It depends on the course type, depth, and how much time you can commit. Typical durations for AI courses aimed at business professionals:

• Mini workshop / executive briefing: 2–8 hours (one session or a couple of half-days). Good for high-level awareness and strategy.
• Short applied course: 1–6 weeks (2–6 hours/week). Teaches practical tools, use cases, and simple hands‑on exercises (e.g., prompt engineering, using off‑the‑shelf AI tools).
• Bootcamp / intensive workshop: 2–5 days (full‑time). Fast, hands‑on skills for specific tasks (data‑driven decision making, automation).
• Professional certificate: 2–6 months (3–8 hours/week). Deeper coverage of AI concepts, business applications, vendor tools, and a capstone project.
• Graduate or executive education (postgrad certificate / part‑time master’s): 6 months–2 years (varied weekly load). For strategists who need rigorous technical understanding plus leadership & implementation planning.

Estimated total study hours by level:

• Awareness: 2–8 hours
• Practical competency: ~20–60 hours
• Job‑ready applied skills: ~80–200 hours
• Advanced/leadership level: 200+ hours

Things that affect duration:

• Prior technical background (non‑technical learners often need more time).
• Depth (strategy vs. hands‑on ML engineering).
• Learning format (self‑paced vs. instructor‑led).
• Project requirement (capstones add time).
• Time available per week.

Recommended approach for busy professionals:

• Start with a 2–8 hour executive course to set goals.
• Follow with a 4–8 week applied course (2–5 hours/week) that includes a mini project tied to your work.
• Use microlearning (15–30 minute modules) and put new skills into practice weekly to solidify learning.

If you want, tell me how much time per week you can commit and your goal (awareness, implement a pilot, lead AI strategy), and I’ll recommend a specific realistic timeline and types of courses.