Growth in DSA is not just about solving problems, but about evolving the way you think. Day 29/100 — Data Structures & Algorithms Journey Today marks a shift in my learning. After practicing multiple problems across different topics, I’m now moving into a new phase — focusing on learning new patterns in DSA and understanding them deeply. Instead of just solving questions, I’ll be: - Identifying patterns behind problems - Learning when to apply each technique - Improving problem-solving intuition - Focusing on optimized approaches New Focus Areas: - Advanced Dynamic Programming patterns - Sliding Window & Prefix Sum techniques - Graph algorithms - Backtracking & recursion patterns Why this shift? Because solving problems is one part, but recognizing patterns quickly is what makes problem-solving efficient. Key Takeaways: DSA is about patterns, not isolated problems Understanding “why” is more important than “how” Learning structured approaches improves speed and accuracy Consistency + strategy = real growth Excited to explore deeper concepts and take my problem-solving skills to the next level 🚀 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

A high school student that I tutor asked me a while ago if one can learn #physics by #programming in #Python. I answered: “Of course!” Since then, I’ve had all kinds of ideas about how to introduce computational physics and numerical methods to advanced high-school or early-level university students. This is the first post in a (long-term) series focusing on numerical methods and computational physics. https://lnkd.in/d5gDAieW

Why the Chemistry lab of the future runs on code. Over the past few months, while transitioning TheChemstore to a custom React and Node.js infrastructure, I’ve also been diving deep into Python to build custom computational tools. The ability to write a script that can automate data analysis or visualize molecular dynamics is rapidly becoming just as critical as knowing how to run a perfect titration. If you are a student or a young professional in the sciences, learning a programming language or mastering AI research tools isn't a distraction—it’s an upgrade. Are you incorporating coding or AI into your chemistry workflow yet? Let me know what tools you are using in the comments! 👇 #TheChemstore #ComputationalChemistry #PythonForScience #Cheminformatics #FutureOfWork #STEM #TechInScience

We are proud to collaborate with Stanford’s Open Source team on the launch of Ship It: Python Packaging for Research Software in the Generative AI Era. This forward-looking course brings together leading Python experts to deliver high-quality, asynchronous training designed to strengthen how research software is built, packaged, and shared. By equipping researchers with practical, sustainable development practices, the program advances the longevity, usability, and real-world impact of scientific outputs in an evolving AI landscape. We look forward to supporting a more resilient and open research ecosystem through this work!

I am so excited to launch ShipIt tomorrow to a new cohort of learners!! This is a 2-week cohort based asynchronous course that takes learners from 0 to a published package on (test) pypi while navigating the ins and outs of test suites, docs and Generative AI. It has been so wonderful to work with Zach Chandler and Ma Francesca Vera on this launch through Stanford Data Science * the Stanford OSPO (open source program office). This is a new flexible teaching format that will allow pyOpenSci to scale their training WHILE also connecting researchers working on #opensource and research software around the world! It is going to be awesome! 💜 💜 💜 💜 💜 💜 💜 💜

We are so grateful to be working with Zach and the Stanford Open Source Program Office. Today we kicked off our first asynchronous Python packaging course — and we cannot wait to see what happens when 65 researchers from open source program offices around the world learn packaging and research software development together. Zach said it better than I could: "Find the good humans, and work with them." That's exactly what is happening here. and the synergy is 🔥 #opensource

Bridging the gap between mathematics and programming is one of the most powerful things we can do for students today. usingMaths.com has published a fantastic free tutorial that teaches senior secondary students how to solve cubic polynomial equations in Python — and then animate an object moving along the curve using Turtle graphics. Here’s what students learn: • The mathematics of third-degree polynomial equations (y = ax³ + bx² + cx + d) • How to derive coefficients from maximum and minimum turning points using calculus • How to implement a Python polynomial solver from scratch • How to build a visual animation that brings the equation to life This is exactly the kind of applied, project-based learning that builds both mathematical rigour and computational thinking — skills that are increasingly critical across STEM fields, data science, machine learning, and software engineering. For educators designing cross-curricular programmes, or students looking to go beyond the textbook, this is a resource worth bookmarking. 🔗 https://lnkd.in/eEvRJ9wk #MathsEducation #Python #STEM #ComputationalThinking #SeniorSecondary #EdTech #CodingEducation

The Oliveira Lab is hosting the Python for Bioengineers Workshop 2.0 as part of Oliveira Outreach and now in its second year. This one-day, hybrid workshop introduces participants to applying Python to biological data through hands-on sessions. No prior programming experience is required. Open to all, with a focus on undergraduate researchers in biomedical and related fields. Highlights: • Intro to Python in biological research • Hands-on coding with biological data • Guest speaker Dr. Tianqi Song • Talks from Oliveira Lab researchers • Networking with Dr. Samuel Oliveira and the lab • Exposure to research at the Joint School of Nanoscience & Nanoengineering (JSNN) 📅 April 11, 2026 🌐 Hybrid format (virtual + limited in-person) 📍 Joint School of Nanoscience and Nanoengineering , Greensboro, NC 🔗 Register: https://lnkd.in/eQDQVe-t Lunch provided for in-person attendees. Spots are limited. Read more about the workshop: https://lnkd.in/eNxryWQb #Python #Bioengineering #STEM #Workshops

🌍 From Equations to Real Simulations Physics becomes powerful when you can see it, simulate it, and control it. That’s exactly what Python in Physics: Model, Simulate, Visualize delivers. 📘 A hands-on guide that transforms: • Equations → Models • Models → Simulations • Simulations → Visual Insights Perfect for: 🎓 Students 🔬 Researchers ⚙ Engineers 💻 Python learners https://lnkd.in/gSBdVTKN   🚀 Don’t just study physics — experience it with Python. Get the book today and start modeling the universe.

📊 Python + Mathematics = Powerful Combo Using libraries like SymPy, you can solve complex mathematical expressions easily. 👉 Symbolic computation 👉 Integration 👉 Advanced math automation 💡 Python sirf coding nahi… research aur engineering ka tool bhi hai. 🚀 Learn tools → Build powerful projects #Python #Sympy #Coding #Developers #Math #Tech