The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.
Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview.
By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.

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Spis treści

Cracking the Data Science Interview. Unlock insider tips from industry experts to master the data science field eBook -- spis treści

• 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