Master Product Data Analytics
Master Product Data Analytics:Acing Meta's Analytical Interview
V. Resources and Practice (Continuous Learning)
Here are some additional resources to help you continue your preparation and stay up-to-date on the latest trends in data science:
1. SQL Practice Platforms
2. Python/R Resources
- Official Documentation:
- Online Courses:
- Books:
- "Python for Data Analysis" by Wes McKinney
- "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
- "R for Data Science" by Hadley Wickham and Garrett Grolemund
3. Statistical Learning Resources
- "An Introduction to Statistical Learning" (free online version available)
- Khan Academy Statistics and Probability
- OpenIntro Statistics (free online textbook)
4. Product Sense Development
- Blogs:
- Stratechery (by Ben Thompson)
- Lenny's Newsletter (by Lenny Rachitsky)
- Reforge Blog
- Silicon Valley Product Group (SVPG)
- Books:
- "Inspired: How to Create Products Customers Love" by Marty Cagan
- "Hooked: How to Build Habit-Forming Products" by Nir Eyal
- "The Lean Startup" by Eric Ries
- "Measure What Matters" by John Doerr
- "Crossing the Chasm" by Geoffrey A. Moore
5. Mock Interview Platforms
6. Community Forums and Groups
- Reddit:
- Discord servers:
- Search for "data science" or "programming" related servers.
- Slack channels:
- Look for data science or analytics-focused Slack communities.
- Facebook Groups:
- Search for groups related to "data science interview prep", "Meta data science", etc.
7. A/B Testing and Experimentation
- "Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing" by Ron Kohavi, Diane Tang, and Ya Xu
- Udacity A/B Testing Course (by Google)
- Optimizely: A/B Testing Resources
- VWO: A/B Testing Resources
8. Business Analytics and Case Studies
- Harvard Business Review (Analytics)
- MIT Sloan Management Review (Data & Analytics)
- Kaggle Datasets (for practice)
- Maven Analytics Data Playground (for practice)