Artificial Intelligence is rapidly transforming bioinformatics but using AI correctly, safely, and effectively in biological research requires more than just asking questions.

This course is a complete, practical guide to using AI responsibly in bioinformatics and genomics, with a strong focus on RNA-seq, variant analysis, pipeline development, interpretation, and scientific reporting. You will learn where AI truly adds value, where it must not be trusted, and how to combine AI with Linux, Python, and standard bioinformatics tools to accelerate real research workflows.

Instead of replacing bioinformatics tools, this course teaches you how to use AI as a research assistant for experimental design, pipeline generation, debugging, biological interpretation, hypothesis development, and professional scientific writing while maintaining reproducibility, accuracy, and ethical integrity.

Through hands-on examples, real-world case studies, structured prompt libraries, and capstone projects, you will build AI-assisted workflows that reflect how modern bioinformatics research is actually conducted in academia and industry.

This is not a theory-only course.

You will work with:

• Real RNA-seq and genomics scenarios

• Step-by-step prompting examples

• Pipeline generation and debugging exercises

• Interpretation of real biological outputs

• AI-assisted report writing

• Case studies reflecting real research workflows

You will see how AI behaves with good prompts vs poor prompts, how hallucinations appear, how errors emerge, and how to systematically detect and correct them.

The goal is not automation for automation’s sake the goal is professional-grade bioinformatics practice.

Whether you are a student, researcher, or professional, this course equips you with future-ready skills to work faster, think more clearly, and communicate your bioinformatics results with confidence without sacrificing scientific rigor.

This course does not promise shortcuts. It promises clarity, structure, responsibility, and professional growth.

If you want to use AI the right way in bioinformatics with confidence, ethics, and scientific credibility, this course is built for you.