CS CORNER Sunita Rai

🎯 LINKEDIN TIPS FOR DEVELOPERS Profile optimize karo: 1️⃣ Headline: "Python Developer | Automation Expert" NOT "Student" or "Fresher" 2️⃣ Summary: • What you do • Skills (Python, pandas, etc) • Projects (2-3 lines) 3️⃣ Featured: • GitHub repos • Projects • Certificates 4️⃣ Post regularly: • Python tips • Mini tutorials Clients LinkedIn se milte hain! 💼 for freelancing, for contractual jobs, for part time jobs Double Tap ♥️ For More

ESSENTIAL ARRAY PATTERNS 📌 Every Developer Should Know 1. TWO POINTERS Find pairs, remove duplicates, compare elements from both ends, and optimize array traversals. 2. SLIDING WINDOW Solve subarray and contiguous sequence problems efficiently without repeatedly recalculating values. 3. PREFIX SUM Answer range-sum and cumulative queries quickly by reusing previously computed sums. 4. KADANE'S ALGORITHM Find the maximum-sum subarray in O(n) time. 5. BINARY SEARCH Whenever the search space is sorted or monotonic, think O(log n) instead of scanning everything. 6. CYCLIC SORT Useful for finding missing, duplicate, or misplaced numbers when values belong to a known range. 7. MERGE INTERVALS Handle overlapping, merging, and scheduling interval problems efficiently. 8. MONOTONIC STACK Solve next greater/smaller element problems and many range-optimization problems in O(n). 9. HASH MAP / FREQUENCY COUNT Count occurrences, detect duplicates, and perform fast lookups using hashing. 10. SORTING + GREEDY Sort the data first, then make locally optimal decisions to reach the best overall result. ✅ THE GOAL Don't memorize individual solutions. Learn to recognize the pattern behind the problem. Pattern recognition → Faster approach → Better complexity → Stronger interview performance

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Nokia is hiring Position: Software Test Engineer Qualification: Bachelor’s/ Master’s Degree Experience: Experienced Location: Bangalore, India (Hybrid) 📌Apply Now: https://jobs.nokia.com/en/sites/CX_1/jobs/preview/37314/?keyword=engineer&location=India&locationId=300000000471745&locationLevel=country&mode=location

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🚀 GigaChat 3.5 Reasoning — a new open-source LLM that thinks before it answers. It breaks problems into stages, builds a plan, checks intermediate results, and self-corrects. Built on GigaChat 3.5 Ultra, it explores multiple step-by-step reasoning paths for math & coding, using automated verification to reinforce correct answers. ⚡️ Proprietary linear attention makes it highly efficient on long contexts, retaining key points without re-matching from scratch. It’s also token-efficient: uses 37% fewer tokens than DeepSeek V4 Flash Preview on math problems! 📈 Benchmark gains over non-reasoning version: • IFBench: 44 → 77 • Natural Plan: 64 → 80 • LiveCodeBench v6: 56 → 85 📦 MIT license. Weights on Hugging Face: fp8 | bf16