ML Concepts Questions for Data Scientists
Learn best practices for answering ML concepts questions. Particularly important for data science candidates applying for roles in machine learning and algorithms.
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1,000+ students
Updated Sep 2026
Interview prep trusted by 1M+ candidates who've landed jobs at
What you'll find in this course
29 lessons
8 videos
7 hours
ML Concepts Questions for Data Scientists
3 modules
29 lessons
8 videos
Describe Linear Regression
Explain the Bias-Variance Tradeoff
Explain “Training" and “Testing” Data
Discuss Batch, Mini-Batch, Stochastic Gradient Descent
Explain Feature Scaling and Normalization
Explain Classification vs Regression
Identify When Model Needs Refresh
Handle an Exploding Gradient
Build Fraud Detection Model
Describe How Decision Trees are Created
Measure Algorithm Success
Compare Forecast Models to Other ML Models
Build Recommendation System for Online Courses
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