What's the time commitment for this bootcamp?

The bootcamp requires 10 hours per week over 6 weeks. This includes live sessions, hands-on projects, and self-paced learning. Most students find this manageable alongside their full-time jobs.

Do I need prior AI experience to join?

No prior AI experience is required, but you should have few years of software development experience. The bootcamp is designed for software engineers who want to upskill in AI engineering.

What if I can't make a live session?

All live sessions are recorded and available for replay. We also offer multiple office hours throughout the week, so you can catch up on any missed content or get help with assignments.

How much should I budget for APIs and resources?

We estimate €10-50 for the entire bootcamp, covering API costs for OpenAI and other services. We'll show you how to optimize costs and use free tiers when possible.

What happens if I can't attend this cohort?

You can defer to the next cohort at no additional cost. We run cohorts every 2-3 months, so you won't have to wait long to join.

How long will I have access to materials after the bootcamp?

You'll have lifetime access to all course materials, recordings, and the private community. This includes future updates and new content we add to the bootcamp.

What's the refund policy?

Yes, you can get a 100% refund if you've progressed less than 10% of the bootcamp or it's within 7 days of your purchase. We're confident in our curriculum and instructor quality, which is why we offer this guarantee.

Do you offer team discounts?

Yes! We offer 20%+ discounts for teams of 3 or more. Contact us at param@learnwithparam.com for team pricing and bulk enrollment options.

Daily Bytes of AI

Bite-sized insights for building production AI systems. Expert guides, real-world patterns, and practical engineering wisdom.

18 AI Bytes

Practical insights for production AI systems

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Daily Bytes of AI

18 AI Bytes

AI Engineering in Practice: Building an AI Bedtime Story Generator

Structured Output: Making LLMs Application-Ready

RAG Evaluation: Proving Your System Actually Works

Advanced RAG with Tools: Using LlamaIndex

Agentic RAG: Building a System That Thinks, Acts, and Corrects

Advanced RAG: Building Self-Correcting Systems

Vector Databases and Embeddings: The Brain of RAG

Splitting Techniques for RAG: The Art of the Right Chunk

Weekly Bytes of AI — Newsletter by Param