Uploaded November 2022 | Updated September 2026, 2 days ago
Data science is a rapidly growing field and there are many different career types available to people who want to pursue it. In this video, we're going to explore the difference between data providers and data users, and how to choose the job role in data science.
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👉 Watch the full video: youtu.be/qbN_t6sh4_E
👉 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
👉 Practice real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
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About The StrataScratch Platform:
StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link) 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 interview practice with real data science interview questions, visit 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.
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Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
#StrataScratch #DataScienceJobs #DataScienceCareer
Data science is a rapidly growing field and there are many different career types available to people who want to pursue it. In this video, we're going to explore the difference between data providers and data users, and how to choose the job role in data science.
______________________________________________________________________
👉 Watch the full video: youtu.be/qbN_t6sh4_E
👉 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
👉 Practice real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
______________________________________________________________________
About The StrataScratch Platform:
StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link) 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 interview practice with real data science interview questions, visit 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
______________________________________________________________________
#StrataScratch #DataScienceJobs #DataScienceCareer
![Top Data Science Interview Question And Answer Mistakes 2021 [Asked By Amazon]](https://i.ytimg.com/vi/j8kGqAAIhxA/mqdefault.jpg "Top Data Science Interview Question And Answer Mistakes 2021 [Asked By Amazon]
Were going to cover the #1 most common mistake made on data science interviews. This mistake is made by both inexperienced and experience data science professionals; it happens both on interviews and in the work setting; and the mistake takes place when trying to solve the most common data science question. Lets cover it so that you dont make the same mistake.
Follow me interactively with the question here: https://platform.stratascratch.com/coding/9915-highest-cost-orders?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Platforms I recommend to practice data science real scenarios:
- https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link (data science questions)
- https://leetcode.com (general database questions)
- https://datacamp.com (niche specific analytical skillsets)
👉 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
Timestamps:
Intro: (0:00)
Description of the most common mistake: (0:34)
Coding example of mistake: (1:00)
How to properly solve the question: (4:50)
Reason why youre making these mistakes: (7:30)
Recommendations to improve: (8:10)
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#datascience #sqlinterviews #codinginterviews")
![Mastering Movie Classification: Rotten Tomatoes Data Project [Part 2]](https://i.ytimg.com/vi/kcTrK4xxhPk/mqdefault.jpg "Mastering Movie Classification: Rotten Tomatoes Data Project [Part 2]
Welcome to the final episode of our Rotten Tomatoes Data Project series! In this video, we dive into the exciting world of movie rating predictions. Weve built a high-performance classification algorithm to determine whether a movie is labeled as rotten, fresh, or certified fresh. Join us as we explore the steps involved in predicting a movies status and discuss tips to enhance the performance of our model. From gathering and analyzing reviews to using random forest models, well guide you through the process. Dont forget to like, subscribe, and leave a comment with your thoughts and suggestions.
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+p2
Dont miss the previous part:
📌 Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]: https://youtu.be/Qh9ajFNeIEc
👉 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+p2
Timeline:
Intro: (0:00)
Approach review: (0:44)
Predicting the Movies status: (2:25)
Body of Lies status prediction: (2:31)
Angel Heart status prediction: (4:09)
The Duchess status prediction: (5:37)
Improving the models performance: (6:27)
Take away: (7:13)
About The Platform:
StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p2) 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+p2. 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")
