Course Roadmap

In this part of the course, we’re given a roadmap that outlines the full journey of preparing for machine learning interviews. Each section is designed to build our skills systematically and strategically, based on real-world experience and mentorship insights.

• We start with essential ML concepts, learning how to clearly explain high-frequency topics that appear in nearly every interview.
• We then move into practical ML coding and modeling, covering notebooks, EDA, model selection, feature engineering, and evaluation techniques.
• Coding foundations are reinforced to help us succeed in general algorithm rounds, with a focus on what companies expect from ML candidates.
• We’ll tackle ML algorithm coding, where we may be asked to implement algorithms like decision trees or k-means from scratch.
• ML system design is emphasized for senior-level roles, with frameworks and examples for building scalable systems.
• Finally, we prepare for project deep dives and behavioral interviews, learning how to share impactful stories, followed by crafting a personalized study plan that fits our timeline and goals.

If you want to learn even more from Yayun:

• Book 1 on 1 career guidance with her here: https://calendly.com/your-friend-yayun/1on1
• Follow her on LinkedIn: https://www.linkedin.com/in/yayunjin/