Hi, I'm Bartosz – Data-Intensive AI Specialist. I love helping companies build AI-based Big Data applications and analytics pipelines.
Stop explaining why your AI initiatives fail in production. Start building solutions that work when it matters.
Are you tired of AI systems that look impressive in demos but fall apart in production? Of being woken up by alerts at 3 AM when your AI behaves unexpectedly? Of explaining to executives why that promising AI project still isn't delivering business value?
I help engineering leaders and their teams transform AI prototypes into reliable, production-grade systems through comprehensive MLOps practices that most AI training ignores. This isn't about building quick demos—it's about creating AI solutions your entire organization can trust.
Most AI training teaches you to build proof-of-concept systems that look good in demos but crumble under real-world conditions. They treat AI as "just another API" rather than the complex ML systems they truly are.
This 2-day hands-on workshop focuses on what others ignore: rigorous testing, evaluation frameworks, and reliability practices that ensure your AI works in production, not just in presentations.
Before: Explaining repeated AI failures to skeptical executives
After: Showcasing reliable AI systems that consistently meet business expectations
Before: Constant firefighting and late-night alerts for unpredictable AI behavior
After: Systematic evaluation and monitoring that prevents problems before they reach production
Before: Endless development cycles with no production deployment
After: Clear implementation pathways with measurable success metrics aligned to business outcomes
I bring 5 years of MLOps experience and 4 years working on data engineering teams to this workshop. With 14 years of total programming experience and 5 years teaching programming workshops, I understand both the technical challenges and how to effectively transfer these skills to your team.
Unlike theoretical AI courses, this workshop is intensely practical. Your team will work in small groups on hands-on exercises that mirror real-world implementation challenges. They'll build evaluation frameworks, testing methodologies, and monitoring systems they can immediately apply to your organization's AI initiatives.
I've helped 953 programmers transform their careers through hands-on AI and ML workshops. Don't take my word for it—here's what they say:
I'm extremely impressed with Bartosz's expertise and experience. We covered all assignments, addressing various details, scenarios, and potential errors. Every question we asked was answered thoroughly. The workshop format of the sessions and small group activities were particularly enjoyable. We had opportunities to apply our new knowledge practically. The trainer remained accessible whenever questions arose. If any uncertainties emerged, the facilitator explained everything with patience.
The training was exceptional because it successfully integrated theory with practical application, which enhanced the learning process. For example, the exercises allowed us to immediately implement what we had learned, and the real project examples were incredibly useful. Furthermore, the trainer were outstanding at addressing our questions and explaining challenging topics, which made the training truly meaningful.
I greatly appreciate the standard of classes taught by Bartosz Mikulski. Wonderfully taught lessons with an extensive amount of information. The examples serve as a solid groundwork for practical implementations.
The most engaging classes, concentrating on individual (+ group-based at the end) task implementation.
Everything was conducted excellently. A considerable amount of knowledge but presented gradually so that it was clear what led to what.
One of the most content-rich lessons I've experienced, may there be more such classes.
This 2-day online workshop is limited to 20 participants to ensure personalized attention and maximum learning effectiveness. Each session includes:
Don't waste another quarter explaining AI failures or rebuilding the same system repeatedly. Equip your team with the skills to build AI that works in production, not just in demos.
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