4.5
Beginner
10h
Updated 2 weeks 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.
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
Show more
TAKEAWAY SKILLS
Learning Roadmap
2.
Handling Diverse Real-World Data
Handling Diverse Real-World Data
Explore data types, processing techniques, and collection methods essential for data science.
3.
Preparing and Transforming Data for Machine Learning Pipelines
Preparing and Transforming Data for Machine Learning Pipelines
5 Lessons
5 Lessons
Master essential data cleaning, transformation, and feature engineering techniques for effective machine learning.
4.
Understanding Supervised Learning Algorithms
Understanding Supervised Learning Algorithms
8 Lessons
8 Lessons
Explore supervised learning techniques, model evaluation, and real-world applications in data science.
5.
Understanding Unsupervised Learning Algorithms
Understanding Unsupervised Learning Algorithms
5 Lessons
5 Lessons
Explore unsupervised learning techniques to find patterns in unlabeled data.
6.
Advanced Machine Learning Concepts
Advanced Machine Learning Concepts
5 Lessons
5 Lessons
Master essential techniques for model optimization and evaluation in machine learning.
7.
ML Applications and Deployment in the Real World
ML Applications and Deployment in the Real World
6 Lessons
6 Lessons
Explore machine learning applications across health care, finance, retail, and autonomous vehicles, focusing on model deployment and monitoring.
8.
Responsible Machine Learning: Ethics, Fairness, and Privacy
Responsible Machine Learning: Ethics, Fairness, and Privacy
4 Lessons
4 Lessons
Explore fairness, bias, and ethics in machine learning.
9.
ML Interview Preparation and Case Studies
ML Interview Preparation and Case Studies
5 Lessons
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.
Complete more lessons to unlock your certificate
Course Author:
Developed by MAANG Engineers
Trusted by 2.9 million developers working at companies
"These are high-quality courses. Trust me the price is worth it for the content quality. Educative came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"
Anthony Walker
@_webarchitect_
"Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!"
Evan Dunbar
ML Engineer
"You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it."
Software Developer
Carlos Matias La Borde
"I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site"
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.
AI Prompt
Code Feedback
Explain with AI
AI Code Mentor
Free Resources
