Stellamaris (Stella) N. W, MSc, MA’s Post

Computer science should feel accessible, creative, and connected to the world students live in. That’s why I’m excited about imagi and its plug-and-play computer science and AI lessons for grades 3–12. Teachers can introduce Python, AI, and coding fundamentals with confidence, even without prior tech experience. Full lesson plans and materials are provided, AI-assisted debugging helps keep momentum going, and lessons work on Chromebooks, laptops, and tablets. Learn more: https://imagilabs.com/ #education #edtech #STEM #coding #vibecoding #AI #STEMEducation Lovable

Building something I wish existed when I started learning quantum computing. Qiskit Intuition is an open-source interactive lab that teaches quantum computing the way physics should be taught — through visual intuition, not equations first. Drop a gate. Watch the Bloch sphere move. Ask the AI why. It combines a drag-and-drop circuit composer, real-time 3D state visualization, a multi-agent AI tutor (A.C.E.), and a live Qiskit sandbox — all in one place. Still very much a work in progress, but the architecture is taking shape. The latest update adds parameterized gates, an intent-routing AI chat, preset experiments, and a full 6-level curriculum from Python basics to IBM hardware execution. Would love feedback from anyone in quantum education or QC research. 🔗 https://lnkd.in/grQuKrJA #QuantumComputing #Qiskit #OpenSource #MachineLearning #Physics #Quantum

When I was building this course for Coursera I put myself in the persective of a student wanting to learn REAL WORLD #rust, not the Rust taught by tenured Computer Science professors raging against [x,y,z] and "why wasn't I consulted". Instead it is about how to ship production Rust code. Check out another banger from Pragmatic AI Labs Take the course here: https://lnkd.in/eBCE4E-y /learn/ship

One of the most complete Computer Science learning repositories on GitHub. Over 80K+ stars and packed with free university-level video courses from: • MIT• Stanford• Berkeley• Harvard• CMU• Princeton• Caltech• IIT Topics covered: → Data Structures & Algorithms→ Operating Systems→ Distributed Systems→ Database Systems→ Computer Networks→ Machine Learning & Deep Learning→ NLP & Computer Vision→ Security & Cryptography→ Robotics→ Blockchain→ Quantum Computing From beginner-friendly CS50 all the way to advanced systems courses like MIT 6.824 Distributed Systems. What stands out is not just the quantity — it’s the quality and structure. This is the kind of resource that can genuinely change someone’s technical journey if they stay consistent. The curriculum is free.The commitment is yours. https://lnkd.in/eF-tB9_G #ComputerScience #Programming #Cybersecurity #AI #MachineLearning #SoftwareEngineering #DataScience #Robotics #DistributedSystems #Linux #Learning #Tech

🚀 Mini Project Completed: Quantum Algorithm Simulation Tool I’m excited to share my recent mini project where we developed a GUI-based Quantum Algorithm Simulation Tool using Qiskit.This project focuses on making quantum computing concepts more interactive, visual, and accessible, especially for beginners. 🔍 What the project does: Simulates key quantum algorithms: Bernstein–Vazirani Deutsch–Jozsa Grover’s Search Provides an intuitive GUI to: Select algorithms Input parameters Generate quantum circuits Visualize results using histograms This project was inspired by my learning in quantum computing through a Coursera course, where I explored the fundamentals of quantum algorithms and their applications. ⚡ Key Learnings: Practical understanding of superposition and interference Insight into quantum speedup and amplitude amplification Hands-on experience with Qiskit and circuit simulation 🎯 This project helped me bridge the gap between theoretical concepts and real-world implementation. 🔗 GitHub Repository: 👉 https://lnkd.in/dApSX9u6 Would love to hear your feedback! #QuantumComputing #Qiskit #Python #MiniProject #ComputerScience #Learning #Innovation #StudentProject #Tech

Zyphra's ZAYA1-8B is a sub-1B-active-parameter MoE trained entirely on AMD MI300x. Apache 2.0. Matches or exceeds models many times its size on AIME/HMMT math and LCB coding. New Compressed Convolutional Attention scheme, MLP-based MoE router, five-stage post-training pipeline (SFT -> reasoning warmup -> RL-Gym -> math/code RL -> RLHF/RLAIF). 1,024 MI300x nodes — significant as a non-Nvidia training proof point. https://lnkd.in/eHxzywGJ

-- Quantum ML Series 2 | Post 07 of 11 #QFD2 -- Post 6 ended with a working forward pass. Post 7 closes the loop. Today we train the quantum classifier for the first time. Here is what we built: A complete hybrid quantum-classical model. The quantum circuit handles feature processing. A classical linear layer maps the 16 quantum outputs to 10 digit class probabilities. Both components train together end to end. Cross entropy loss. Adam optimizer at 0.01 learning rate. 10 epochs. 500 training images. The training loop looks like standard PyTorch. Zero gradients. Forward pass. Compute loss. Call loss.backward(). Step the optimizer. The quantum specific part is invisible at this level. PennyLane handles the parameter shift rule gradient computation automatically. Gradients flow through the quantum circuit just like they flow through any classical layer. Honest results from my run: After 10 epochs on 500 training images the loss went from 2.29 down to 1.61. Test accuracy: approximately 35 to 45 percent. Random chance on a 10 class problem is 10 percent. So the model learned something real. But a classical logistic regression on the same 16 features would likely hit 60 to 70 percent. A classical CNN on the full image would hit 99 percent plus. I am sharing the exact numbers, not the best case. That is the point of learning in public. One honest observation. Training a quantum circuit is slow. Each backward pass runs the circuit twice per parameter for the parameter shift rule. With 32 quantum parameters that is a lot of circuit evaluations per batch. We trained on 500 images for practical reasons. The full 60,000 image MNIST training set would take a very long time on a laptop simulator. That constraint is real. It goes in the benchmark comparison in Post 8. Full article with all explanations below. https://lnkd.in/gBgf7avB Article link in first comment 👇 I am also currently open to full stack development and quantum computing opportunities. Six years of coding experience. Building in QML. Looking for a team working on something technically interesting. If that sounds like your team, feel free to reach out or connect. #QuantumComputing #QuantumML #MachineLearning #LearnInPublic #Developer #PennyLane #QML #Coding #FutureTech #QuantumMLSeries #OpenToWork #FullStackDeveloper

🤪 You do not need to spend a single dollar to learn #quantum computing in 2026-27. Here are 9 free courses worth your time 👇 🟢 Beginner 🔹IBM Quantum Learning - build real circuits on IBM hardware from day 🔹one #Xanadu Codebook - interactive exercises right in your browser, no setup needed 🔹QWorld QBronze - #Python notebooks covering gates, states and Grover's algorithm 🔵 Intermediate 🔸MIT OpenCourseWare - full MIT lecture series with problem sets, completely free 🔸#Qiskit Textbook - quantum algorithms in real runnable code 🔸University of St Andrews on Coursera - audit free, covers hardware and circuit design 🟣 Advanced Google Cirq tutorials - NISQ algorithms and noise models from the Google Quantum AI team 🔹Caltech Quantum #Cryptography on edX - BB84, post-quantum standards, audit free 🔹Scott Aaronson lectures on #YouTube - the deepest free dive into why #quantum computers are powerful Total cost? Zero. The #quantum talent shortage is real. There are 3x more open roles than qualified candidates right now. These courses are the fastest free path to closing that gap. -------------------- 👉 Quantum Jobs List (global): https://lnkd.in/dYSJ3XBm WhatsApp channel for job alerts: https://lnkd.in/dxZ_umhR 👉 Quantum Jobs USA: https://lnkd.in/dN2UW5BR WhatsApp channel for US quantum Jobs: https://lnkd.in/dej6ZzQv #QuantumComputing #QuantumJobs #CareerChange #TechCareers #QuantumTech #FutureOfWork #JobSearch #Hiring2026 #QuantumJobsUSA #QuantumJobsList 📌 Content Usage #Policy: This infographic may be reused for educational or editorial purposes. Kindly provide proper attribution to ‘Quantum Jobs List ( www.quantumjobslist.com )’ with a link to the original source. #QuantumJobs #NoDegreeNoProblem #FutureTech #QuantumComputing #CareerChange #LearnQuantum #TechCareers #Upskilling

🌈 You do not need to spend a single dollar to learn #quantum computing in 2026-27. Here are 9 free courses worth your time 👇 🟢 Beginner 🔹IBM Quantum Learning - build real circuits on IBM hardware from day 🔹one #Xanadu Codebook - interactive exercises right in your browser, no setup needed 🔹QWorld QBronze - #Python notebooks covering gates, states and Grover's algorithm 🔵 Intermediate 🔸MIT OpenCourseWare - full MIT lecture series with problem sets, completely free 🔸#Qiskit Textbook - quantum algorithms in real runnable code 🔸University of St Andrews on Coursera - audit free, covers hardware and circuit design 🟣 Advanced Google Cirq tutorials - NISQ algorithms and noise models from the Google Quantum AI team 🔹Caltech Quantum #Cryptography on edX - BB84, post-quantum standards, audit free 🔹Scott Aaronson lectures on #YouTube - the deepest free dive into why #quantum computers are powerful Total cost? Zero. The #quantum talent shortage is real. There are 3x more open roles than qualified candidates right now. These courses are the fastest free path to closing that gap. -------------------- 👉 Quantum Jobs List (global): https://lnkd.in/dYSJ3XBm WhatsApp channel for job alerts: https://lnkd.in/dxZ_umhR 👉 Quantum Jobs USA: https://lnkd.in/dN2UW5BR WhatsApp channel for US quantum Jobs: https://lnkd.in/dej6ZzQv #QuantumComputing #QuantumJobs #CareerChange #TechCareers #QuantumTech #FutureOfWork #JobSearch #Hiring2026 #QuantumJobsUSA #QuantumJobsList 📌 Content Usage #Policy: This infographic may be reused for educational or editorial purposes. Kindly provide proper attribution to ‘Quantum Jobs List ( www.quantumjobslist.com )’ with a link to the original source. #QuantumJobs #NoDegreeNoProblem #FutureTech #QuantumComputing #CareerChange #LearnQuantum #TechCareers #Upskilling

If you are looking to break into the quantum space or deepen your foundational knowledge, this curated list from Quantum Jobs List is an incredible starting point. The roadmap effectively breaks down the journey from zero prior experience to advanced topics like quantum cryptography and error correction, utilizing high-quality, free resources from industry leaders like IBM, Xanadu, Google, and top-tier universities. For anyone looking to understand the fundamentals of qubits, circuit building, or framework programming like Qiskit and Cirq, the barrier to entry has never been lower. It’s a great reminder that the most valuable investment you can make in this field right now is simply your time. Which of these platforms have you found most effective for hands-on learning? #QuantumComputing #QuantumPhysics #DeepTech #ContinuousLearning #Semiconductors