AI headlines move fast, but the skills gap behind them doesn’t close by reading about the latest model launch. Five real, currently-enrollable programs — from a $99 no-code credential to a technical NVIDIA exam — make up an actual learning path right now. Here’s what each one covers, what it costs, and the order that makes sense to take them in.
Step 1: Google Cloud’s Generative AI Leader ($99)
This is the entry point for anyone who needs to speak intelligently about generative AI without writing a line of code — product managers, executives, marketers. The exam runs 90 minutes with 50 to 60 multiple-choice questions, costs $99 USD, and the resulting certification stays valid for three years. Google pairs it with a free, self-paced learning path on Google Cloud Skills Boost, so the prep material costs nothing even though the exam itself isn’t free.
Step 2: DeepLearning.AI’s Free Short Courses
Andrew Ng’s DeepLearning.AI runs a library of free, 1-to-3-hour short courses hosted on Coursera, several co-taught with engineers from OpenAI, Anthropic, LangChain, and Hugging Face. If you’re still non-technical, start with “Generative AI for Everyone,” Ng’s own conceptual overview. Once you’re ready to actually touch code, the catalog’s hands-on modules on prompt engineering and building with LLMs are the cheapest way to go from theory to practice — they cost nothing and take an afternoon, not a semester.
Step 3: Pick a Cloud — AWS or Azure
Once the concepts are solid, a vendor-specific foundational certification proves you can apply them on an actual platform. AWS Certified AI Practitioner (exam code AIF-C01) costs $100, runs 65 questions in 90 minutes, and requires a scaled score of 700 out of 1000 to pass — the same foundational-tier price AWS charges for its Cloud Practitioner exam. On the Microsoft side, AI-900 (Azure AI Fundamentals) was retired on June 30, 2026, and replaced by AI-901, which covers an expanded scope of Azure’s AI services and responsible-AI principles for around $99, though the exact fee varies by the country where you sit the exam. Pick whichever cloud shows up most in job listings you actually want.
Step 4: Go Technical — NVIDIA’s Deep Learning Institute
This is the rung for people who want to build and deploy models, not just discuss them. NVIDIA’s Deep Learning Institute (DLI) offers 13 certification exams ranging from $125 to $500, with NCA-GENL — the NVIDIA-Certified Associate: Generative AI LLMs exam — as the accessible $125 entry point. Self-paced prep courses run $30 to $90 each, and a handful of DLI’s self-paced courses, mostly in the Omniverse, Isaac Sim, and AI-agent tracks, are free. NVIDIA has also run 50%-off exam promotions around its GTC conferences, so it’s worth timing a purchase around one if your schedule allows.
The Order, and the Real Cost
Run the path in this sequence: free DeepLearning.AI short courses to build intuition, then Google’s $99 Generative AI Leader exam to formalize the non-technical layer, then an AWS ($100) or Azure (~$99) foundational cert to prove platform fluency, then NVIDIA’s $125 NCA-GENL once you’re ready to get technical. All told, that’s roughly $325 to $425 in exam fees for a path that runs from zero to genuinely employable AI literacy — and apart from NVIDIA’s instructor-led workshops, every step on this list is self-paced, so it fits around a full-time job rather than requiring one to pause for it.
