Data Scientist & Data Engineer
I work across the full data science pipeline — from raw data to tested, deployed models — and pair that with software engineering to build real, usable products.
Explains CPU and device concurrency, interrupts and traps, bootstrapping, I/O flow, and storage hierarchy basics.
Breaks down system components, user and OS viewpoints, kernel responsibilities, and the API vs system call model.
Explains estimate reconciliation and compares LOC, FP, process-based, UCP, and agile estimation using standard formulas and examples.
Covers software risk types, risk identification factors, assessment checklists, projection steps, risk exposure, and RMMM planning.
Explains the five core planning activities, project task set, scope definition, feasibility checks, and schedule setup for reliable software delivery.
Explains software crisis symptoms, causes, quality attributes, and the ACM code of ethics as a practical framework for responsible engineering.