🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the most in-demand AI skill in today’s job market: building autonomous AI systems.

In Ready Tensor’s free, project-first program, you’ll create three portfolio-ready projects using 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, and vector databases — and deploy production-ready agents that employers will notice.

Includes guided lectures, videos, and code.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.

👉 Apply now: https://go.readytensor.ai/cert-584-agentic-ai-certification

ChatGPT Prompts Book
Oliver Theobald, 2024

🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the most in-demand AI skill in today’s job market: building autonomous AI systems.

In Ready Tensor’s free, project-first program, you’ll create three portfolio-ready projects using 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, and vector databases — and deploy production-ready agents that employers will notice.

Includes guided lectures, videos, and code.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.

👉 Apply now: https://go.readytensor.ai/cert-584-agentic-ai-certification

React ❤️ for more

ChatGPT prompt ideas for SWOT Analysis:

5 Easy Projects to Build as a Beginner

(No AI degree needed. Just curiosity & coffee.)

❯ 1. Calculator App
 • Learn logic building
 • Try it in Python, JavaScript or C++
 • Bonus: Add GUI using Tkinter or HTML/CSS

❯ 2. Quiz App (with Score Tracker)
 • Build a fun MCQ quiz
 • Use basic conditions, loops, and arrays
 • Add a timer for extra challenge!

❯ 3. Rock, Paper, Scissors Game
 • Classic game using random choice
 • Great to practice conditions and user input
 • Optional: Add a scoreboard

❯ 4. Currency Converter
 • Convert from USD to INR, EUR, etc.
 • Use basic math or try fetching live rates via API
 • Build a mini web app for it!

❯ 5. To-Do List App
 • Create, read, update, delete tasks
 • Perfect for learning arrays and functions
 • Bonus: Add local storage (in JS) or file saving (in Python)


React with ❤️ for the source code

Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a

Coding Projects: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502

ENJOY LEARNING 👍👍

🔖 Save this for Later✨

🤖 ChatGPT Prompts That You Shouldn't Know About :

1. Use the 80/20 principle to learn faster than ever

✅ Prompt: „I want to learn about [insert topic]. Identify and share the most important 20% of learnings from this topic that will help me understand 80% of it.“

2. Learn and develop any new skill in 30 days

✅ Prompt: „I want to learn / get better at [insert desired skill]. I am a complete beginner. Create a 30 day learning plan that will help a beginner like me learn and improve this skill.“

3. Enhance your problem solving skills

✅ Prompt: „Your role is that of a problem solver. Give me a step-by-step guide to solving [insert your problem].“

4. Use stories and metaphors to aid your memory

✅ Prompt: „I am currently learning about [insert topic]. Convert the key lessons from this topic into engaging stories and metaphors to aid my memorization.“

5. Strengthen your learning by testing yourselt

✅ Prompt: „I am currently learning about [insert topic]. Ask me a series of questions that will test my knowledge. Identify knowledge gaps in my answers and give me better answers to fill those gaps.“

6. Generate new ideas and overcome writers block

✅ Prompt: „I am writing a blog post about [insert topic]. Give me an outline for this blog post with 10 bullet points. Also give me 5 options for a catchy headline.“

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✅ | Chatbots
✅ | AI Assistants
✅ | Multi-Agent Systems

⚡️ Master tools like LangChain, LangGraph, RAGAS, & more.

Join now ⤵️
https://go.readytensor.ai/cert-584-agentic-ai-certification

🤖 A-Z of Essential Artificial Intelligence Concepts 🧠

A: Agent - An entity that perceives its environment and acts upon it to achieve goals. 🎯

B: Backpropagation - An algorithm used to train neural networks by calculating gradients and updating weights. 🔄

C: Convolutional Neural Network (CNN) - A deep learning model particularly effective for processing images and videos. 👁️

D: Deep Learning - A subset of machine learning that utilizes artificial neural networks with multiple layers to analyze data. 🧠

E: Expert System - A computer system designed to emulate the decision-making ability of a human expert. 👩‍💻

F: Feature Extraction - The process of selecting and transforming relevant features from raw data for use in AI models. ⚙️

G: Generative Adversarial Network (GAN) - A type of neural network architecture used for generating new, realistic data samples. 🖼️

H: Heuristic - A problem-solving approach that uses practical methods and shortcuts to produce solutions that may not be optimal but are sufficient. 💡

I: Inference - The process of drawing conclusions from data using logical reasoning and AI algorithms. 🤔

J: Knowledge Representation - Methods used to encode knowledge in AI systems, such as rules, frames, and semantic networks. 📚

K: K-Nearest Neighbors (KNN) - A simple machine learning algorithm used for classification and regression based on proximity to other data points. 🏘️

L: LSTM (Long Short-Term Memory) - A type of recurrent neural network (RNN) architecture used for processing sequential data, such as time series and natural language. ⌚

M: Machine Learning (ML) - The study of algorithms that allow computer systems to improve their performance through experience. 📈

N: Natural Language Processing (NLP) - A field of AI focused on enabling computers to understand, interpret, and generate human language. 🗣️

O: Optimization - The process of finding the best parameters for an AI model to minimize errors and maximize performance. ✅

P: Perceptron - A basic unit of a neural network that takes inputs, applies weights, and produces an output. ➕

Q: Q-Learning - A reinforcement learning algorithm used to learn an optimal action-selection policy for any Markov decision process (MDP). 🕹️

R: Reinforcement Learning (RL) - A type of machine learning where an agent learns to make decisions by interacting with an environment and receiving rewards or penalties. 🎮

S: Supervised Learning - A machine learning approach where an algorithm learns from labeled training data. 🏷️

T: Transfer Learning - A machine learning technique where a model trained on one task is repurposed on a second related task. ♻️

U: Unsupervised Learning - A machine learning approach where an algorithm learns from unlabeled data by identifying patterns and relationships. 🔍

V: Vision (Computer Vision) - A field of AI focused on enabling computers to "see" and interpret images and videos. 👁️

W: Word Embedding - A technique in NLP for representing words as vectors in a continuous space, capturing semantic relationships between words. ✍️

X: XAI (Explainable AI) - A set of methods aimed at making AI decision-making processes more transparent and understandable to humans. ❓

Y: YOLO (You Only Look Once) - A real-time object detection system widely used in computer vision applications. 🚗

Z: Zero-Shot Learning - A type of machine learning where a model can recognize objects or perform tasks it has never seen during training. ✨

React ❤️ for more

🤖 𝗕𝘂𝗶𝗹𝗱 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Join 𝟭𝟱,𝟬𝟬𝟬+ 𝗹𝗲𝗮𝗿𝗻𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝟭𝟮𝟬+ 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 building intelligent AI systems that use tools, coordinate, and deploy to production.

✅ 3 real projects for your portfolio
✅ Official certification + badges
✅ Learn at your own pace

𝟭𝟬𝟬% 𝗳𝗿𝗲𝗲. 𝗦𝘁𝗮𝗿𝘁 𝗮𝗻𝘆𝘁𝗶𝗺𝗲.

𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲 ⤵️
https://go.readytensor.ai/cert-584-agentic-ai-certification

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