A geneticist studies how traits are inherited and how DNA works, in labs, clinics, or on computers. In the US this is a graduate-level career: most geneticists hold a master's or a PhD, and many do postdoctoral training. The path has three stages. First you build the biology, statistics and coding base. Then you gain real lab and data-analysis experience, which is what gets you hired. Finally you specialize (research, clinical, or computational) and lead projects. Everything below uses free resources. If you want to see patients as a clinical geneticist, you will need extra licensing, which is
See the full roadmap free
Every stage from beginner to expert, with lessons, practice drills, projects, interview questions and free resources. Free with a Rolearch account.
Stage 1 of 3 · about 20 weeks
Understand how genes work and learn to read data with basic statistics and code.
Core genetics and molecular biology
Every task you will do, from reading a variant report to designing an experiment, rests on knowing how DNA becomes RNA becomes protein, and how traits pass between generations.
Statistics and probability for genetic data
Genetics is probability. Inheritance ratios, allele frequencies and significance of results all depend on it. Without stats you cannot tell a real finding from noise.
Programming with Python and R
Job postings list Python and R constantly. Sequencing produces files too big for Excel, so you need code to filter, summarize and plot them.
Lab notebooks and basic lab techniques
Keeping a clear notebook is a core task of the job, and it protects your results. Knowing PCR and gel electrophoresis helps you understand the data you will later analyze.
Linux command line and Git
Genomics tools run mostly on Linux servers, and Git keeps your analysis reproducible and shareable, which employers value.
Then 2 more stages (about 104 weeks in all) with lessons, drills, projects, 6 interview questions with strong answers and free resources.