Uploaded August 2024 | Updated September 2026, 2 days ago
Boost your data science productivity with ChatGPT! Learn how to leverage AI to automate tasks, from data retrieval and cleaning to analysis, visualization, and model building. Discover practical tips and tricks to streamline your workflow and achieve better results.
This video covers:
◉ SQL query generation with ChatGPT and integration with popular databases
◉ Automated data cleaning using ChatGPT and Python scripts
◉ Generating insights and summaries directly from your data
◉ Creating stunning visualizations with ChatGPT and Python libraries
◉ Brainstorming model features for enhanced model performance
◉ Efficient code debugging and optimization with ChatGPT's assistance
◉ Automating documentation for better project management
Master ChatGPT for data science today!
______________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow
______________________________________________________________________
Timeline:
Intro: (0:00)
Hack #1 - Retrieving Data: (0:17)
Hack #2 - Automate Data Cleaning: (1:00)
Hack #3 - Generate Insights and Summaries: (1:44)
Hack #4 - Data Visualization: (2:39)
Hack #5 - Brainstorm Model Features: (3:39)
Hack #6 - Code Debugging and Optimization: (4:11)
Hack #7 - Automate Documentation: (4:48)
Conclusion: (5:32)
______________________________________________________________________
About The Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
______________________________________________________________________
#datascience #chatgpt #ai #dataanalytics #dataanalysis #dataanalyst #datascienceskills
Boost your data science productivity with ChatGPT! Learn how to leverage AI to automate tasks, from data retrieval and cleaning to analysis, visualization, and model building. Discover practical tips and tricks to streamline your workflow and achieve better results.
This video covers:
◉ SQL query generation with ChatGPT and integration with popular databases
◉ Automated data cleaning using ChatGPT and Python scripts
◉ Generating insights and summaries directly from your data
◉ Creating stunning visualizations with ChatGPT and Python libraries
◉ Brainstorming model features for enhanced model performance
◉ Efficient code debugging and optimization with ChatGPT's assistance
◉ Automating documentation for better project management
Master ChatGPT for data science today!
______________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow
______________________________________________________________________
Timeline:
Intro: (0:00)
Hack #1 - Retrieving Data: (0:17)
Hack #2 - Automate Data Cleaning: (1:00)
Hack #3 - Generate Insights and Summaries: (1:44)
Hack #4 - Data Visualization: (2:39)
Hack #5 - Brainstorm Model Features: (3:39)
Hack #6 - Code Debugging and Optimization: (4:11)
Hack #7 - Automate Documentation: (4:48)
Conclusion: (5:32)
______________________________________________________________________
About The Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+chatgpt+in+ds+workflow. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
______________________________________________________________________
#datascience #chatgpt #ai #dataanalytics #dataanalysis #dataanalyst #datascienceskills
![Advanced Facebook Data Science SQL interview question [RANK()]](https://i.ytimg.com/vi/PlpUo6bHsBQ/mqdefault.jpg "Advanced Facebook Data Science SQL interview question [RANK()]
This advanced SQL question is from the Facebook data science interview that tests your ability to write window functions and rank data and use some advanced functions like coalesce. It’s a complicated question that involves subqueries and joins and also tests your knowledge in rankings.
Link to the question to follow along with me: https://platform.stratascratch.com/coding/2007-rank-variance-per-country?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Interview Question: (0:33)
Framework to solve the problem: (0:58)
Understand your data: (2:18)
Formulate your approach: (5:38)
Code Execution: (8:42)
Conclusion: (23:05)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#FacebookDataScienceInterview")
![Advanced Data Science SQL Interview Question [Amazon] (window functions & aliasing)](https://i.ytimg.com/vi/QenwDm5oWdU/mqdefault.jpg "Advanced Data Science SQL Interview Question [Amazon] (window functions & aliasing)
This SQL data science interview question was asked by Amazon and will test your date manipulation and window function skills. I’ll cover both the question and walk you through the approach. I’ll also talk about my 4 step approach to solving any data science interview question. This is literally how I would answer every data science interview question and prepare for every data science interview at FAANG companies and others.
Link to the question: https://platform.stratascratch.com/coding/10319-monthly-percentage-difference?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
This series is for both beginner and intermediate data scientists and analysts interested in learning how to solve common data science interview questions in SQL. These are real data science interview questions. For some background context and an intro about what this series is about: https://bit.ly/36kKbxG
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Question: (1:18)
4-Step framework to solve the question: (2:02)
Explore underlying data: (2:18)
Identify required columns: (3:45)
Visualize the output: (4:12)
Build solution step-by-step and test: (4:44)
Coding: (4:57)
Format data to YYYY-MM: (6:27)
Calculate current months revenue: (7:46)
Calculate previous months revenue: (8:36)
Aggregate to year-month: (10:25)
Implement month-over-month difference formula: (11:26)
Apply a window alias: (13:15)
Clean up formatting: (14:06)
Conclusion: (14:50)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#datascienceinterview #sqlinterviews")
![Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]](https://i.ytimg.com/vi/Qh9ajFNeIEc/mqdefault.jpg "Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]
Welcome to the second series of the Facebook data science project for predicting movie ratings! In this video, we explore building a high-performance classification algorithm to predict movie ratings. We merge two data sets, focusing on review sentiment to determine whether a movie is labeled as Rotten or Fresh. Join us as we preprocess the data, analyze the distribution of review types, and implement a random forest model. Dont forget to subscribe and stay tuned for the next video in our series!
Go to the project through the link below and follow along with us👇
https://platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1
Watch the previous videos from the first series:
📌 [Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings: https://youtu.be/cM12QtrhdLo
📌[Part 2]: Exploring Decision Tree Classifiers For A Facebook Data Science Project of Movie Ratings: https://youtu.be/Ih6G5hnn30Q
📌 [Part 3]: Random Forest Classifier For A Facebook Data Science Project of Movie Ratings: https://youtu.be/J4rheMtvu6g
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1
Timeline:
Intro: (0:00)
Take-home assignment: (0:18)
Approaches review: (0:31)
Preparing the dataset: (1:10)
Using the head method for data review: (2:34)
Encoding the labels into integer representation: (3:45)
Splitting the dataset into train and test sets: (4:30)
Tokenization in NLP: (4:53)
Using a random forest classifier: (6:21)
Improving the models performance: (7:33)
Take away: (9:24)
About The Platform:
StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
#datascienceproject")
