HomeCoursesData Science and Machine Learning Interview Handbook

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Updated 2 months ago

Data Science and Machine Learning Interview Handbook

This hands-on course prepares you for ML and data science interviews through real-world data handling, core algorithms, deployment strategies, and ethical, production-ready AI practices.

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Overview

Content

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This course equips you with practical skills to ace data science and machine learning interviews. You’ll begin with real-world datasets, including structured, unstructured, time series, text, and images, and learn key techniques for collecting and querying data using APIs, SQL, and web scraping. Next, you’ll cover data preprocessing workflows: cleaning, normalization, handling missing data, feature engineering, and managing outliers. You’ll then apply supervised learning methods like regression, decision trees, SVM, Naive Bayes, and unsupervised techniques such as k-means, hierarchical clustering, and PCA. The course also covers advanced topics, including ensemble methods, regularization, hyperparameter tuning, and the fundamentals of deep learning. You’ll explore real-world applications in health care, finance, and autonomous systems. Finally, you’ll practice with case studies, model deployment strategies, fairness and privacy in AI, and mock interview practice to make you industry-ready.

This course equips you with practical skills to ace data science and machine learning interviews. You’ll begin with real-world d...Show More

WHAT YOU'LL LEARN

An understanding of how to clean, transform, and prepare structured, unstructured, time series, and image data, mirroring the messy datasets used in interviews

Working knowledge of building and evaluating supervised and unsupervised models, including regression, classification, clustering, and dimensionality reduction techniques

Hands-on experience applying cross-validation, regularization techniques (Lasso, Ridge), hyperparameter tuning, and ensemble methods to boost model performance under interview pressure

The ability to understand and navigate the deployment life cycle to demonstrate job-ready, industry-relevant ML skills

Familiarity with fairness, bias mitigation, and data privacy considerations in machine learning

An understanding of how to clean, transform, and prepare structured, unstructured, time series, and image data, mirroring the messy datasets used in interviews

TAKEAWAY SKILLS

Machine Learning Fundamentals

Machine Learning

Data Science

Data Analysis

Python

Content

46 Lessons14 Challenges

Getting Started

1 Lessons

Prepare for machine learning and data science interviews with hands-on challenges and real-world scenario-based learning.

About This Course

Handling Diverse Real-World Data

7 Lessons

Explore data types, processing techniques, and collection methods essential for data science.

Structured vs. Unstructured Data

Time Series Data

Handling Text Data

Handling Image Data

Real-World Data Collection Methods

Data APIs and Web Scraping

SQL Query Challenges

Preparing and Transforming Data for Machine Learning Pipelines

5 Lessons

Master essential data cleaning, transformation, and feature engineering techniques for effective machine learning.

Understanding Supervised Learning Algorithms

8 Lessons

Explore supervised learning techniques, model evaluation, and real-world applications in data science.

Understanding Unsupervised Learning Algorithms

5 Lessons

Explore unsupervised learning techniques to find patterns in unlabeled data.

Advanced Machine Learning Concepts

5 Lessons

Master essential techniques for model optimization and evaluation in machine learning.

ML Applications and Deployment in the Real World

6 Lessons

Explore machine learning applications across health care, finance, retail, and autonomous vehicles, focusing on model deployment and monitoring.

Responsible Machine Learning: Ethics, Fairness, and Privacy

4 Lessons

Explore fairness, bias, and ethics in machine learning.

ML Interview Preparation and Case Studies

5 Lessons

Master machine learning pipeline design, case studies, and interview preparation strategies.

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Ria Cheruvu

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Carlos Matias La Borde

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Souvik Kundu

Front-end Developer

"Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content."

Vinay Krishnaiah

Software Developer

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Free Resources

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