Professional Certificate in Research Methodology Batch-02

FAQs

You’ll complete a research blueprint—from problem statement and questions/hypotheses to a defensible design, ethics protocol, data plan, analysis approach, and report outline.
No. We start from fundamentals and build up to advanced concepts like mixed methods and triangulation.
Both. Examples span theses, policy studies, UX/product research, market research, and social-impact evaluations.
Yes—foundational workflows for NVivo-style coding and survey tooling; guidance on spreadsheet/entry tools and referencing (APA). (Tool choice is flexible.)
We focus on research design, measurement, and validity/piloting. You’ll get essentials for survey construction and interpretation; deep stats are referenced, not the main goal.
A polished problem statement, research questions/hypotheses, a structured literature-review framework, sampling & design plan, qualitative/quantitative instruments, and a report/presentation outline.
A polished problem statement, research questions/hypotheses, a structured literature-review framework, sampling & design plan, qualitative/quantitative instruments, and a report/presentation outline.
You’ll learn convergent and sequential mixed-methods designs to integrate interviews, surveys, and observations into one coherent study.
AI can assist (brainstorming, language editing, code suggestions, transcription), but cannot be an author. Most institutions/journals allow AI with clear disclosure and human verification. You remain accountable.
AI can speed coding, summaries, and starter analyses, but it also hallucinates, miscodes, and reflects training bias. Build guardrails: independent verification, inter-coder checks, prompt/version logs, and full reproducibility.
Assume prompts may be logged. Do not paste identifiable/sensitive data into consumer tools. Use approved/enterprise instances, de-identify data, and reflect AI usage in consent/IRB documents.