Most beginners get stuck not because they lack knowledge, but because they never convert knowledge into the things employers actually respond to. Getting hired is a distinct project from learning, and it has its own steps.
Step 1: pick a target role
Vague goals get vague results. Name one role - applied AI analyst, machine learning engineer, AI implementation - and work backward from real job listings. This tells you exactly what to learn and prove. See assess if you have AI skills employers want.
Step 2: build evidence
Two or three finished projects tied to that role beat a shelf of certificates. Follow how to build an AI portfolio as a beginner. Add a recognised credential if the role scans for one - do online AI certifications help you get hired.
Step 3: tell a coherent story
Connect your past to your target. Career changers especially should read transition to AI from another career - your old field is leverage, not a gap.
Step 4: get in front of people
Applications alone are slow. Referrals and relationships move faster - how to network your way into an AI career.
Step 5: prepare for the conversation
Be able to explain your projects, your reasoning and where AI helps a business. A course like Strategic Application of AI in Business sharpens that fluency.
The bottom line
Getting hired is its own project: target a role, build evidence, tell a clear story, network, and prepare to talk. Stop collecting courses and start producing proof. Next: how to get an AI job with no experience.