Data Science Interview Preparation

Data Science Interview Preparation, available at $59.99, has an average rating of 3.94, with 68 lectures, based on 9 reviews, and has 130 subscribers.

You will learn about Data Science Interview Format Practice Interview Questions previously come in the Fortune Top 100 companies interviews Practice Hands-on SQL, Python and ML Model Building Included Solution Templates for Product Analytics and Design rounds with Case Studies Practice Probability, Hypothesis Testing and AB Testing Questions Practice Behavior and Cultural Fit Questions Follow the Course in any order as per your requirement This course is ideal for individuals who are This course is for anyone who is preparing for Data Science Interview whether you are applying for Entry Level Data Scientist or Senior Data Scientist or Lead/staff Data Scientist or 10+ Years of Experience It is particularly useful for This course is for anyone who is preparing for Data Science Interview whether you are applying for Entry Level Data Scientist or Senior Data Scientist or Lead/staff Data Scientist or 10+ Years of Experience.

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Summary

Title: Data Science Interview Preparation

Price: $59.99

Average Rating: 3.94

Number of Lectures: 68

Number of Published Lectures: 68

Number of Curriculum Items: 68

Number of Published Curriculum Objects: 68

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Data Science Interview Format

Practice Interview Questions previously come in the Fortune Top 100 companies interviews

Practice Hands-on SQL, Python and ML Model Building

Included Solution Templates for Product Analytics and Design rounds with Case Studies

Practice Probability, Hypothesis Testing and AB Testing Questions

Practice Behavior and Cultural Fit Questions

Follow the Course in any order as per your requirement

Who Should Attend

This course is for anyone who is preparing for Data Science Interview whether you are applying for Entry Level Data Scientist or Senior Data Scientist or Lead/staff Data Scientist or 10+ Years of Experience

Target Audiences

This course is for anyone who is preparing for Data Science Interview whether you are applying for Entry Level Data Scientist or Senior Data Scientist or Lead/staff Data Scientist or 10+ Years of Experience

The objective of this course is to provide the candidate with the right direction and proper guidance so that candidate must get ready for any kind of Data Science interview through Hands-on and practice questions in each possible rounds.

This course is for anyone who is preparing for Data Science Interview whether you are applying for Entry Level Data Scientist or Senior Data Scientist or Lead/staff Data Scientist or 10+ Years of Experience.

This course has covered all the possible important topics such as SQL, Python, Machine Learning Building, ML Design,

Product Analytics and Metrics, Statistics, AB Testing, Probability, Behavior and Cultural Fit Rounds etc.

90% of the practice questions in this course have previously come in the Fortune Top 100 companies’ interviews.

Follow the chapters in any order and you can pick and select any course in any order as per your requirement.

This course has covered Hands-on Practice Questions, Templates, preparation tips, Solutions, downloadable datasets as well as Python and SQL codes.

what you should not expect from the course ? This course will not cover like teaching fundamental concepts on python or SQL or ML. or some of the statistical concepts. In fact this is one of the pre-requisite that you already know the fundamental concepts and through this course you want to practice for your DS interviews. Moreover, You have access to Python Notebook and SQL editor.

Course Curriculum

Chapter 1: Introduction and Interview Format

Lecture 1: Course Introduction

Lecture 2: Data Science Interview Format

Chapter 2: SQL Questions

Lecture 1: Case Study 1: Manager Job Posting (Q1-3)

Lecture 2: Case Study 2: Survey Data (Q4-6)

Lecture 3: Employee Salary More than Dept Salary

Lecture 4: Balance Before Input Date

Lecture 5: Top 3 Products Across Each Category

Lecture 6: Find Customer Highest and Lowest Paid

Lecture 7: Customer Highest and 2nd Lowest Paid

Lecture 8: Customers Status in Consecutive 3 Times

Lecture 9: Employees Earn More Than Managers

Lecture 10: Customers Who Never Order Anything

Lecture 11: Find Dates with higher temperature

Lecture 12: Find The Second Highest Salary In Table

Lecture 13: Users Login Date Q1

Lecture 14: Users Login Date Q2

Lecture 15: Users Login Date Q3

Lecture 16: Users Login Date Q4

Lecture 17: Users Login Date Q5

Lecture 18: Practice Qestions

Lecture 19: SQL Preparation Tips

Chapter 3: Python Coding

Lecture 1: Arranging Zeros and Non-Zero Numbers

Lecture 2: String Can be Segmented

Lecture 3: Best Time to Sell Buy Stock

Lecture 4: Sum of Numbers Equal to Target

Lecture 5: Palindrome or Not

Lecture 6: Remove Duplicates

Lecture 7: Sum of the Digits of a Number

Lecture 8: Fibonacci Series

Lecture 9: Split the String Based on Vowels

Lecture 10: Case Study : Pandas & Visualization

Lecture 11: Practice Questions

Lecture 12: Python Preparation Tips

Chapter 4: Machine Learning Model Building

Lecture 1: Regression: Bike Sales Count

Lecture 2: Classification: Churn Prediction

Lecture 3: Practice : Movie Rating Prediction

Chapter 5: Machine Learning Design

Lecture 1: Template

Lecture 2: Predict Infrastructure Issue

Lecture 3: Fraud Identifying System

Lecture 4: Managing Employees Bandwidth

Lecture 5: Design Practice Questions

Chapter 6: Product Analytics & Metrics

Lecture 1: Template

Lecture 2: FB Likes are decreasing by 10%

Lecture 3: Team Change UI of the Text Box

Lecture 4: Analyze if Product is Performing Well

Lecture 5: Reduce Number of Fake Accounts

Lecture 6: Practice Questions

Chapter 7: Cognitive Ability

Lecture 1: Organizing Office Event

Lecture 2: Charging For Email Product

Lecture 3: Practice Question

Chapter 8: Probability Questions

Lecture 1: Questions 1-3

Lecture 2: Questions 4-6

Lecture 3: Expected Rolls to get Consecutive Sixes

Lecture 4: Practice Questions

Chapter 9: Hypothesis Questions

Lecture 1: Question 1

Lecture 2: Question 2

Lecture 3: Question 3

Chapter 10: Machine Learning Questions

Lecture 1: ML Questions Part 1

Lecture 2: ML Questions Part 2

Lecture 3: ML Questions Part 3

Lecture 4: ML Questions Part 4

Lecture 5: ML Questions Part 5

Lecture 6: Practice Questions

Chapter 11: Behavior & Cultural Fit

Lecture 1: Part 1: Q1-3

Lecture 2: Part 2: Q4

Lecture 3: Part 3: Q5-6

Lecture 4: Part 4: Q7-11

Lecture 5: Practice Questions

Instructors

Mohit Jain
Principal Data Scientist

Rating Distribution

1 stars: 1 votes

2 stars: 2 votes

3 stars: 0 votes

4 stars: 0 votes

5 stars: 6 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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