🚀 Coding Projects & Ideas 💻
Inspire your next portfolio project — from beginner to pro!
🏗️ Beginner-Friendly Projects
1️⃣ To-Do List App – Create tasks, mark as done, store in browser.
2️⃣ Weather App – Fetch live weather data using a public API.
3️⃣ Unit Converter – Convert currencies, length, or weight.
4️⃣ Personal Portfolio Website – Showcase skills, projects & resume.
5️⃣ Calculator App – Build a clean UI for basic math operations.
⚙️ Intermediate Projects
6️⃣ Chatbot with AI – Use NLP libraries to answer user queries.
7️⃣ Stock Market Tracker – Real-time graphs & stock performance.
8️⃣ Expense Tracker – Manage budgets & visualize spending.
9️⃣ Image Classifier (ML) – Classify objects using pre-trained models.
🔟 E-Commerce Website – Product catalog, cart, payment gateway.
🚀 Advanced Projects
1️⃣1️⃣ Blockchain Voting System – Decentralized & tamper-proof elections.
1️⃣2️⃣ Social Media Analytics Dashboard – Analyze engagement, reach & sentiment.
1️⃣3️⃣ AI Code Assistant – Suggest code improvements or detect bugs.
1️⃣4️⃣ IoT Smart Home App – Control devices using sensors and Raspberry Pi.
1️⃣5️⃣ AR/VR Simulation – Build immersive learning or game experiences.
💡 Tip: Build in public. Share your process on GitHub, LinkedIn & Twitter.
🔥 React ❤️ for more project ideas!
Inspire your next portfolio project — from beginner to pro!
🏗️ Beginner-Friendly Projects
1️⃣ To-Do List App – Create tasks, mark as done, store in browser.
2️⃣ Weather App – Fetch live weather data using a public API.
3️⃣ Unit Converter – Convert currencies, length, or weight.
4️⃣ Personal Portfolio Website – Showcase skills, projects & resume.
5️⃣ Calculator App – Build a clean UI for basic math operations.
⚙️ Intermediate Projects
6️⃣ Chatbot with AI – Use NLP libraries to answer user queries.
7️⃣ Stock Market Tracker – Real-time graphs & stock performance.
8️⃣ Expense Tracker – Manage budgets & visualize spending.
9️⃣ Image Classifier (ML) – Classify objects using pre-trained models.
🔟 E-Commerce Website – Product catalog, cart, payment gateway.
🚀 Advanced Projects
1️⃣1️⃣ Blockchain Voting System – Decentralized & tamper-proof elections.
1️⃣2️⃣ Social Media Analytics Dashboard – Analyze engagement, reach & sentiment.
1️⃣3️⃣ AI Code Assistant – Suggest code improvements or detect bugs.
1️⃣4️⃣ IoT Smart Home App – Control devices using sensors and Raspberry Pi.
1️⃣5️⃣ AR/VR Simulation – Build immersive learning or game experiences.
💡 Tip: Build in public. Share your process on GitHub, LinkedIn & Twitter.
🔥 React ❤️ for more project ideas!
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✅ Top Artificial Intelligence Concepts You Should Know 🤖🧠
🔹 1. Natural Language Processing (NLP)
Use Case: Chatbots, language translation
→ Enables machines to understand and generate human language.
🔹 2. Computer Vision
Use Case: Face recognition, self-driving cars
→ Allows machines to "see" and interpret visual data.
🔹 3. Machine Learning (ML)
Use Case: Predictive analytics, spam filtering
→ AI learns patterns from data to make decisions without explicit programming.
🔹 4. Deep Learning
Use Case: Voice assistants, image recognition
→ A type of ML using neural networks with many layers for complex tasks.
🔹 5. Reinforcement Learning
Use Case: Game AI, robotics
→ AI learns by interacting with the environment and receiving feedback.
🔹 6. Generative AI
Use Case: Text, image, and music generation
→ Models like ChatGPT or DALL·E create human-like content.
🔹 7. Expert Systems
Use Case: Medical diagnosis, legal advice
→ AI systems that mimic decision-making of human experts.
🔹 8. Speech Recognition
Use Case: Voice search, virtual assistants
→ Converts spoken language into text.
🔹 9. AI Ethics
Use Case: Bias detection, fair AI systems
→ Ensures responsible and transparent AI usage.
🔹 10. Robotic Process Automation (RPA)
Use Case: Automating repetitive office tasks
→ Uses AI to handle rule-based digital tasks efficiently.
💡 Learn these concepts to understand how AI is transforming industries!
💬 Tap ❤️ for more!
🔹 1. Natural Language Processing (NLP)
Use Case: Chatbots, language translation
→ Enables machines to understand and generate human language.
🔹 2. Computer Vision
Use Case: Face recognition, self-driving cars
→ Allows machines to "see" and interpret visual data.
🔹 3. Machine Learning (ML)
Use Case: Predictive analytics, spam filtering
→ AI learns patterns from data to make decisions without explicit programming.
🔹 4. Deep Learning
Use Case: Voice assistants, image recognition
→ A type of ML using neural networks with many layers for complex tasks.
🔹 5. Reinforcement Learning
Use Case: Game AI, robotics
→ AI learns by interacting with the environment and receiving feedback.
🔹 6. Generative AI
Use Case: Text, image, and music generation
→ Models like ChatGPT or DALL·E create human-like content.
🔹 7. Expert Systems
Use Case: Medical diagnosis, legal advice
→ AI systems that mimic decision-making of human experts.
🔹 8. Speech Recognition
Use Case: Voice search, virtual assistants
→ Converts spoken language into text.
🔹 9. AI Ethics
Use Case: Bias detection, fair AI systems
→ Ensures responsible and transparent AI usage.
🔹 10. Robotic Process Automation (RPA)
Use Case: Automating repetitive office tasks
→ Uses AI to handle rule-based digital tasks efficiently.
💡 Learn these concepts to understand how AI is transforming industries!
💬 Tap ❤️ for more!
❤5
AI easily interprets information in simple requests, but if input is very long and complex, model may misunderstand.
To avoid this, try adding structure to prompt and make response of AI more predictable and clear.
How to structure a prompt?
It seems that markup is complicated so you can show your prompt to the AI and ask it to add markup itself without changing the essence.
To avoid this, try adding structure to prompt and make response of AI more predictable and clear.
How to structure a prompt?
The creators of neural networks suggest using special markup that the AI understands. These can be:
☞ Markdown, a text formatting language. For prompts, you can use bulleted and numbered lists, as well as the # sign, which in Markdown signifies different levels of headings and, in the prompt, defines the hierarchy of tasks.Task
Plan a birthday party for a company of 8 people.
Restrictions
- Budget: 10,000 rubles
- Location: at home
- There are vegetarians among the guests
What should be in the plan?
1. Menu
- Main dishes
- Snacks
- Drinks
2. Entertainment
- Games
- Music
- Activities
3. Timing of the event
☞ XML tags that indicate the boundaries of any text element. The beginning and end of the element are marked with <tag> and </tag>, and the tags themselves can be any.<goal>Create a weekly menu for a family of 3 people</goal>
<restrictions>
<budget>10,000 rubles</budget>
<preferences>More vegetables, minimum fried food, soup every day</preferences>
<exclude>Mushrooms, nuts, seafood, honey</exclude>
</restrictions>
<format>
<meals>breakfast, lunch, dinner, snack</meals>
<description>A detailed recipe for each dish with a list of ingredients</description>
</format>
☞ JSON, a data structuring standard that allows you to mark up any information in the prompt with simple syntax.{
"task": "Make a shopping list for the week",
"parameters": {
"number_of_people": 2,
"preferences": ["vegetarian", "minimum sugar"],
"budget": "up to 10,000 rubles"
},
"categories": [
"vegetables and fruits",
"cereals and pasta",
"dairy products",
"drinks",
"other"
],
"format_of_answer": {
"type": "list",
"group_by_categories": true
}
>
It seems that markup is complicated so you can show your prompt to the AI and ask it to add markup itself without changing the essence.
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