Question 1

I'm not technical — can I still join?

Accepted Answer

Yes — non-technical is exactly who one of these two programs is built for. AI Training for Professionals is role-based and requires no coding at all: it has dedicated tracks tailored to Managers (Sales, Ops, HR), Creative Professionals, and Educators, each teaching the specific AI-native workflows and automations relevant to that role rather than generic prompting tips. AI Training for Engineers, by contrast, is the hands-on, code-first track built for working developers — it covers structured LLM workflow design, evaluation and reliability harnesses, and building agents on the Model Context Protocol, all of which assume you're already comfortable writing and shipping code. Both run as small, live cohorts capped at 8 seats with direct instructor access, so pick based on whether your day-to-day work involves writing production code or not, not based on how technical you feel in general.

Question 2

What's the difference between the two programs?

Accepted Answer

The split is role, not difficulty. AI Training for Professionals runs 4 weeks at 6–8 hours per week and teaches AI-native workflows and automations mapped to your specific role — Managers, Creative Professionals, and Educators each get role-relevant tools and use cases, no coding required. AI Training for Engineers also runs 4 weeks but at a lighter 3 hours per week, aimed at working developers building production-grade LLM systems: structured prompting and system architecture for reliable workflows, evaluation harnesses that catch failures before users do, and designing agents wired into real tools via the Model Context Protocol (MCP). Both are live, small-cohort programs (capped at 8 seats) rather than pre-recorded courses, so you get direct instructor access either way — the difference is entirely in whether the curriculum assumes you already write code day-to-day at your job.

Question 3

Is there a job guarantee on these programs?

Accepted Answer

No — and that's intentional, not a gap. These are fast, practical upskilling programs designed for people who already have a career and want to add AI fluency to it quickly, not job-placement bootcamps built around a career change. Because they run just 4 weeks at a handful of hours per week rather than months of full-time study, they're structured to fit alongside your existing job, not replace it. If what you actually want is a guaranteed path into AI engineering as a new career — complete with the structured curriculum, JobCamp support, and a 100% tuition refund if you don't land a qualifying job offer within 10 months — the AI Software Engineering Bootcamp is the program built for that instead. Think of AI Training for Professionals and AI Training for Engineers as acceleration for the career you already have, and the bootcamp as the path into a new one.

Question 4

How big are the cohorts?

Accepted Answer

Small on purpose, and capped rather than just described as small: both AI Training for Professionals and AI Training for Engineers hold cohorts to 8 seats. That size exists so you get direct access to instructors and live office hours instead of sitting in a lecture-style webinar with dozens of other participants — every session is live instruction, not pre-recorded video, which only works well at this scale. It also means your specific role or codebase context (whether you're a manager automating a workflow or an engineer shipping an agent) can actually get addressed during the program rather than getting generic, one-size-fits-all answers. If you need this same format at larger scale for an organization, AI Training for Tech Teams runs the same live, hands-on structure for teams of 5 or more engineers instead of the individual 8-seat cohorts.

Question 5

Can I train my whole team instead of enrolling individually?

Accepted Answer

Yes — AI Training for Tech Teams exists specifically for that. Rather than sending individual engineers through the standard 8-seat cohorts, it runs private cohorts (or, if you prefer, open cohorts) for teams of 5 or more engineers at once, so your whole team learns the same AI-native workflows, evaluation practices, and agent-building patterns together rather than fragmenting the knowledge across whoever happened to enroll separately. The format stays live and hands-on — the same instructor-led, practical structure as the individual programs, not a webinar or pre-recorded course — which matters more, not less, at team scale, since it lets instructors address your team's actual codebase and workflows instead of generic examples. If you're deciding between sending people individually or training as a group, team cohorts are usually the better fit once you have 5 or more engineers who'd benefit from AI fluency at the same time.

Become AI-native in 4 weeks.

No code, or code-first?

AI Training for Professionals

AI Training for Engineers

Practical AI skills, not theory.

Role-based workflows

LLM workflow design

Evaluation & reliability

Agents & MCP

Production deployment

Picking a program, answered.

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