Currently Locked in on the learning journey #6MonthsOfLockIn. Ml/Dl, MLops, Development, GYM, AI Engineering, System Design. In love with @porsche

Joined November 2024
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Manifesting spending upcoming years in San Francisco with the GOATS 🐐!!! Affirming it!
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Abdullah retweeted
2026 Data Engineering Roadmap 📊 Stage 1: SQL Stage 2: Python Stage 3: Data Modeling Stage 4: ETL Pipelines Stage 5: PostgreSQL Stage 6: Spark Stage 7: Airflow Stage 8: Data Warehousing Stage 9: Cloud (AWS/GCP/Azure) Stage 10: Streaming Systems Stage 11: Data Quality Monitoring Stage 12: Production Pipelines Data scientists get the spotlight. Data engineers move the data.
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Best thing about using Claude is that before it starts hallucinating they simply ends the session limit. No BS, straight turn off.
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I have my first ever Associate Software engineer interview scheduled in next 3 days, how do i prepare for it? Please share material and resources.
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Abdullah retweeted
AI in production still follows the same IT principles: • Least privilege • Auditability • Observability • Rollback plans
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The #AWS Bahrain outage exposed a quiet truth in tech: We’ve built global systems on local assumptions #AWSDown Bahrain going down showed us the gap between theory and reality. Kubernetes won’t save you. CI/CD won’t save you. Only multi‑region architecture will. More on Medium:
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Until and Unless you dont define your destiny Your end goal Your purpose It is very hard to move blindly and just chase out there anything and everything Sit Talk Explore Find Then stick to it and be master of it.
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Revised Plan for #6MonthsOfLockIn: 🎓AWS cert (Cloud Practitioner / Solutions Architect) 🐍Master Python FastAPI & Django 🤖GenAI/AI Engineering 💻TS 💻Next.js 🚀Deepen DevOps & MLOps 🧠DSA, OOP & DBs. Later if time allows, Automation mastery Locked in. 🚀
Life Update Lately: Got an A in my FYP 1 Got an A in Devops Course Survived a heavy semester Explored new niches Met amazing people Started AWS cert prep Finished Software Architecture for Large‑Scale Systems on Udemy. Started Deep learning course on Coursera
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Life Update Lately: Got an A in my FYP 1 Got an A in Devops Course Survived a heavy semester Explored new niches Met amazing people Started AWS cert prep Finished Software Architecture for Large‑Scale Systems on Udemy. Started Deep learning course on Coursera
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Learned to make CI/CD pipelines Learned Docker Attended a WorkShop @SystemsLtd and learned that how important Cloud is. Showed at GYM 3/4 days a week
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Learned About GenAI Learned basics about RAG Learned Basics about Langchain Tried to understand Gitflow
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At this point of time you only can learn software engineering through two ways 1)By making projects 2)By going through case studies, codebases, reading functionalities, understand existing systems and their flows. (1)
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A successful product ≠ a successful business. We’ve all seen brilliant products… but the company behind them collapses.
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💡The beauty of DDD is that it helps you build better systems and better businesses
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👉 Have you ever worked on a product that succeeded technically but the business failed? What was the missing link in your experience?
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Gradient descent is an algorithm which step by step in an iterative way adjust parameters (weights and biases) of the layers until the error (loss) is as low as possible, achieving the best model fit. Technical: computes the gradient of the loss with respect to model parameters.
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