#Jad Software Development Methodology

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#Jad Software Development Methodology Reel by @adrien.ninet (verified account) - 👇🏼Comment "ROCKET" and I'll send you my full guide to building any app. Build a profitable SaaS in 5 steps. No coding required. Use ChatGPT + Rock
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@adrien.ninet
👇🏼Comment “ROCKET” and I’ll send you my full guide to building any app. Build a profitable SaaS in 5 steps. No coding required. Use ChatGPT + Rocket to generate your app, iterate in chat, connect tools like Stripe, Resend, and Supabase, then publish live in minutes. #saas #nocode #aidevelopment #startup #rocket
#Jad Software Development Methodology Reel by @the.datascience.gal (verified account) - Here's a roadmap to help you go from a software engineer to a data scientist 👩‍💻 👇 If you're tired of writing vanilla apps and want to build ML sy
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@the.datascience.gal
Here’s a roadmap to help you go from a software engineer to a data scientist 👩‍💻 👇 If you’re tired of writing vanilla apps and want to build ML systems instead, this one’s for you. Step 1 – Learn Python and SQL (not Java, C++, or JavaScript). → Focus on pandas, numpy, scikit-learn, matplotlib → For SQL: use LeetCode or StrataScratch to practice real-world queries → Don’t just write code—learn to think in data Step 2 – Build your foundation in statistics + math. → Start with Practical Statistics for Data Scientists → Learn: probability, hypothesis testing, confidence intervals, distributions → Brush up on linear algebra (vectors, dot products) and calculus (gradients, chain rule) Step 3 – Learn ML the right way. → Do Andrew Ng’s ML course (Deeplearning.ai) → Master the full pipeline: cleaning → feature engineering → modeling → evaluation → Read Elements of Statistical Learning or Sutton & Barto if you want to go deeper Step 4 – Build 2–3 real, messy projects. → Don’t follow toy tutorials → Use APIs or scrape data, build full pipelines, and deploy using Streamlit or Gradio → Upload everything to GitHub with a clear README Step 5 – Become a storyteller with data. → Read Storytelling with Data by Cole Knaflic → Learn to explain your findings to non-technical teams → Practice communicating precision/recall/F1 in simple language Step 6 – Stay current. Never stop learning. → Follow PapersWithCode (it's now sun-setted, use huggingface.co/papers/trending, ArXiv Sanity, and follow ML practitioners on LinkedIn → Join communities, follow researchers, and keep shipping new experiments ------- Save this for later. Tag a friend who’s trying to make the switch. [software engineer to data scientist, ML career roadmap, python for data science, SQL for ML, statistics for ML, data science career guide, ML project ideas, data storytelling, becoming a data scientist, ML learning path 2025]
#Jad Software Development Methodology Reel by @chhavi_maheshwari_ - Handling 1 Million RPS isn't about code - it's about smart architecture. 1️⃣ Traffic Distribution (Load Balancers) ➡️ Spreads incoming requests acros
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@chhavi_maheshwari_
Handling 1 Million RPS isn’t about code — it’s about smart architecture. 1️⃣ Traffic Distribution (Load Balancers) ➡️ Spreads incoming requests across many servers so nothing overloads. Example: 1M requests split across 200 servers = ~5K requests per server. ⸻ 2️⃣ Scale Out, Not Up (Horizontal Scaling) ➡️ Add more machines instead of making one server bigger. Example: Flash sale traffic? Instantly launch 50 new API instances. ⸻ 3️⃣ Fast Reads with Cache ➡️ Use Redis/Memcached to avoid hitting the database every time. Example: Cached user data = millions of DB calls saved daily. ⸻ 4️⃣ Edge Delivery with CDN ➡️ Static content loads from servers closest to the user. Example: Users in Delhi fetch images from a Delhi CDN node. ⸻ 5️⃣ Background Work with Queues ➡️ Heavy tasks run asynchronously so APIs respond instantly. Example: Payment succeeds now, email receipt sent in background. ⸻ 6️⃣ Split the Database (Sharding) ➡️ Divide data across multiple databases to handle scale. Example: Usernames A–M on one shard, N–Z on another. ⸻ 7️⃣ Rate Limiting ➡️ Prevent abuse and traffic spikes from taking the system down. Example: Limit clients to 100 requests/sec to block bots from killing the API. ⸻ 8️⃣ Lightweights Payloads ➡️ Smaller payloads = faster responses + less bandwidth. Example: Send only required fields instead of massive JSON blobs. Please follow for more such videos🙏 #systemdesign #softwaredevelopers #programming #tech #interview [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]
#Jad Software Development Methodology Reel by @iron.coding - Full-stack projects Coding project 2025 💻 In this video, I'm sharing five complete full-stack projects that I've personally built - including an e-c
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@iron.coding
Full-stack projects Coding project 2025 💻 In this video, I’m sharing five complete full-stack projects that I’ve personally built — including an e-commerce store, admin dashboard, SaaS web app, chat application, and more. These projects are worth over $20,000, but I’m giving them away completely free. You can use them to enhance your resume, learn real-world full-stack development, or customize and sell them to your clients. These projects are perfect for web developers and software or app developers. This is hidden gem for coder and programmers. #webdevelopment #coding #html #css #javascript #java #python #pythonprogramming #pythoncode
#Jad Software Development Methodology Reel by @codewithnishchal (verified account) - Comment "HLD" to get the complete flow or just take the screenshot. One System Design Flow for every HLD interview. Use the flow in your next interv
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@codewithnishchal
Comment “HLD” to get the complete flow or just take the screenshot. One System Design Flow for every HLD interview. Use the flow in your next interview, scale application from 1 to million users and modify your application services in between before servers. Hope it helps! Follow for more! #systemdesign #datastructure #hld #reelitfeelit
#Jad Software Development Methodology Reel by @buildmuse_ - Save this and follow @buildmuse_ ! Most engineers think scaling reads means "add more servers." That's usually wrong. Here are 4 production-grade J
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@buildmuse_
Save this and follow @buildmuse_ ! Most engineers think scaling reads means “add more servers.” That’s usually wrong. Here are 4 production-grade Java patterns senior engineers use to scale read-heavy systems: 1. Redis Cache 2. Read Replicas 3. Index + Pagination 4. Async Precomputation These are the kinds of practical system design decisions interviewers expect from experienced engineers. Master fundamentals before jumping to microservices. #interviewprep #javaprogramming #softwareengineering #systemdesign #coding
#Jad Software Development Methodology Reel by @dev.nd.drive - next time before quitting DSA, watch this video again #leetcode #javascript #developerlife [ dsa patterns on leetcode ]
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@dev.nd.drive
next time before quitting DSA, watch this video again #leetcode #javascript #developerlife [ dsa patterns on leetcode ]
#Jad Software Development Methodology Reel by @sundaslovescoding - Scalability in System Design is not equal to fast. #webdevelopment #javascript #sundaslovescoding #programming #coding
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@sundaslovescoding
Scalability in System Design is not equal to fast. #webdevelopment #javascript #sundaslovescoding #programming #coding
#Jad Software Development Methodology Reel by @jessramosdata (verified account) - Comment "project" for my full video that breaks each of these projects down in detail with examples from my own work. If you're using the Titanic, Ir
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@jessramosdata
Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!
#Jad Software Development Methodology Reel by @dev.nd.drive - important js output based question #javascript #codinglife #softwaredevelopment
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@dev.nd.drive
important js output based question #javascript #codinglife #softwaredevelopment
#Jad Software Development Methodology Reel by @vnz.dev - He creado una estructura base para crear microservicios de una manera sencilla con Nestjs con servicios de Api Gateway, User Service, Product Service
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@vnz.dev
He creado una estructura base para crear microservicios de una manera sencilla con Nestjs con servicios de Api Gateway, User Service, Product Service y Notification Service, cada uno con su base de datos . Link del repositorio: https://github.com/jaimeirazabal1/microservicios-base-nestjs #programacion #nestjs #microservicios #arquitecturadesoftware #jaimeirazabal
#Jad Software Development Methodology Reel by @emrcodes (verified account) - Comment "JS" to get the links! 🔥 Trying to build for the web without understanding JavaScript is like trying to drive a car without touching the ste
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@emrcodes
Comment “JS” to get the links! 🔥 Trying to build for the web without understanding JavaScript is like trying to drive a car without touching the steering wheel. If you want interactive apps, real frontend power, and the foundation of modern web development—this mini roadmap is your starting point. ⚡ JavaScript in 100 Seconds The fastest high-level intro you’ll ever watch. Perfect if you want to quickly understand what JavaScript is, where it runs, and why it powers almost everything on the web. 📚 JavaScript Visualized – Event Loop, Web APIs, (Micro)task Queue Struggling with async code? This visual deep dive makes the event loop, callbacks, promises, and the task queue finally make sense—so you stop “guessing” and start understanding. 🎓 JavaScript Course for Beginners – Your First Step to Web Development Your complete beginner-friendly foundation. Learn variables, functions, loops, DOM manipulation, and the core concepts you need before jumping into frameworks like React or Vue. 💡 With these JavaScript resources you will: 🚀 Understand how the web actually becomes interactive 🧠 Master async behavior and the event loop (where most beginners get stuck) 🏗 Build a strong foundation before moving to frameworks and advanced tools 🌐 Level up for Frontend, Full-Stack, and Web Engineering roles If you want to move from static pages to dynamic, real-world web applications, JavaScript isn’t optional—it’s essential. 📌 Save this post so you never lose this JavaScript roadmap. 💬 Comment “JS” and I’ll send you all the links! 👉 Follow for more Web Dev, System Design, and Engineering Career Growth content.

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