How I Mastered Data Structures and Algorithms for ML (In 6 Weeks)

2026-07-15 · Source: Towards Data Science · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Data Science & Analytics · Depth: Intermediate, medium

Summary

The author presents a 6-week strategy for mastering Data Structures and Algorithms (DSA) specifically for machine learning and data science coding interviews, claiming over a 90% pass rate since 2024. This method advocates for a practice-first approach, contrasting with traditional theory-heavy learning. It involves daily problem-solving sessions (30-60 minutes, two problems, 20 minutes each), followed by solution review focused on patterns, and then re-attempting the problem. The strategy emphasizes concentrating on high-return-on-investment topics like Arrays & Hashing, Two Pointers, and Graphs, while deliberately avoiding less frequent topics such as Dynamic Programming. The author suggests practicing a curated set of 40 LeetCode problems, adapted from lists like NeetCode 150, and highlights the importance of external accountability for consistency.

Key takeaway

For Data Scientists and Machine Learning Engineers preparing for coding interviews, adopt a strategic, practice-driven approach to DSA. Instead of extensive theoretical study, prioritize solving problems daily, focusing on high-frequency topics like Arrays & Hashing and Graphs. Utilize curated problem sets, such as the author's recommended 40 LeetCode problems, to maximize your return on time investment. Implement an accountability system to ensure consistent practice over 6 weeks, which is crucial for solidifying understanding and achieving a high interview pass rate.

Key insights

Mastering DSA for ML interviews requires a practice-first, pattern-focused approach on high-ROI topics with consistent accountability.

Principles

• Practice precedes theory for interview prep.
• Focus on high-ROI DSA topics.
• Accountability drives consistent effort.

Method

Spend 30-60 minutes daily on two problems, giving 20 minutes per problem. If stuck, review the solution for patterns, then re-attempt after 5 minutes. Prioritize specific DSA topics.

In practice

• Dedicate 30-60 minutes daily to LeetCode.
• Focus on 9 core DSA topics.
• Find an accountability partner.

Topics

• Data Structures and Algorithms
• Coding Interviews
• Machine Learning Engineering
• Data Science
• LeetCode
• Interview Preparation
• Problem Solving

Best for: Machine Learning Engineer, Data Scientist, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards Data Science.