Practical AI Skills for Infrastructure Professionals - Even If You Don’t Trust AI
in Production Yet
Build a private AI setup, a searchable knowledge base from your own docs, and automation workflows you can use at work - securely. Hands-on training for Systems Engineers, DevOps, Presales, and Solutions Architects.
Most finish in 2-3 weeks at ~1 hour/day. Self-paced. No deadlines. 14-day satisfaction guarantee.
€149 = less than 3 hours of your professional time. One automated workflow pays for the entire course.
Inside the Course
A Look Inside
45-page RFP → structured compliance report in 15 minutes Module 3
Private ChatGPT clone on your laptop — fully offline Module 4
AI generating infrastructure automation in Cursor Module 6
RAG knowledge base — query your docs, get cited answers Module 5
No-code AI agent built in n8n — fully on your infra Module 9
Professional course structure — 10 modules, 71 lessons Course Platform
Screen recordings with real tools, not slide decks. A few foundational lessons use slides to build context — the rest is hands-on: watch, pause, build alongside in your own environment. 10+ hours of video instruction, 4+ hours of technical reading, and exercises you complete on your own infrastructure.
Course Outcomes
What You’ll Actually Learn
How to turn a 45-page vendor RFP into a structured compliance report in 15 minutes - using the prompt + document conversion workflow you’ll build in Module 3
The specific prompting technique from Module 2 that turns “ChatGPT gives me garbage” into “I got a reliable, usable Ansible playbook in minutes” - and why most engineers never discover it on their own
Set up a private ChatGPT clone on your laptop in under 30 minutes - fully offline, fully under your control.
How the RAG pipeline you’ll build in Module 5 turns your scattered runbooks, wikis, and PDFs into a searchable AI knowledge base - one that cites its sources instead of guessing
Drop a screenshot of an error - wrong language, purple screen, cryptic log - into AI and get the diagnosis, the likely cause, and the fix. In seconds, not hours. That’s Module 3.
2 ways to build AI agents that run fully offline on your infrastructure - one uses Python, the other requires zero code (you’ll master both)
The Transformation
Before & After This Course
Before:
- Drowning in tickets, holding systems together with glue and tape
- Continuous context switching due to urgent requests
- Feeling like you’re falling behind while everyone else talks about AI
- Nodding along in meetings when AI comes up, hoping nobody asks a follow-up
- Knowing AI could help, but no time or structure to learn it
- Spending more time on repetitive work than on actual engineering
After:
- Find answers buried in your runbooks in seconds - not hours of manual searching
- Finish RFP responses and technical proposals in minutes instead of days
- Generate documentation and presentations while you focus on real engineering
- Automate the repetitive work that eats your evenings and weekends
- Walk into any AI conversation with confidence - because you’ve actually built things with it
- Become the person your team turns to when they need help with AI
Why This Course
What Makes This Course Different
Built for your reality, not generic AI hype.
Every lesson, example, and exercise is framed for Systems Engineers, DevOps, Presales, and Solutions Architects. No “write a poem” demos. You work with runbooks, RFPs, infrastructure automation, and vendor documentation.
Private, offline, security-first.
You’ll deploy a private AI environment and build agents that run entirely on your infrastructure. No GPU clusters. No cloud dependencies. No data leaving your network. Works on Windows, macOS, or Linux.
Battle-tested prompts and tools you won’t find elsewhere.
Tools to convert virtually any document format to clean Markdown - locally and securely. Plus optimized prompts refined through real use: automated RFP analysis in 15 minutes, presentation generation from research notes, and more.
Realistic about limitations.
You’ll learn when AI is the wrong answer - when it hallucinates, when simpler automation beats agents. This isn’t cheerleading; it’s engineering.
Structured path from a 20-year enterprise veteran.
A structured curriculum from a credible trainer with 20+ years in enterprise IT. Each module builds on the last. Hands-on from Day 1 - you build real tools you’ll actually use, not just memorize facts to forget in a month.
Pay once, keep forever.
No subscriptions, no expiring access. Come back when you have time. Your course stays yours.
Curriculum
The Full Curriculum
10 modules. 60+ lessons. 10+ hours of video instruction. 4+ hours of technical reading.
How LLMs actually work under the hood, why tokens matter for cost and context limits, and why hallucinations happen (and how to design around them). No PhD required.
- The Transformer architecture and why “next token prediction” explains most LLM behavior
- Tokens, tokenization, and why your API bills depend on understanding them
- Parameter memory vs. context window
- Hallucinations: not bugs, but features you must design around
- Multimodal capabilities
Set up your Python environment, run OpenAI Whisper locally for offline transcription, experiment with tokenization, and generate/edit images with text prompts.
How to turn vague ChatGPT outputs into reliable, repeatable results. Prompts aren’t magic words - they’re structured instructions.
- The 6-component effective prompt anatomy
- Zero-shot, few-shot, chain-of-thought, tree-of-thoughts, and prompt chaining
- Using Anthropic’s Prompt Improver and OpenAI’s Playground to refine prompts
- Converting virtually ANY document to clean Markdown - locally and securely
- Security and data hygiene
Build your personal library of “golden prompts” for tasks you repeat. Convert vendor documents to LLM-friendly format. Create presentations using a structured AI workflow.
How to use AI as a research assistant that synthesizes information from multiple sources, cites its work, and saves you hours of manual searching.
- ChatGPT Deep Research vs. Perplexity vs. Gemini: strengths, speed, and accuracy tradeoffs
- NotebookLM for building personal knowledge bases
- Automating RFP first-pass analysis with AI
- Troubleshooting faster with multimodal AI: screenshot → diagnosis → fix
- Generating customized, environment-specific documentation on demand
Run a competitive analysis with Deep Research. Build a study notebook for a certification. Analyze an RFP and generate a compliance report. Troubleshoot real errors using screenshots.
How to run AI completely offline on your own infrastructure - no data leaving your network, no expensive hardware required.
- Private AI vs. Sovereign AI: what you actually need
- Ollama: installation, CLI usage, model management, API endpoints
- GPU memory, quantization, and model sizing for your hardware
- Open WebUI: deploying your own ChatGPT-style interface
- Connecting local and cloud models in a single unified UI
A private, self-hosted AI environment you control completely.
How Retrieval-Augmented Generation works end-to-end - from document ingestion to vector storage to grounded answer generation. The highest-impact skill for making AI useful with your internal documentation.
- Why RAG beats fine-tuning for knowledge-heavy enterprise use cases
- Chunking strategies and why they matter more than model choice
- Embeddings, vector databases, and PostgreSQL + pgvector
- Hybrid search (semantic + keyword), reranking, and metadata filtering
- RAG-specific prompting
Open WebUI track: Configure RAG with your own documents. n8n track: Build a complete RAG pipeline from scratch.
You will buildA private, searchable knowledge base from your own runbooks, wikis, and documentation.
How to use AI-powered IDE and CLI-based code agents to write automation faster - without becoming a software developer.
- Cursor (agentic IDE): Agent mode, Ask mode, Plan mode, file referencing
- Claude Code (agentic CLI): terminal-first workflow, project context
- “Vibe coding” vs. spec-driven development: when each approach works
- Translating automation between frameworks (Ansible ↔ Terraform)
- Secrets management: .env files, .gitignore, OpenRouter for API safety
Real automation scripts, playbooks, and documentation - faster than you thought possible.
MCP is the emerging standard for connecting AI to external tools and systems. Think of it as “USB-C for AI integrations” - one protocol, any tool, any model.
- MCP architecture: Hosts, Clients, Servers, Tools, Resources, Prompts
- The M×N integration problem and how MCP solves it
- Security considerations
- Connecting MCP servers to code agents
Connect to a PostgreSQL database via MCP and query it with natural language. Manage Docker containers through AI-driven commands.
What AI agents actually are (model + tools + instructions in a loop), when to use them vs. simpler workflows, and how to build them in Python without heavy software engineering.
- The agent loop: observe → decide → act → repeat
- Agent memory and design patterns
- When agents make sense vs. deterministic workflows
- The Agno framework: lightweight, well-documented, LLM-optimized
Working Python agents for research, content analysis, and knowledge retrieval - capable of running fully offline with local models.
How to build AI agents without writing code using n8n - a self-hostable, low-code automation platform. Security-first pattern for agents that take real action on your systems.
- n8n fundamentals
- Safe agent design: explicitly scoped tools instead of unrestricted access
- Building an SE Support Agent that diagnoses systems and restarts services
- Hybrid workflows: deterministic logic + AI reasoning where it adds value
A practical, secure support agent running entirely on your own infrastructure.
How to keep growing after the course ends. Which certifications matter, which trends to follow (and which to ignore), and how to build a visible portfolio of your AI capabilities.
- AI certifications for SE/Presales/Solution Architect
- Emerging trends that matter
- Staying current without burning out
Build your personal AI learning roadmap and turn your LinkedIn profile into a professional website - using a coding agent - that positions you for Architect and Lead roles.
Every lesson uses real infrastructure scenarios - runbooks, automation, RFPs, troubleshooting - framed for Systems Engineers, DevOps, Presales, and Solutions Architects.
Free Preview
Want to See the Course Quality Before You Buy?
Watch a free lesson from Module 2 — Converting Virtually Any Document for Use with LLMs:
Who Is This For
Built Specifically for These Roles
This course is for you if:
- You want practical AI skills you can apply to your actual job - not academic theory
- You’re tired of feeling behind while everyone else talks about AI
- You want to learn fast - no fluff, no padding, just what you need to get results
- You need vendor-neutral techniques that work across hybrid environments
- You value structured learning over another “figure it out yourself” YouTube playlist
This course is NOT for you if:
- You’re a software developer looking for deep ML/model training content - this is about applying AI, not building models from scratch
- You’re looking to become a data scientist - this focuses on IT operations workflows
- You aren’t willing to invest at least an hour a day for a few weeks
Specifically helpful if you:
- Need to automate repetitive work but never have time to set it up
- Want to answer client questions about AI confidently (Presales/Solutions roles)
- Are building an AI strategy or roadmap for your team (Architects/Leads)
- Want to upskill your team - skills from this course scale across your organization
- Work in regulated environments where data privacy matters
“Don’t let the AI for Systems Engineers title fool you. While the content is tailored for systems engineers, the framework it provides is incredibly valuable for anyone working in a technical cross-functional role, including Program Managers like me. It helps you ‘speak the language’ and future-proof essential skills for anyone trying to stay relevant as AI transforms our day-to-day jobs.”
Rohit T. - Program and Portfolio Management, Dell Technologies
Prerequisites
What You Need (and What You Don’t)
What you need:
- A laptop or desktop computer (Windows, macOS, or Linux)
- Basic familiarity with command line / terminal
- Some scripting experience (Python, PowerShell, Bash - any of these is fine)
- Ability to install software (Docker, Python, VS Code, Cursor)
- Willingness to invest 1 -2 hours per day
What you DON’T need:
- Prior AI/ML experience (we start from foundations)
- A powerful GPU (you will benefit even with just CPU)
- Deep programming skills (you’re using AI as a tool, not building ML models)
- A cloud infrastructure subscription
What Engineers Are Saying
Hear From Your Peers
This is exactly the type of course I was looking for so that I could rapidly learn new skills and capabilities for the age of AI. It will make great SEs superhuman, and junior SEs will ramp faster in their skills and knowledge. This course gets it right - it is the accelerator for scale and efficiency that separates good from great technologists in the age of AI.
Bill L.
Director of Technical Marketing Engineering, Cloud Platforms & HCI
I’ve taken many technical training courses over the years, but AI For Systems Engineers genuinely stands out. What makes this course special is how relentlessly practical it is. Every module is packed with concrete skills, ideas, tips, and tricks that I could put to use immediately. I’m already using what I’ve learned to build and refine an AI-first workflow that has made me noticeably more productive and effective.
Michael L.
Staff Technical Marketing Engineer, Infoblox
Even with at most one hour of time and mental energy to focus on it at any given night, I am still getting value. The course content is broken up into digestible chunks that caters well to my schedule. Though I am still working my way through the course, I’ve already started applying some of the knowledge, especially prompt engineering, in my day-to-day activities including at work.
Daniel C.
Senior Technical Marketing Manager, Dell Technologies
I would highly recommend this course to any IT industry presales professional looking to gain tangible and practical knowledge about AI. Hands-on lab learning opportunities are typically only available via in-person live workshops that cost much more - making the value and flexibility of this course unmatched.
Jason M.
Experienced IT Industry Professional, Nutanix
With the explosive growth of AI tools, it can be overwhelming to figure out where to begin. If you take only one AI course this year, make it this one. It strikes the perfect balance between concise, clear explanations and practical, hands-on exercises. This course truly opened my eyes to what’s possible with AI.
David G.
Seasoned Technical Marketer and Product Manager
The scope is perfectly tailored for systems engineers / presales / platform architects like myself. It lets you grasp the key ideas and concepts behind building AI solutions in a pretty straightforward way - without going deep into purely developer or programming topics. The hands-on exercises are absolutely essential. Highly recommended!
Paweł A.
Advisory Systems Engineer and Presales, Dell Technologies
Pricing
€149 - One-Time Payment. Lifetime Access.
The complete course - all 10 modules, full curriculum.
One-time payment · Lifetime access
- All 10 modules (60+ lessons)
- 10+ hours of hands-on video instruction
- 4+ hours of deep-dive technical reading
- Hands-on exercises across all 10 modules
- Private engineer community on the course platform
- Battle-tested prompt library
- Document conversion toolkit
- 12 months of guaranteed updates
(last updated: February 2026) - Course GitHub repository with all code
Secure payment via Stripe. Invoice provided for company reimbursement.
Launch pricing - available until March 31, 2026. Price increases when new modules drop.
| Alternative | Price | What’s Missing |
|---|---|---|
| Generic beginner AI courses | ~$49/mo subscription | No infrastructure content, too high-level |
| Developer-focused AI training | $0 -500+ | Heavy math, Python-centric, irrelevant to sysadmin work |
| DevOps-specific learning platforms | $29 -45/mo subscription | Fragmented short courses, ongoing cost |
| Vendor certification exams | $165+ per exam | Too basic, vendor-locked, no practical application |
| Premium academic programs | $2,500 -4,500 | Prohibitively expensive, too academic |
| This course | €149 one-time | Built for infrastructure roles. Hands-on. Lifetime access. |
€149 is less than 3 hours of your professional time. One-time payment. Lifetime access. Pays for itself if it saves you just 2 hours/week for 2 weeks.
Instructor
Karol Boguniewicz
Senior Principal Engineering Technologist · 20+ years in enterprise IT: Dell Technologies, EMC, GSK
Connect with me on LinkedInI’ve led a global team to win Dell’s internal AI Hackathon. I’ve spent over 15 years delivering workshops for enterprise IT teams worldwide. And I built this course because I know the grind - virtualization projects, cloud migrations, documentation nobody reads, endless firefighting.
I’m not a data scientist who learned about IT from a textbook. I’m a systems engineer who spent two decades in the trenches and then figured out how to make AI actually useful for work like ours.
Karol is an extraordinary technical educator, subject matter expert and above all, a masterful storyteller. After each session Karol delivered, we received 100% positive feedback - an incredible testament to his dedication, and relentless drive to deliver best in class learning experiences.Anita V. - Senior Manager, Client Learning at Visa
What stands out most about Karol is his professional passion for AI and emerging technologies. He’s endlessly curious, deeply knowledgeable, and always willing to share insights with a practical, business-focused lens.Linka B. - Global Product Marketing at Dell Technologies
I’ve been particularly impressed by Karol’s knowledge into Large Language Models, including RAG techniques and model customization. He is a remarkably quick learner, able to absorb and apply new information rapidly, and a genuine forward-thinker, often anticipating future trends and their implications.Benedikt M. - Sr Solutions Architect at NVIDIA
14-Day Satisfaction Guarantee
If you haven’t automated at least one recurring task by the end of the first 14 days, email me for a full refund. No hassle. No questions asked.
You have nothing to lose - except the hours you’re currently spending on work that should be automated.
01
Instant access
After payment, you receive login credentials - no waiting, no approval.
02
Start immediately
Log in and follow the 10-day roadmap from Day 1. Module 1 setup takes ~30 minutes.
03
Join the community
Introduce yourself, ask questions, connect with other engineers.
04
Go at your own pace
Lifetime access - come back whenever you want. No deadlines, no pressure.
FAQ
Frequently Asked Questions
“Even with at most one hour of time and mental energy to focus on it at any given night, I am still getting value.” - Daniel C., Senior Technical Marketing Manager
“Knowing Karol, I’m sure the course content will keep ‘living’ and evolving over time.” - Paweł A., Advisory SE and Presales
“Hands-on lab learning opportunities are typically only available via in-person live workshops that cost much more - making the value and flexibility of this course unmatched.” - Jason M., IT Industry Presales Professional, Nutanix
Ready?
Ready to Stop Drowning and Start Building?
- Hours lost to repetitive toil that AI could handle
- Peers pulling ahead while you’re still figuring out where to start
- Opportunities to position yourself as the AI expert slipping away
You’ve survived every technology wave so far - virtualization, cloud, containers, Kubernetes. You adapted. You learned. You stayed relevant.
AI is the next wave. And it’s moving faster than the rest.
10 modules. 60+ lessons. Hands-on from Day 1.
Get structured, practical AI skills built specifically for Systems Engineers - for less than 3 hours of your professional time.
“If you take only one AI course this year, make it this one.” - David G.
Enroll in Practical AI for Systems Engineers - €149€149 · One-time payment · Lifetime access · 14-day guarantee
P.S. - Remember: you get a 14-day satisfaction guarantee. If you haven’t automated at least one recurring task, you get a full refund. No questions asked. The only risk is staying where you are. €149. Lifetime access. Start today.