I Tried 30+ Books and Courses for Machine Learning Interviews: Here Are My Top 9 for 2026

My favorite resources to prepare for Machine Learning Engineer Interviews in 2026

I Tried 30+ Books and Courses for Machine Learning Engineer Interviews: Here Are My Top 9

Hello friends, After spending months testing every major ML interview prep resource — from Udemy to Educative, tryExponent to ByteByteGo — I’ve narrowed it down to the 9 resources that actually work.

Whether you’re a mid-level engineer targeting FAANG or an experienced professional aiming for senior roles, these are the materials that will move the needle on your preparation.

Why ML Interview Prep is Different (and Harder)?

Let’s be honest: ML interviews aren’t like coding interviews. You can’t just leetcode your way through.

Companies like Google, Meta, and Amazon don’t want to hear you recite the definition of a confusion matrix. They want to see you design end-to-end ML systems — the kind that actually ship at scale.

If you’re 3–5+ years in, you’ll get open-ended problems like: “Design a recommendation system for 1M users” or “How would you build a real-time fraud detection pipeline?”

This is where most candidates stumble. Theory gets you past the first round. System design gets you the offer.

If you are getting late, I suggest, go ahead and join ByteByteGo, one of the best platform to prepare for ML System Design interviews. They are also offering 50% discount on their lifetime plan.

System Design · Coding · Behavioral · Machine Learning Interviews

The 9 Best Resources for ML Interview Success

Without any further ado, here are the best online courses you can join to prepare for ML Engineering interviews:

1. Grokking the Machine Learning Interview — Best Overall Course

Platform: Educative.io | Time: 20–25 hours | Cost: $14.99/month (subscription)

Why it works: This course is obsessively practical. Instead of abstract theory, you work through 10+ real ML system design problems inspired by actual FAANG interviews.

The instructor walks you through how to approach an ambiguous problem, ask clarifying questions, and articulate trade-offs — the exact skills interviewers are testing for.

You’ll learn:

Feature engineering at scale
Model selection & evaluation
Data pipeline design
Real-time inference systems
ML monitoring & serving

Best for: Engineers with solid ML fundamentals who need the system design edge.

Note: Requires basic Python and ML knowledge. If you’re intermediate level, start here.

Here is the link to → Start course

Grokking The Machine Learning Interview

By the way, you can either join this course individually or you can take an educative subscription for just $14.9 per month (recommended) to get access to their 1250+ high-quality, AI powered, text-based, interactive courses to learn key skills for coding interviews, software development, and technology.

2. Machine Learning System Design Interview — Best Book

Format: Book | Time: 8–12 hours reading | Cost: ~$40–50

Why it’s essential: This book is the bible for ML system design. It covers everything from ML pipelines and model serving to data storage and real-time inference.

Unlike other books that dive into math, this one focuses on how companies actually build ML systems. Each chapter includes concrete examples from Google, Meta, and other tech giants.

Perfect companion to any course — read a chapter, then apply it in an interview.

Here is the link to → Get the book

Machine Learning System Design Interview

Pro tip: Alternatively, grab a ByteByteGo lifetime membership ($499 with 50% off) to get this book + courses + case studies on Gen AI and ML system design. Better value if you’re doing multi-round interviews.

3. Data Science Interview Course by tryExponent — Best for Mock Interviews

Platform: tryExponent.com | Time: 52 hours | Cost: $14/month (yearly plan recommended)

Why it’s game-changing: This isn’t just videos — it’s the closest thing to real interviews without actually interviewing.

You get:

25+ full mock interview videos (watch top data scientists solve problems)
60+ interactive practice questions (SQL, stats, ML, behavioral)
Interview rubrics (see exactly how you’d be scored)
Expert instructors from Google, Amazon, Meta, and top startups

The mocks alone are worth the price. You’ll see exactly what interviewers are looking for and how to structure your answers.

Best for: People who learn by doing and want real interview simulation.

Here is the link to → Start course

Data Science Interview Prep Course – Exponent

Pricing note: Their yearly plan is $14/month vs. $79/month — go yearly and you get access to System Design + ML courses too.

4. Data Science Career Guide — Interview Preparation — Best Budget Option

Platform: Udemy | Time: 4 hours | Cost: $15–20

Why it’s solid: A bestseller on Udemy for good reason. It covers resume building, interview frameworks, and real practice questions.

It’s concise (4 hours), practical, and includes interviews with actual data scientists sharing their experience.

Requirements: You need DS fundamentals (stats, Python/R, SQL, ML algorithms).

Best for: People with DS background wanting a quick confidence boost before interviews.

Here is the link to join this course — Data Science Career Guide — Interview Preparation

Data Science Career Guide – Interview Preparation

5. SQL for Tech and Data Science Interviews — Best for SQL Prep

Platform: Udemy | Time: 2.5 hours | Cost: $15–20

Why it matters: SQL questions come up in every DS/ML interview. This course is focused specifically on the types of queries you’ll actually see.

The instructor includes:

Real interview questions (curated by someone who’s interviewed at top companies)
A 5-step framework for solving SQL problems under pressure
Mock interviews with explanations

Requirements: Basic SQL knowledge.

Best for: Anyone nervous about SQL interview questions (which is most people).

Here is the link to join this course — SQL for Tech and Data Science Interviews

SQL for Tech and Data Science Interviews

6. Machine Learning for Interviews & Research and DL Basics — Best for Technical Depth

Platform: Udemy | Time: 5 hours | Cost: $15–20

Why it’s valuable: If you need to brush up on ML fundamentals and theory, this course covers 50 lectures on everything — algorithms, deep learning basics, research concepts.

4.3★ rating from 4,000+ students.

Requirements: High school math + basic DS knowledge.

Best for: People who want to understand why algorithms work, not just how to use them. Great complement to system design prep.

Here is the link to → Enroll

Machine Learning for Interviews & Research and DL basics

7. Machine Learning System Design Course — Best for Practical Systems

Platform: Educative.io | Time: 1.5 hours | Cost: $14.99/month (subscription)

Why it works: Shorter than course #1, this is a rapid-fire walkthrough of ML system design best practices based on 100+ industry papers.

Instructor Khang Phem synthesizes cutting-edge practices into actionable interview answers. By the end, you’ll have vocabulary and mental models that impress interviewers.

Rating: 4.6★

Best for: People short on time who want system design fundamentals fast.

Here is the link to join this course → Start course

Machine Learning System Design – AI-Powered Course

8. The Data Science Course 2026: Complete Data Science Bootcamp — Best for Beginners

Platform: Udemy | Time: 29 hours | Cost: $15–20

Why it’s comprehensive: 78,000+ students, 4.6★ rating, 100K+ reviews. If you’re starting from scratch or need a refresher, this covers everything — stats, Python, ML, deep learning.

Requirements: None — designed for complete beginners.

Best for: People transitioning into DS who need foundational knowledge before tackling interview-specific prep.

Here is the link to join this course — The Data Science Course 2026: Complete Data Science Bootcamp

Machine Learning for Interviews & Research and DL basics

9. Generative AI System Design Interview — Best for 2026 Job Market

Format: Book | Time: 8–10 hours | Cost: ~$40–50

Why it’s essential now: AI is exploding. If you’re interviewing in 2026, you will get questions about LLMs, prompt optimization, and retrieval-augmented generation (RAG).

This is the only resource that specifically prepares you for these emerging interview questions. Covers:

Large language model architectures
Image generation systems
Conversational AI design
Real-time inference at scale

Best for: Anyone interviewing at a company that touches LLMs or Gen AI (basically everyone now).

Here is the link to → Get the book

Generative AI System Design Interview

Pro tip: Get it as part of ByteByteGo lifetime membership (50% off = $79) to also get the ML System Design book + case studies.

My Recommendation: A 6-Week Interview Prep Plan

Week 1–2: Foundation

Start with Course #1 (Grokking ML Interview) OR Book #2 if you prefer reading
Parallel: Course #5 (SQL) to knock that out early

Week 3–4: Depth

Course #7 (ML System Design) for 1.5-hour overview
Book #9 (Gen AI System Design) if targeting AI roles

Week 5–6: Practice

Course #3 (tryExponent mocks) — do 2–3 full mock interviews
Udemy #4 (Data Science Career Guide) for final confidence boost

Total time: 40–50 hours over 6 weeks = ~7–8 hours/week (doable while working)

The Bottom Line

These 9 resources represent the consensus best-of across thousands of engineers who’ve cracked FAANG interviews. No single resource covers everything — you need a mix of:

System design theory (Books #2 & #9, Courses #1 & #7)
Practice with feedback (Course #3 mocks)
Technical depth (Courses #4, #5, #6)

Start with your weak spots. If system design scares you, hit course #1. If SQL makes you nervous, start with course #5.

The engineers who succeed aren’t the smartest — they’re the ones who actually practice. So pick your first resource and commit to 2 weeks. That alone will put you ahead of most candidates.

You’ve got this. Now go ace it.

Bonus Resources

P. S. — If you are keen to learn Data science and Machine Learning in-depth then you can also check out this Machine Learning A-Z™: Hands-On Python & R In Data Science course by the SuperDataScience team and Krill Eremenko on Udemy I highly recommend you to join the this course to beginners and experienced developers, and if you like reading books, following two are best.

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