Real Data Science Interviews Faang Companies And Startups

Data Science Interview Mastery: Prepare with Real Questions From Top Companies and Startups

What you'll learn

Work with real Data Science Interview Questions, not made up ones.

See the different types of interview questions that can be asked.

Full Python, SQL, and Machine Learning Review/Preparation for interviews

Understand the interview process and data science job descriptions.

Requirements

No experience necessary, but Python, SQL, and statistics are soft prerequisites.

Description

Breaking into the field of data science requires a strong grasp of technical skills and a strategic approach to the interview process. This course is designed to equip aspiring data scientists with the knowledge and practice needed to succeed in job interviews across various industries, including Big Tech, fintech, Food and Delivery, and more. Through a combination of real-world interview questions, hands-on coding exercises, and case studies, students will develop expertise in Python, SQL, machine learning, and data analysis. The course covers different types of interviews, such as take-home assignments, live coding challenges, and system design. Students will gain insights into data science hiring trends, organizational roles, and the expectations of employers at different experience levels.Key topics include data preprocessing, exploratory data analysis, feature engineering, model evaluation, and machine learning algorithms commonly tested in interviews. Students will also learn how to prepare for recruiter screenings, and effectively communicate technical concepts during interviews. The course also provides strategies for tackling time-constrained coding challenges and problem-solving assessments.By the end of this course, students will have the confidence and skills necessary to tackle technical interviews, showcase their problem-solving abilities, and secure data science roles in a competitive job market. Additionally, students will understand industry-specific nuances and best practices for structuring data-driven solutions during interviews.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 General Data Science Overview

Section 2: Python Tutorial

Lecture 3 Python Review Part I

Lecture 4 Python Review Part II

Section 3: SQL Tutorials

Lecture 5 SQL Review

Section 4: Machine Learning Tutorial

Lecture 6 Machine Learning Review Part I

Lecture 7 Machine Learning Review Part II

Section 5: The Actual Interviews

Lecture 8 Fintech SQL Question

Lecture 9 Fintech Python Question

Lecture 10 FAANG SQL Question

Lecture 11 Insurance Tech Take Home Question

Lecture 12 Insurance Tech Take Home Question Going through An Example

Lecture 13 Food Delivery Data Science Take Home

Lecture 14 Bitcoin Analysis Timed Take Home

Section 6: Conclusion

Lecture 15 Thank You

Beginners, Career Transitioners.