- Module 1: The dawn of AI-native platform engineering
-
The dawn of AI-native platform engineering
-
The dawn of AI-native platform engineering
-
Resources
-
Discussion topic
- Module 2: Platform fundamentals and AI as accelerator
-
Platform engineering fundamentals and the AI recap
-
Platform engineering fundamentals and the AI recap
-
Resources
-
Discussion topic
- Module 3: Shifting down - from writing code to orchestrating intent
-
Shifting down - from writing code to orchestrating intent
-
Shifting down - from writing code to orchestrating intent
-
Resources
-
Discussion topic
- Module 4: Shifting down - builds, testing, and deployments
-
Shifting down - builds, testing, and deployments
-
Shifting down - builds, testing, and deployments
-
Resources
-
Untitled Lesson
- Module 5: Shifting down - Operations, security, and governance
-
Shifting down - Operations, security, and governance
-
Shifting down - Operations, security, and governance
-
Resources
-
Discussion topic
- Module 6: Platforms for AI and ML workloads
-
Building platforms to support ML/AI
-
Building platforms to support ML/AI
-
Example training and inference platform design
-
Resources
-
Untitled Lesson
- Module 7: Reference architectures for data and AI with focus on compliance
-
The Machine Learning / Data Plane
-
The Machine Learning / Data Plane
-
Resources
-
Discussion topic: Module 7
- Module 8: The future of platform engineering roles
-
The evolution of platform engineering
-
The evolution of platform engineering
-
Resources
-
Discussion topic
- Next steps
-
Next steps and outlook
-
Next steps and outlook resources
- Untitled Section
- Course feedback survey
-
Feedback survey
AI in Platform Engineering
Platform engineering is the key to unlocking AI at enterprise scale. This course teaches you to supercharge your entire SDLC with AI-native capabilities, like automating and streamlining everything from initial builds to complex ops and compliance. Finally, you’ll learn to architect "platforms for AI," future-proofing your skill set for the next era of platform engineering.
What you'll learn
By the end of this course, you’ll be able to:
Design the AI-native SDLC: Accelerate everything from agentic coding to self-healing CI/CD pipelines. Unlock conversational observability and AI-driven root cause analysis. Define requirements for hosting data and AI workloads Design reference architectures AI/data reference architectures with focus on compliance and Finops Transition to the next evolution of platform engineering
Who's it for?
Practitioners
DevOps and SREs who want to integrate AI into their workflows, automate complex tasks, and future-proof their careers for the AI-native era.
Platform Engineers
Individual contributors looking to build next-gen AI platforms, manage AI/ML workloads at scale, and lead AI infrastructure best practices within their organization.
Leaders
Head of platforms and product owners, tasked with driving the AI transformation strategy and want to manage architectural shifts towards AI-native platform setups.
8 MODULES · 8 QUIZZES · LIVE SESSIONS INCLUDED
CURRICULUM
Complete the modules in order. Quizzes throughout.
MODULE 1 The dawn of AI-native platform engineering
Navigate the "trust paradox" to align high AI adoption with user trust Differentiate between AI-enhanced platforms and platforms built for AI workloadsShift from manual configuration to AI orchestration and governanceMODULE 2 Platform fundamentals and AI as accelerator
AI in platform engineering principles and self-service adoption AI as 'Interface' vs. 'Capability' across the layers of an Internal Developer Platform The evolution of DevOps into autonomous, AI-native engineering environmentsMODULE 3 Transforming planning and code authoring
The shift in UX: Why AI is becoming the primary interface to empower intent-to-action Use AI agents to turn requirements into executable technical specifications Move from simple coding assistants to agentic coding Orchestrate multi-agent workflows for specialized autonomous software reviewsMODULE 4 Building intelligent and adaptive delivery flows
Enable advanced AI delivery using graph-based backends over linear pipelines Build & test - from "pass/fail" logs to "predict & heal" Enable intent-based releases triggered by natural language and failure predictionMODULE 5 Resilience & control: Managing day 2 operations
Democratizing access through conversational observability Operate & monitor - from "dashboard staring" to "conversational observability" Security & covernance - continuous, automated complianceMODULE 6 Platforms for AI and ML workloads
The requirements of data and ML engineers as new platform user personas Balance specialized compute for model training versus high-availability inference Manage GPU and TPU resources efficiently within container orchestrationMODULE 7 Reference architectures for data and AI with focus on compliance
Discuss the blueprint for a modern AI/Data platform Secure the AI supply chain with rigorous model provenance and data privacy Monitor model drift and manage the high costs of tokens and GPU usageMODULE 8 The future of platform engineering roles
Transition from infrastructure operator to architect of a digital workforce Measure AI impact through improved velocity and DORA metrics Ensure ethical standards through human-in-the-loop platform designLIVE SESSIONS
Cohort-based sessions with the instructor.
Join live for Q&A, guidance, and accountability. Dates shown here are the next cohort.
Meet your Instructor
Mallory Haigh
Course instructor and Platform Engineering SME
- Full-stack engineer by background (LAMP stack veteran + PHP lifer)
- Also experienced in: Engineering management, customer success, product development
- Platform Engineering SME, course instructor, trainer, and coach
- #horsegirl, farmer, cat+dog mom
|
Desktop
|
Mobile |
 |
|
| Desktop | Mobile |
 |
Alumni stories
| Testimonials | |||||
| Name | Image | Position | Text | LinkedinPost | |
| Jay Moran |  |
SVP of Platform Engineering & Distinguished Engineer at Fiserv | I don’t often feel certifications are too useful, but in this case beyond being not vendor specific, I think this is one certification that really helps define a “Platform Engineer” versus someone who does some of the many components of what goes into platform engineering… | https://www.linkedin.com/in/jaycmoran/ | https://www.linkedin.com/posts/jaycmoran_platformasaproduct-idp-platformengineering-activity-7364777833262448641-ku7Z/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAB7W6ucBwi1gPqF5QCBe36ipfkH_n4Cityo |
| Daniel Palermi |  |
Senior Cloud Engineer at Serko | The Platform Engineering Practitioner certification helped me understand the evolution of DevOps and engineering practices over the years. It clarified the concept of platform engineering and its true purpose. In my opinion, everyone working in an IT company should take this course, as it offers valuable lessons that span across all roles. |
https://www.linkedin.com/in/daniel-palermi-4a5b881b/ | |
| Brittany Lebel |  |
Senior Product Owner, Kinsale Insurance | The Platform Engineering course was a transformative addition to my career. The content was well-structured, covering everything from designing Platform Engineering Maturity Models to developing reference architectures that drive standardization and empower developers with seamless self-service capabilities. The hands-on lectures on Pocket IDP provided an in-depth exploration of the entire implementation process, diving into technical details and real-case scenarios. This comprehensive approach offered invaluable insights into how an IDP functions as a product and how it can efficiently support production workloads.Thanks to this course, I now have the expertise to contribute meaningfully to the development and enhancement of our Internal Developer Platform, enabling us to accelerate application delivery cycles.I highly recommend this course to anyone eager to elevate their engineering expertise and make a tangible impact in platform engineering! | https://www.linkedin.com/in/brittany-lebel/ | |
| Marc Schnitzius |  |
Service Lead Platform Engineering at Codecentric AG | The Platform Engineering Certified Practitioner course is a great guide for better understanding that the success of an internal developer platform is not just about making developers happy and shifting all their problems to a platform team. | https://www.linkedin.com/in/marc-schnitzius/ | |
| Rafael de Araujo Pires |  |
Global Director of Architecture at AB InBev | The Platform Engineering Practitioner certification was more than concepts. It was a reflection on my own platform journey since 2022.The biggest lesson? Platforms are about people. It’s about listening, building trust, and reducing friction so teams can deliver value with autonomy. It’s about connecting culture, product, and technology, and showing that developer satisfaction can be as strategic as any infrastructure investment.Platform engineering isn’t just code: it’s people, trust, and real business impact. | https://www.linkedin.com/in/rafaeldearaujop/ |
| Desktop | Mobile |
 |
|
| Question | Answer |
|
Why this course? |
Unlike other programs, this course blends technical, product, and business frameworks so you can actually build and scale a successful platform initiative, not just understand the tech. |
|
What will I learn? |
You’ll master platform engineering fundamentals: how to design an Internal Developer Platform, build golden paths, and scale adoption across teams, all using proven frameworks from top platform teams. |
|
How is it delivered? |
Live weekly sessions (recorded if you can’t join), self-paced modules, guest lectures, and an active Slack community of 500+ platform engineers. |
|
How much time will it take? |
About 3 hours per week for 5 weeks, including optional homework. All sessions are recorded for flexible learning. |
|
When will the instructor-led live sessions take place? |
The sessions (unless stated otherwise) take place on Tuesdays at 6:30 pm CET/12:30 pm ET. But remember - all recordings are shared, so it’s easy to take the course asynchronously. |
|
Is this course for me? |
It’s for engineers, platform leads, and managers who want to align technical and business goals around platform engineering. No coding required. |
|
I’m not an engineer, will I still benefit? |
Absolutely. The course is designed for both technical and non-technical leaders. You’ll gain a shared framework for platform success across teams. |
|
Do I get a certificate? |
Yes. By doing an exam after the course, you’ll earn a verified digital certificate and LinkedIn badge recognized by leading platform teams. |
|
What if I can’t attend live? |
No problem, every session is recorded and available on demand. |
|
What’s the exam like? |
60 minutes, 50 multiple-choice questions. Passing score: 75%. You’ll have 2 attempts within 6 months of completing the course. |
|
Can I pay by invoice or installments? |
Yes, just contact us to arrange. |
|
Can I buy now and start later? |
Absolutely. Just contact us to arrange and join any future cohort. |
|
Do I need any specific tools or technologies? |
No special setup needed, just a laptop. A basic understanding of DevOps concepts (like Kubernetes or IaC) helps, but isn’t required. |
|
Is coding required? |
No. The course focuses on frameworks, adoption, and product thinking, not hands-on coding. |
|
What technologies are discussed? |
We reference tools like Terraform, Backstage or Kubernetes, but the focus is on best practices for platform design, not on tool-specific tutorials. |
|
Do you offer private training for teams? |
Yes, we run private team cohorts (virtual or in-person) tailored to your platform maturity and goals. Contact us for more information. |
|
Still have questions? |
Contact certifications@platformengineering.orgFor team or group enquiries (training, private cohorts, workshops): Contact advisory@platformengineering.org |
