Starting your AI engineering career as a new graduate is one of the most exciting paths you can take in tech today. This comprehensive roadmap is designed for recent graduates from any major, computer science, engineering, mathematics, physics, or even non-technical fields, who want to break into AI engineering. The key advantage you have as a new grad is a clean slate: no legacy habits to unlearn, fresh perspective on emerging technologies, and the energy to immerse yourself completely in learning. The challenge is standing out in a competitive market without professional experience. This path addresses that head-on by focusing on portfolio projects that demonstrate real AI engineering skills, not just coursework. You'll build working applications that solve actual problems, giving you concrete examples to discuss in interviews. We start with programming fundamentals and Python mastery, then progress through data structures and algorithms essential for technical interviews. From there, you'll dive into machine learning concepts and modern AI tools like LLMs and RAG systems. The final milestones focus heavily on building an impressive portfolio and mastering the job search process. Employers hiring junior AI engineers care most about demonstrated learning ability, genuine enthusiasm for AI, and evidence you can build things that work. This 6-12 month timeline accounts for the learning curve of building foundational skills while still being aggressive enough to capitalize on the current AI job market demand.
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build