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.
Enroll now: Data Science Interview Preparation
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.
Can I take my courses with me wherever I go?
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