Ohara Courses

Learn AI from the ground up — from understanding how LLMs work to designing production-ready agent architectures. Each course is bilingual (English + German), self-paced, and includes hands-on exercises.

Recommended Learning Path

beginner AI Fundamentals → beginner Prompt Engineering → intermediate AI-Assisted Development → intermediate AI Tool Selection & Management → advanced Advanced AI Integrations → architect Agentic AI Architecture

AI Fundamentals

Foundations

beginner 2-3 hours

From the Dartmouth Conference to GPT-5 — understand the 70-year journey of AI, how LLMs work under the hood, and why 2022 changed everything.

The History of AIThe AI Landscape 2026How LLMs Actually WorkTokens, Context & Cost +1 more

Prompt Engineering

Foundations

beginner 1-2 hours

Master the art of communicating with AI — from basic prompts to advanced techniques like chain-of-thought, few-shot learning, and system prompt design.

Prompt BasicsAdvanced TechniquesSystem Prompt DesignPitfalls & Best Practices +1 more

AI-Assisted Development

Development

intermediate 4-6 hours

Master AI coding tools: from Copilot to agentic development. Learn vibe coding vs. spec-driven approaches, AGENTS.md, and build 3 projects hands-on.

AI Coding Tool LandscapeVibe Coding vs. Spec-DrivenEnvironment SetupHands-On: Build 2048 +3 more

AI Tool Selection & Management

Management

intermediate 2 hours

Navigate the AI tool landscape: compare providers, manage costs, set up routing, and choose the right model for each task. Learn when to self-host vs. use cloud.

The Provider LandscapeModel Selection by TaskCost Management & BudgetingIntelligent Model Routing +1 more

Advanced AI Integrations

Engineering

advanced 2-3 hours

Build MCP servers, sub-agent systems, custom commands, and remote-controlled AI agents. Deep dive into production AI tooling.

Build Your Own MCP ServerSub-Agent SystemsCustom Commands & SkillsRemote Agent Control +1 more

Agentic AI Architecture

Architecture

architect 2-3 hours

Design production-ready AI agent systems: layer models, deployment patterns, 11 real-world use cases, and the interactive architecture builder.

What is Agentic AI?Layer Models Comparison11 Real-World Use Cases3 Paths to the Goal +1 more

6

Courses

32

Sections

2

Languages

11+

Hands-On Exercises