Learning Path
30-Day Agentic AI Interview Prep Path
Learn Agentic AI Step by Step
Follow a 30-day Agentic AI interview prep path with short lessons, coding problems, mini projects, and hands-on practice for AI engineering roles.
Curriculum
4 phases · 30 days · ~45 min / day
Free vs Pro access
| Feature | Free | Pro |
|---|---|---|
| Days 1–7 articles | ||
| Days 1–7 problems | ||
| Progress tracking | ||
| Days 8–30 articles | Preview | |
| Days 8–30 problems | — | |
| Mini projects | — | |
| Capstone project | — | |
| Full completion | — |
30
Total days
30
Lessons
30
Practice problems
7
Free days
Frequently asked questions
Do I need prior AI experience to start this path?+
This path is designed for beginners to intermediate learners. You should have basic Python knowledge, but no prior AI agent experience is required. The first phase covers foundational concepts.
How long does each day take?+
Each day is designed to take about 45 minutes total. The article takes about 10–12 minutes to read, and the practice problem takes about 30–35 minutes to solve. You can go at your own pace.
What is included in the free version?+
The first 7 days are completely free. You get full articles, linked practice problems, and progress tracking. Days 8–30 are part of the Pro path with advanced topics, mini projects, and a capstone project.
How is this different from the Curriculum section?+
The Curriculum section provides in-depth concept articles. The Learning Path is a structured daily program that combines short lessons with immediate practice. The path tells you what to do each day; the curriculum is a reference library.
Can I skip days or go out of order?+
The path is designed to be followed in order since each day builds on previous concepts. However, you can access any day page directly. Progress tracking works best when following the sequence.
What happens after I complete all 30 days?+
After completing the full path, you will have built multiple agent projects, solved 30 practice problems, and gained interview-ready knowledge covering agent loops, tools, RAG, memory, evals, guardrails, and system design.