Section	Candidate Type	Eligible?	Typical Requirement	Notes
Primary fit	Data analysts and senior analysts	Yes	Daily work with SQL and BI tools	Primary audience — course maps directly to the analyst workflow end to end.
Primary fit	BI developers and BI leads	Yes	Building reports, dashboards, and semantic layers	Strong fit — AI patterns accelerate dashboard narratives and stakeholder communication.
Primary fit	Analytics engineers	Yes	Owning transformations in dbt or similar tools	Useful for documentation, testing, and explaining models to stakeholders.
Adjacent backgrounds	Data scientists focused on applied work	Yes	Experience with SQL and Python	Helpful for text classification, stakeholder comms, and productizing findings.
Adjacent backgrounds	Operations and growth analysts	Yes	Embedded in a business function	Useful for experimentation readouts, segmentation, and executive summaries.
Adjacent backgrounds	Product managers with analytics ownership	Yes	Running self-serve analytics or KPIs	Fits PMs who write queries themselves and need to communicate findings clearly.
Experience level	Junior analysts (0-2 years)	Yes	Basic SQL and dashboard building	Course provides structure and AI patterns that compress the ramp-up curve.
Experience level	Mid-level analysts (2-5 years)	Yes	Comfortable across SQL, BI tools, and stakeholder work	Best fit — immediately replaces repetitive parts of the workflow with AI patterns.
Experience level	Senior analysts and analytics leads	Yes	5+ years and team responsibility	Useful for setting team AI standards, governance, and scaling analytics practice.