computer vision made simple
✅ Hugging Face Transformers – Pretrained models for NLP, CV, and more

React with ❤️ for more

10 New & Trending AI Concepts You Should Know in 2025

✅ Retrieval-Augmented Generation (RAG) – Combines search with generative AI for smarter answers
✅ Multi-Modal Models – AI that understands text, image, audio, and video (like GPT-4V, Gemini)
✅ Agents & AutoGPT – AI that can plan, execute, and make decisions with minimal input
✅ Synthetic Data Generation – Creating fake yet realistic data to train AI models
✅ Federated Learning – Train models without moving your data (privacy-first AI)
✅ Prompt Engineering – Crafting prompts to get the best out of LLMs
✅ Fine-Tuning & LoRA – Customize big models for specific tasks with minimal resources
✅ AI Safety & Alignment – Making sure AI systems behave ethically and predictably
✅ TinyML – Running ML models on edge devices with very low power (IoT focus)
✅ Open-Source LLMs – Rise of models like Mistral, LLaMA, Mixtral challenging closed-source giants

Free AI Resources: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y

ENJOY LEARNING 👍👍

10 AI Tools Every Developer Should Try

✅ GitHub Copilot – Your AI coding buddy that completes code in real-time
✅ Codeium – A free AI autocomplete alternative to Copilot
✅ Amazon CodeWhisperer – AI suggestions optimized for AWS developers
✅ Cursor – An AI-first code editor built on VS Code
✅ Polycoder – Open-source AI that understands multiple programming languages
✅ Blackbox AI – Lets you copy code from videos, images & PDFs
✅ Mutable AI – Write, refactor, and document code with AI
✅ AskCodi – Natural language to code generation
✅ Kite – Autocompletion powered by machine learning
✅ Replit Ghostwriter – AI assistant inside your online IDE

If this was helpful, react with emoji and turn all notifications on to never miss a drop!

🔗 AI Engineer Roadmap

10 Real-World AI Use Cases You Should Know

✅ Healthcare Diagnosis – AI detects diseases like cancer from X-rays & MRIs faster than humans
✅ Fraud Detection in Finance – Banks use ML to catch unusual transactions in real-time
✅ AI in Education – Personalized learning paths, grading automation, and virtual tutors
✅ Self-Driving Cars – AI helps vehicles understand surroundings and make split-second decisions
✅ Customer Service Chatbots – 24/7 support powered by natural language understanding
✅ Recommendation Systems – Netflix, Amazon, Spotify know your taste better than you
✅ Agriculture AI – Drones and sensors optimize irrigation, crop monitoring, and yield prediction
✅ Cybersecurity – AI detects threats and anomalies before they escalate
✅ Retail & Inventory – AI forecasts demand and automates stock management
✅ Voice Assistants – Siri, Alexa, and Google Assistant getting smarter every day

15+ Must Watch Movies for Programmers🧑‍💻🤖

1. The Matrix
2. The Social Network
3. Source Code
4. The Imitation Game
5. Silicon Valley
6. Mr. Robot
7. Jobs
8. The Founder
9. The Social Dilemma
10. The Great Hack
11. Halt and Catch Fire
12. Wargames
13. Hackers
14. Snowden
15. Who Am I

ChatGPT cheat sheet for job seekers 👆

Machine Learning Algorithms 👆

𝗛𝗼𝘄 𝘁𝗼 𝗚𝗲𝘁 𝗦𝘁𝗮𝗿𝘁𝗲𝗱 𝗶𝗻 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗭𝗲𝗿𝗼 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲!🧠⚡

AI might sound complex. But guess what?
You don’t need a PhD or 5 years of experience to break into this field.

Here’s your 6-step beginner roadmap to launch your AI journey the smart way👇

🔹 𝗦𝘁𝗲𝗽 𝟭: Learn the Basics of Python (Your AI Superpower)
Python is the language of AI.
✅ Learn variables, loops, functions, and data structures
✅ Practice with platforms like W3Schools, SoloLearn, or Replit
✅ Understand NumPy & Pandas basics (they’ll be your go-to tools)

🔹 𝗦𝘁𝗲𝗽 𝟮: Understand What AI Really Is
Before diving deep, get clarity.
✅ What is AI vs ML vs Deep Learning?
✅ Learn core concepts like Supervised vs Unsupervised Learning
✅ Follow beginner-friendly YouTubers like “StatQuest” or “Codebasics”

🔹 𝗦𝘁𝗲𝗽 𝟯: Build Simple AI Projects (Even as a Beginner)
Start applying your skills with fun mini-projects:
✅ Spam Email Classifier
✅ House Price Predictor
✅ Rock-Paper-Scissors Game using AI
Pro Tip: Use scikit-learn for most of these!

🔹 𝗦𝘁𝗲𝗽 𝟰: Get Comfortable with Data (AI Runs on It!)
AI = Algorithms + Data
✅ Learn basic data cleaning with Pandas
✅ Explore simple datasets from Kaggle or UCI ML Repository
✅ Practice EDA (Exploratory Data Analysis) with Matplotlib & Seaborn

🔹 𝗦𝘁𝗲𝗽 𝟱: Take Free AI Courses (No Cost Learning)
You don’t need a fancy bootcamp to start learning.
✅ “AI For Everyone” by Andrew Ng (Coursera)
✅ “Machine Learning with Python” by IBM (edX)
✅ Kaggle’s Learn Track: Intro to ML

🔹 𝗦𝘁𝗲𝗽 𝟲: Join AI Communities & Share Your Work
✅ Join AI Discord servers, Reddit threads, and LinkedIn groups
✅ Post your projects on GitHub
✅ Engage in AI hackathons, challenges, and build in public
Your network = Your next opportunity.

🎯 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 = 𝗬𝗼𝘂𝗿 𝗘𝗻𝘁𝗿𝘆 𝗣𝗼𝗶𝗻𝘁
It’s not about knowing everything—it’s about starting.
Consistency will compound.
You’ll go from “beginner” to “builder” faster than you think.

Free Artificial Intelligence Resources: https://whatsapp.com/channel/0029VaoePz73bbV94yTh6V2E

#ai