14.7M
ITWait for assembly 😮
#programming #code
@itstundeanthony
#Apl Programming Tutorials
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30.6K
_P🐍Learning Python with AI
🔸️In this class, we're training students to learn Python faster with AI collaboration!
🔸️Here, Aidan uses ChatGPT to recreate a version of the classic arcade game Asteroids.
🔸️This is Aidan's 12th day of Python programming.
🔸️"But WAIT, if students don't learn procedural and syntax fundamentals, they'll never be able to troubleshoot their own code!"
🔸️Yes. I agree with you. I'm teaching them the basics and not overlooking the critical fundamentals. You're right.
🔸️Also, it's important to show them the capabilities offered through collaborating with a powerful tool and how to use it as a learning aid, ather than a shortcut. This is critical!
@cvcc.va
@a3_automate
🔸️Do you think programming is still a valuable skill given modern technology?
@_papamurph
2.3M
EZHow to start.
#coding #programming #projects #tutorial
@ezsnippet
483.9K
LEWhat is this boy’s tech stack. #vibecoding #learninwithak #codingwithai
@learninwithak
2.1M
RAIntroduction to loops in programming languages🔥. A loop is used to repeatedly execute a block of statements multiple times. It is a very essential concept in programming. #loops #programming #coding #teaching #cplusplus #codingforkids
@rakshith_prabha
143.8K
PY⚡ Whole C++ in one video 🎥💻 — from basics to pro in one shot 🚀✨
❓ If you could master one programming language overnight, which one would it be?
#python #learncoding #codewithme #codinglife💻 #100daysofcode #reelsinstagram #pythonprogramminglanguage #techreels
@py.geist
1.4M
NAI need Followers 🥲
Feeling lost in the jungle of AI tools, frameworks, and APIs for mobile apps?
You’re not alone.
That’s why I mapped it all out—so you can see exactly how everything fits together:
🔹 Frontend: Flutter, React Native, Swift, Kotlin
🔹 On-Device AI: TensorFlow Lite, Core ML, ML Kit
🔹 Cloud Platforms: AWS, GCP, Firebase, Supabase
🔹 LLM / Generative AI APIs: Gemini, Hugging Face, OpenAI, Vertex AI, Bedrock
🔹 Databases: Firestore, Pinecone, ChromaDB, PostgreSQL
🔹 Agent Frameworks: LangChain, LlamaIndex, GenKit
🔹 APIs: Firebase Functions, FastAPI, Lambda, Amplify, Cloud Run
🔹 Memory / Storage: SQLite, Core Data
🔹 Distribution: App Store, Play Store
💡 Why this matters: Whether you’re just starting with Flutter or scaling a Firebase + AI app, this roadmap shows how the pieces connect: and how to ship smarter apps faster.
👇 Curious if I make a deep dive post on one part of this roadmap, which area should I cover first?
Follow @navokitech
#softwareengineer #mobileappdevelopment #peoplewhocode #100daysofcode #navoki
#careertips #mobiledev #mobiledevelopment #mobileappdevelopment #appdeveloper #careertips #programming #codinglife #thedevlife #programmerlife #programminglife #developerlife #girlswhocode #programmerslife💻
#generativeai #aicreator #learnai #roadmap
@navokitech
837.2K
SWIf I was a beginner learning to code, I would use this 90 day roadmap step by step for beginners 💪 #coding #codingforbeginners #learntocode #computerscience #programming
@swerikcodes
750.3K
ERPython beginners, this guide will save you hours of confusion!
#python #coding #code #errormakesclever
@errormakesclever
2.2M
MI1 Million RPS isn't about code, it's about architecture.
Here are the 8 key layers to scale your API architecture.
Unlock 200+ practical problem-solutions just like this one in the Ebook. Link in bio
1️⃣ Load Balancer
👉 Distributes traffic across multiple servers so no single machine melts.
Example: 1M req/s split across 200 servers = only 5k req/s each.
⸻
2️⃣ Horizontal Scaling
👉 Add more servers when traffic spikes instead of upgrading one big server.
Example: Black Friday? Spin up 50 more API nodes in seconds.
⸻
3️⃣ Caching Layer
👉 Serve frequent reads from Redis/Memcached to avoid DB overload.
Example: User profile cached → avoids 10M database hits/day.
⸻
4️⃣ CDN for Static Content
👉 Images and static assets load from edge servers near the user.
Example: A user in Delhi gets images from a Delhi CDN node.
⸻
5️⃣ Async Processing (Queues)
👉 Push heavy tasks to Kafka/SQS so API responds instantly.
Example: Payment API returns fast → receipt email sent in background.
⸻
6️⃣ Database Sharding
👉 Split huge datasets across multiple DB shards to scale reads/writes.
Example: Users A–M on shard 1, N–Z on shard 2.
⸻
7️⃣ Rate Limiting
👉 Block or throttle abusive clients to protect server capacity.
Example: “100 requests/sec limit” prevents bots from killing the API.
⸻
8️⃣ Lightweight Payloads
👉 Reduce JSON response size to cut latency and bandwidth.
Example: Return only “id, name, price” instead of 20 unnecessary fields.
#systemdesign #apidesign #scaling #1millionrps #distributedsystems #loadbalancing #caching #microservices #softwaredeveloper #programming #coding #devops #tech #backenddeveloper #backenddevelopment #api #interviews #database #learninganddevelopment #tech
[API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]
@mission_compile
1.9M
MORelaxing Python & Pygame Creations #coding #programming
@mohcinale
227.8K
LODo you know how to write a loop in a single line using list comprehension in python.
#list #pythoncode #codelikedeveloper #logic #programming
@logic_overflow
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