Frequently asked questions

It is Colaberry's program for going from using AI to architecting real systems with Claude. You join through an AI Membership, learn with Claude, build real guided projects, and follow a focused 12-week build path from idea to a working AI system. It is fully online and mentor-led.

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No. You do not need to become a machine-learning engineer or have a computer-science degree. You need practical skills you can apply, and the right guidance and structure to build them. Beginners are welcome and start step by step.

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Three things, in order: Learn with Claude, using it as a real work partner for research, analysis, planning, and problem solving; build real projects, guided hands-on work you can explain and show; and deploy in the real world, moving from concept to a working AI system over a 12-week build path.

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Yes. Complete the membership and your guided projects and you receive a Colaberry-issued AI Systems Architect certificate, a verifiable credential you can share on LinkedIn and add to your resume.

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Yes, on the monthly plan. At $199 a month, billed monthly, you can cancel anytime and keep access through the month you have paid for. The $149 a month annual plan ($1,788 a year) is the better value if you are committed to the full program. Teams and employers can also license transferable annual seats.

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Everyone learns the same way, there are just three ways in: working professionals who want practical AI skills they can use at work; beginners and career switchers starting AI from the ground up; and builders and founders who want to turn an idea into a working system.

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The Open House is free to attend, with no payment required to explore what is included. Membership is one price that covers everything, and you choose how you pay: $199 a month month-to-month with cancel anytime, or $149 a month billed annually ($1,788 a year), which is our best value. It is the same full membership either way, the only difference is how you pay.

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A 90-minute live online session with demos, real student work, career pathways, and a Q&A. You will see exactly what is inside the membership, how members learn with Claude, and how to get started. See upcoming dates on our Events page.

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You build a set of real, portfolio-grade projects rather than toy exercises: a Business Workflow Assistant with reusable AI Skills, a multi-agent AI team with an Enterprise Prompt Library, a working MCP server integrated with a real system, and a complete Solution Architecture Package.

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You finish with three things you can put in front of any employer: a real AI system deployed in the real world, a GitHub portfolio of guided projects, and a verifiable AI Systems Architect certificate. Free courses leave you with a watch history; this leaves you with proof of capability.

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The membership includes Anthropic Architect certification prep, so you prepare for an Anthropic-backed knowledge credential while you build. The principle is simple: Anthropic certifies knowledge, Colaberry certifies capability. You walk into conversations with both the credential and a deployed system to prove it.

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One membership includes everything, with no separate course fees and no per-course tuition. It covers the full build path, certification prep, a hands-on internship experience, and guided GitHub portfolio projects, all under the single price.

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No. We host a free Open House so you can see exactly how the program works before you commit a dollar. It is your chance to see demos, real student work, and how members learn with Claude, at no cost.

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No professional engineering background is required. It is built for career changers and working professionals who are comfortable with basic software concepts and want to build with AI. Beginners are welcome and start step by step.

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It is the same full membership, the only difference is how you pay. $199 a month is billed monthly, so you can cancel anytime. $149 a month is billed annually ($1,788 a year) and is the best value. Both plans include everything: the full build path, Anthropic certification prep, the internship experience, and the guided GitHub portfolio projects.

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