Cracking the Data Science Interview

Table of Contents

1. Exploring the Modern Data Science Landscape
2. Finding a Job in Data Science
3. Programming with Python
4. Visualizing Data and Data Storytelling
5. Querying Databases with SQL
6. Scripting with Shell and Bash Commands in Linux
7. Using Git for Version Control
8. Mining Data with Probability and Statistics
9. Understanding Feature Engineering and Preparing Data for Modeling
10. Mastering Machine Learning Concepts
11. Building Networks with Deep Learning
12. Implementing Machine Learning Solutions with MLOps
13. Mastering the Interview Rounds
14. Negotiating Compensation