Best starting path
- Microsoft Learn AI engineer paths are strong for structured, free fundamentals.
- Google Cloud Skills Boost offers beginner and advanced generative AI learning paths.
- Use free short courses first before paying for bootcamps.
AI / GenAI
AI & GenAI certification guide
Start with foundations, then move into prompts, LLM workflows, evaluation and responsible AI. Students should learn useful implementation skills before paying for expensive programs.
Best paid or certification path
- Microsoft Azure AI Engineer Associate is a solid credential for cloud-focused AI roles.
- NVIDIA now offers GenAI certifications at associate and professional levels.
- DeepLearning.AI courses are excellent for skill depth even when they are not exam-first.
Recommended sites
| Site | Why use it | Best for |
|---|---|---|
| Microsoft Learn | Free structured AI learning paths and certification prep. | Beginners to cloud AI learners |
| Google Cloud Skills Boost | Beginner-friendly GenAI path plus advanced tracks for developers. | GenAI foundations |
| DeepLearning.AI | High-quality short courses and deeper AI learning. | Hands-on learners |
| NVIDIA | New GenAI certifications and technical AI training. | Students who want a recognisable AI credential |
| AWS Training | Free digital training and cloud-AI ecosystem familiarity. | Cloud + AI mix |
How to save money
- Start with Microsoft Learn and Google Cloud Skills Boost because many modules are free.
- Watch for official exam offers or event vouchers before paying full exam price.
- Use DeepLearning.AI short courses to validate interest before buying big cohorts.
What to build after learning
- A prompt playground with evaluation notes.
- A small chatbot using a hosted model API.
- A resume project that compares prompts, latency and cost.