Week 1: Python Reset + DSA Launch
Sep 15–21 · Target times: Easy ≤ 15m · Medium ≤ 30m · Hard ≤ 55m
Daily routine: 75 min DSA (timed) + 10 min syntax typing + 35 min second block. Talk out loud. No AI autocomplete. Over cap → 48h redo queue.
Revise (topic checklist)
Note: Drill from memory, no autocomplete. 10 min SyntaxCache/SpeedCoder. Outcome: write list ops + comprehensions without lookup.
Revise (topic checklist)
Note: deque = your BFS/queue workhorse. Outcome: write defaultdict/Counter/deque from memory.
Revise (topic checklist)
Note: Watch NeetCode 'Python for Coding Interviews'. Outcome: heapq + string ops from memory; accounts ready.
DSA problems (75 min, timed)
Second block (35 min) — System Design + CS: OS Basics
Process vs thread, context switching, concurrency vs parallelism, virtual memory, deadlock (4 conditions). Most important: process vs thread + why concurrency matters. Read OSTEP intro / Neso Academy OS (first 5). Outcome: explain process vs thread + a deadlock scenario.
DSA problems (75 min, timed)
Second block (35 min) — ML/DL: ML Metrics & bias-variance
Precision/recall/F1, ROC-AUC vs PR-AUC, bias-variance, overfitting, regularization (L1/L2). Most important: PR-AUC vs ROC-AUC on imbalanced data (your medical-imaging domain). Watch StatQuest. Outcome: explain when PR-AUC beats ROC-AUC.
DSA problems (75 min, timed)
Second block (35 min) — System Design + CS: OS Basics
Process vs thread, context switching, concurrency vs parallelism, virtual memory, deadlock (4 conditions). Most important: process vs thread + why concurrency matters. Read OSTEP intro / Neso Academy OS (first 5). Outcome: explain process vs thread + a deadlock scenario.
DSA problems (75 min, timed)
Second block (35 min) — ML/DL: ML Metrics & bias-variance
Precision/recall/F1, ROC-AUC vs PR-AUC, bias-variance, overfitting, regularization (L1/L2). Most important: PR-AUC vs ROC-AUC on imbalanced data (your medical-imaging domain). Watch StatQuest. Outcome: explain when PR-AUC beats ROC-AUC.