Break work into steps
Take a recurring task apart into the steps it really has, so each can be handled on its own.
Partners and press
Overview
Doing it once is a trick. Doing it every week is a workflow.
Applied AI Foundations is OpenAI Academy’s second free, self-paced Foundations course, for ChatGPT users with some experience. In 75–90 minutes you break a task into steps, define inputs and outputs, and build repeatable workflows with review points. It follows AI Foundations and leads to Agents and Workflows, and OpenAI says its badge is not a certification.
5Modules
10–20Questions
1.25–1.5Hours
7Roles
What it covers
Learn all the way down.
Learn all the way down.
Perform when it matters.
Choose capabilities
Decide which ChatGPT capability each step needs, rather than using one tool for everything.
Define inputs and outputs
Say what goes into each step and what must come out, so a workflow can run the same way twice.
Build in review points
Put checkpoints where a person looks at the result before the next step builds on it.
Course outline
Turn the task you repeat
Turn the task you repeat
into a workflow you can rerun.
We design this course ourselves. OpenAI issues the credential, and LUNARTECH is independent of OpenAI.
Not every task deserves a workflow. You learn to spot recurring work with clear steps and a predictable result, and to leave alone the tasks that depend on judgment you cannot write down.
- Signs a task repeats enough to justify the effort
- Tasks that suit a workflow and tasks that do not
- Describing the current process as it really runs
- Estimating time saved and risk added
- Choosing one task to start with
You build A task inventory that marks which of your recurring tasks suit a workflow.
A workflow is a task taken apart. You split one job into the small steps it really contains, name what each step does, and find the steps where AI can help and the ones a person should keep.
- Walking through a task and writing every step
- Making each step small enough to check
- Separating gathering, thinking and producing
- Marking which steps need a person
- Drawing the steps as a simple flow
You build A step-by-step map of one real task, with each step named.
One approach does not fit every step. You match steps to what ChatGPT can do, such as searching for information, reading files, analyzing data, drafting and reformatting, and choose the lightest option that works.
- What the main ChatGPT capabilities are for
- Looking things up versus reading your own files
- Analyzing data versus writing about it
- Drafting, rewriting and reformatting steps
- Choosing the lightest tool that does the job
You build A capability choice, with a reason, for each step of your task map.
A step that is vague on the way in gives a vague result on the way out. You state exactly what each step receives and what it must produce, so the next step, or the next person, can rely on it.
- Stating what each step receives
- Describing the output in a fixed format
- Using templates and examples to keep outputs steady
- Passing results cleanly from one step to the next
- Handling missing or messy input
You build An input and output sheet for every step in your workflow.
Assemble the steps into one workflow you can run again and hand to a colleague. You place review points where a person checks the result before the next step builds on it, then test and refine the whole run.
- Writing the workflow as reusable instructions
- Placing review points where errors would spread
- Running it twice and comparing results
- Fixing the step that varies
- Sharing the workflow with someone else
- Keeping a note of changes
You build A tested, repeatable workflow for one recurring task, with review points marked.
Issued by
Certifying body · Independent of LUNARTECH
OpenAI
A certification in early pilot, and free Academy courses across Foundations, Codex and the API. OpenAI says its Academy badges and certificates of completion are not certifications, and don’t guarantee eligibility for one. Availability is still changing, so check OpenAI’s own pages before planning around any of these.
How you get there
Top-tier roles go to people who can do the work.
Top-tier roles go to people who can do the work.
Here’s how you get there.
Know where you start.
OpenAI pitches it at ChatGPT users with some experience, as the follow-on to its AI Foundations course.
Work through the course.
Five modules, designed by LUNARTECH, at your own pace.
Earn it with OpenAI.
OpenAI issues the credential, so you earn it directly with them.
Support
Support at every stage.
Support at every stage.
You won’t be working through this alone.
Before you start
Try it first.
A 3-day free trial opens a selection of the content. Your card is only charged once it ends.
While you learn
Mentors within reach.
Stuck on a concept? Reach out to a mentor whenever you need help.
While you learn
One-on-one sessions.
On the yearly plan, one-on-one sessions give you dedicated support.
Any time
A team behind you.
Write to info@lunartech.ai at any point, from your trial onwards. If your employer is funding you, we’ll set it up with them directly.
All the way through
A schedule that fits around your life.
Your own paceFrom anywhereAt any hour
After the last lesson
Stay in the network.
Your alumni network stays with you: ongoing support, opportunities and industry insight.
Career support
Career support, past the last lesson. Coaching, a sharper resume, real interview preparation and the people to know.
Career direction
Tailored coaching helps you decide where to aim and how to get there.
Strong portfolio
Hands-on projects become work you can show, not just claim.
Resume and profile
Personalized refinement, so what you send says what you can actually do.
Interview preparation
Preparation for the questions that decide it, so you walk in ready.
Network and search
Connections with industry leaders, and an alumni network that stays with you.
Reviews
Real stories from the community.
LUNARTECH Academy has been the most empowering learning experience of my life, giving me a clear, structured path from the absolute basics to building real-world AI systems with confidence.
Your page is fantastic. As a bachelor’s student in Data Science now accepted for a master’s at UConn, your work has been a real source of motivation.
The programme’s clear, bite-sized content and practical projects dramatically improved my speed from fuzzy idea to MVP and my ability to communicate AI value. I followed the system, and it works.
I really appreciate your teaching style and the way you break down complex topics. It has been incredibly helpful.
After years working mainly with R for econometrics, I found your Python machine learning course a refreshing and engaging way to learn Python.
As a Data Science graduate, I want to thank you for the effort you put into making videos to support growing data scientists.
I’ve been following your work since taking your machine learning course, and I’m impressed by your practical approach to applying AI.
Why choose us
Built around how you actually learn.
One standard behind every course, from the first lesson to long after the last.
Hands-on practice
Apply every idea to real problems, so it becomes something you have used, not only seen.
Industry-aligned curriculum
We keep courses current with the tools, techniques and skills the field asks for.
Flexible learning
Study at your own pace, from anywhere, at any hour.
Certificate of completion
Finish the course and earn a certificate that shows what you have learned.
Focus on your success
Personalized learning plans and support structures carry you through the hard parts.
Lifetime alumni network
Stay connected after you finish, with ongoing support, opportunities and industry insight.
Your certificate
It doesn’t raise its voice. Neither will you.
Finish a LUNARTECH course and its certificate is issued in your name, under our signature. OpenAI’s credential comes from OpenAI.
Certificate of completion
Your Name
Applied AI Foundations course
LUNARTECH RISE Academy
Pricing
This course comes with the membership.
This course comes with the membership.
So does everything else.
One membership opens every course, certification, workshop and masterclass in the Academy. Every plan starts with a 3-day free trial. OpenAI issues the credential.
3 days free, then $29.97 a month. Your card is only charged once the trial ends.
Included in every plan
- Every course in the Academy
- Every certification course
- Workshops and masterclasses
- A certificate of completion
- A 3-day free trial
- Learning at your own pace
- The lifetime alumni network
- Upgrades at any time
In practice
Seven roles.
Seven roles.
One credential across them all.
No single job owns it. Here’s where each role leans hardest, and where its work ends up.
- 01Steps
- 02Capabilities
- 03Inputs and outputs
- 04Workflows
-
Weekly reports are the same steps each time. A defined workflow saves the rework.
Steps, Inputs and outputs, Workflows
Operations, Reporting and analysis
-
A workflow can be shared across a team. Review points keep a person in charge.
Capabilities, Workflows
Everyday knowledge work, Customer-facing teams
-
Recurring reports follow the same inputs each cycle. Define them once and build the workflow around them.
Inputs and outputs, Workflows
Reporting and analysis
-
Month-end tasks repeat and rarely change shape. Review points keep a person on every number.
Steps, Workflows
Reporting and analysis
-
Status updates are a task you can break into steps. A checked workflow beats a fresh prompt each week.
Steps, Workflows
Everyday knowledge work, Operations
-
Ticket triage follows rules a workflow can encode. Humans stay on the cases that need judgment.
Capabilities, Workflows
Customer-facing teams
-
Campaign summaries pull from the same sources every time. Say what goes in and what must come out.
Capabilities, Inputs and outputs
Reporting and analysis
- Everyday knowledge work
- Operations
- Reporting and analysis
- Customer-facing teams
Operations Analyst
Weekly reports are the same steps each time. A defined workflow saves the rework.
Over 10,000 students trust LUNARTECH
LUNARTECH gives you the skills
to learn, build, create and lead.
Engineers
Understand systems all the way down. Build the ones others rely on.
Scientists
Understand what the data says. Build models that hold up.
Researchers
Understand the papers. Build on them, and take the work further.
The field
Anyone can use AI.
Anyone can use AI.
Few can engineer it. This is where that starts.
+340%growth in open roles requiring AI skills
Roles and pay
~35,000 open roles right now
Open roles: Built In, Greenhouse, LinkedIn.
Typical salaries: Glassdoor, Levels.fyi, Payscale, Indeed, Ravio, JobRise, U.S. BLS. Military: 2026 U.S. basic pay, drone officers with aviation incentive pay.
Updated November 2026.
FAQ
Frequently asked questions.
Need help? These answers cover most of what people ask before they start.
No. OpenAI issues it. LUNARTECH is independent of OpenAI, and its names and marks belong to it. When you finish a course of ours, you earn a LUNARTECH certificate of completion for that course.
No. We design this course ourselves, around what the credential covers. OpenAI has no part in it, and you still earn the credential directly with OpenAI.
10–20 questions, 1.25–1.5 hours, online, self-paced. The passing score is 80% on the assessment.
OpenAI pitches it at ChatGPT users with some experience, as the follow-on to its AI Foundations course.
We last reviewed it on 5 November 2026, from excerpts of OpenAI’s official pages, because its site doesn’t accept automated readers. Details change, so check the official page before you book.
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The course
Build the skills behind Applied AI Foundations.
Turn a recurring task into a repeatable AI workflow. Start with a free trial, or enroll in a plan and work through the course at your own pace. OpenAI issues the credential.
LUNARTECH is independent of the vendors and certifying bodies listed here. Their names, exam titles and marks belong to them, exams are run by them, and credentials are issued by them. Reviewed 5 November 2026. Catalogues change often, so confirm the details on the official page before you book.
