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Velza Academy · AI-Powered Professional

Become an AI-Powered Professional, live.

Three weeks of live, hands-on work on the skills that make AI reliable. Prompts and context, memory across steps, work that runs and checks itself, and how to tell what broke when it breaks. No coding background needed.

VELZA ACADEMY AI-Powered Professional LIVE COHORT
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Early bird pricing ends in 00d 00h 00m 00s

Your instructor

Mike Wheeler, founder of Velza Training and Consulting

Learn from Mike Wheeler

Mike Wheeler is an AI and Salesforce trainer and O’Reilly author. He has taught well over 500,000 global learners on major platforms such as edX, LinkedIn Learning, Pearson, and Udemy, and he built the first generative AI course on edX. He teaches for non-coders, working backward from your career goals.

500,000+ global learners taught O’Reilly author

The curriculum & schedule

Your 6 live sessions

Six live sessions over three weeks: three teaching sessions plus three optional office hours. All times Central. Can’t make one live? Every session is recorded.

Session1
Sunday, August 2
7:30-8:30 PM Central

Prompt & Context Engineering

Most of what makes AI useful is not how you ask, it is what the AI knows when you ask. This week builds both.

  • The five parts of a prompt that make it answerable: objective, context, constraints, examples, output format
  • How to tell a prompt problem from a model, data, or retrieval problem, so you stop rewriting prompts that were never the issue
  • The three places context lives, memory, knowledge stores, and live connectors, and how to pick the right one
  • How to give the AI the background it needs up front so it stops guessing
  • You build your own context setup and leave with it working
Week 1
Friday, August 7
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the August Velza Academy cohorts.

Session2
Sunday, August 9
7:30-8:30 PM Central

Memory, State & Loop Engineering

How to make AI work run on its own, remember what happened, and check itself. You follow along in a terminal or a desktop app, whichever you prefer.

  • Where information lives between steps, and what durable memory gives you that a fresh chat does not
  • How to set up work that observes, decides, acts, verifies, and knows when to stop
  • Handing pieces of a job to helpers without losing control of the result
  • The tracker: a running record of what happened, so a failure becomes a fixable ticket instead of a shrug
  • The judge: a second pass that scores the work and never sees the author's own opinion of it, because nothing grades its own homework honestly
Week 2
Friday, August 14
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the August Velza Academy cohorts.

Session3
Sunday, August 16
7:30-8:30 PM Central

Harness Engineering: Making AI Reliable

AI work that ran fine last month quietly stops working. This week is the checks that catch it before it costs you.

  • Why a model plus a harness is the whole system, and what the harness actually does
  • The difference between telling the AI what to do and checking what it actually did
  • How to catch drift, when yesterday's setup silently stops matching today's reality
  • How to find which layer broke when a workflow fails, instead of rewriting the prompt and hoping
  • You leave able to look at a broken AI workflow and say where to look first
Week 3
Friday, August 21
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the August Velza Academy cohorts.

Session1
Sunday, September 6
7:30-8:30 PM Central

Prompt & Context Engineering

Most of what makes AI useful is not how you ask, it is what the AI knows when you ask. This week builds both.

  • The five parts of a prompt that make it answerable: objective, context, constraints, examples, output format
  • How to tell a prompt problem from a model, data, or retrieval problem, so you stop rewriting prompts that were never the issue
  • The three places context lives, memory, knowledge stores, and live connectors, and how to pick the right one
  • How to give the AI the background it needs up front so it stops guessing
  • You build your own context setup and leave with it working
Week 1
Friday, September 11
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the September Velza Academy cohorts.

Session2
Sunday, September 13
7:30-8:30 PM Central

Memory, State & Loop Engineering

How to make AI work run on its own, remember what happened, and check itself. You follow along in a terminal or a desktop app, whichever you prefer.

  • Where information lives between steps, and what durable memory gives you that a fresh chat does not
  • How to set up work that observes, decides, acts, verifies, and knows when to stop
  • Handing pieces of a job to helpers without losing control of the result
  • The tracker: a running record of what happened, so a failure becomes a fixable ticket instead of a shrug
  • The judge: a second pass that scores the work and never sees the author's own opinion of it, because nothing grades its own homework honestly
Week 2
Friday, September 18
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the September Velza Academy cohorts.

Session3
Sunday, September 20
7:30-8:30 PM Central

Harness Engineering: Making AI Reliable

AI work that ran fine last month quietly stops working. This week is the checks that catch it before it costs you.

  • Why a model plus a harness is the whole system, and what the harness actually does
  • The difference between telling the AI what to do and checking what it actually did
  • How to catch drift, when yesterday's setup silently stops matching today's reality
  • How to find which layer broke when a workflow fails, instead of rewriting the prompt and hoping
  • You leave able to look at a broken AI workflow and say where to look first
Week 3
Friday, September 25
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the September Velza Academy cohorts.

Session1
Sunday, October 4
7:30-8:30 PM Central

Prompt & Context Engineering

Most of what makes AI useful is not how you ask, it is what the AI knows when you ask. This week builds both.

  • The five parts of a prompt that make it answerable: objective, context, constraints, examples, output format
  • How to tell a prompt problem from a model, data, or retrieval problem, so you stop rewriting prompts that were never the issue
  • The three places context lives, memory, knowledge stores, and live connectors, and how to pick the right one
  • How to give the AI the background it needs up front so it stops guessing
  • You build your own context setup and leave with it working
Week 1
Friday, October 9
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the October Velza Academy cohorts.

Session2
Sunday, October 11
7:30-8:30 PM Central

Memory, State & Loop Engineering

How to make AI work run on its own, remember what happened, and check itself. You follow along in a terminal or a desktop app, whichever you prefer.

  • Where information lives between steps, and what durable memory gives you that a fresh chat does not
  • How to set up work that observes, decides, acts, verifies, and knows when to stop
  • Handing pieces of a job to helpers without losing control of the result
  • The tracker: a running record of what happened, so a failure becomes a fixable ticket instead of a shrug
  • The judge: a second pass that scores the work and never sees the author's own opinion of it, because nothing grades its own homework honestly
Week 2
Friday, October 16
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the October Velza Academy cohorts.

Session3
Sunday, October 18
7:30-8:30 PM Central

Harness Engineering: Making AI Reliable

AI work that ran fine last month quietly stops working. This week is the checks that catch it before it costs you.

  • Why a model plus a harness is the whole system, and what the harness actually does
  • The difference between telling the AI what to do and checking what it actually did
  • How to catch drift, when yesterday's setup silently stops matching today's reality
  • How to find which layer broke when a workflow fails, instead of rewriting the prompt and hoping
  • You leave able to look at a broken AI workflow and say where to look first
Week 3
Friday, October 23
2-3 PM Central

Office Hours Optional

Job-market intel and open Q&A, shared across the October Velza Academy cohorts.

What you’ll learn

The layers you’ll learn

Seven things that decide whether AI works once or works every time. Hover any one for what it means.

What you’ll walk away with

By the end, you’ll be able to

Companies are adopting AI faster than they can find people who know how to operate it.

These are in-demand skills. They show up on AI certification exams, they show up in job listings, and they carry over to whatever tools your company already runs. You do not need a certification to start using them.

What’s included

Everything that’s included

6 live sessions

Three teaching sessions plus three optional office hours, live over three weeks. Sundays at 7:30-8:30 PM Central.

1-year replay access

Every session is recorded, and you keep access to the replays for a full year, so you can rewatch any time you need them.

Weekly hands-on projects

You leave each session with something you can use at work the next day. Week one, a setup for organizing what your AI needs to know. Week two, a way to keep track of what happened and a second pass that checks the work. Week three, a way to find out why something broke.

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Questions, answered

Frequently asked

Do I need to write code?

You do not need a coding background, and you will not be asked to learn a language. The AI generates the commands and explains what they do. Your job is to direct the work and verify the result, not to write it from scratch. Work wherever you are comfortable: a terminal, a desktop app work surface, or locally.

Is this the right course for me?

It is if you have used AI chat before, want to run real work through it rather than just ask it questions, and are willing to check its output instead of trusting it. You do not need a coding background. It is not the right course if you are a working software developer looking for depth on agent frameworks or SDKs. This is the just-enough version: enough to run the work and verify it, without becoming an engineer.

How is this different from a prompting course?

Prompting is one of five layers we cover. The other four (context, memory, loops, and the harness) are what separate an AI workflow that works once from one that works every time.

What tools will we use?

We stay tool-agnostic on purpose. The concepts transfer across whatever you or your employer already run. Bring the AI tool you actually use. Demos are recorded in one tool so you can see the whole thing work end to end, and we name the equivalents as we go.

What if I can’t make a session live?

Every session is recorded and shared, and you keep access to the replays for a full year, so you can watch or rewatch any of them on your own schedule. The optional Friday office hours are recorded too.

Why a live cohort instead of studying on my own?

Self-study stalls. A live cohort gives you a fixed three-week pace, the chance to ask questions in real time, weekly hands-on work, and optional office hours. You actually finish.

What is your refund policy?

You can request a full refund within 24 hours of the start of the first live session.