In this video, we're breaking down the key differences between data analytics, data engineering, data science, machine learning engineering, and software engineering careers, exploring the day-to-day work, required skills, salary expectations, and personality traits that lead to success in each role.
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📝 Transcript: https://medium.com/towards-data-science/how-to-pick-between-data-science-data-analytics-data-engineering-ml-engineering-and-sw-055de18d05e3
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⏰ Timestamps
00:00 Intro
01:05 Data Analyst role, skills, pros/cons, salary
03:52 Data Engineer role, skills, pros/cons, salary
05:49 Data Scientist role, skills, pros/cons, salary
08:46 Machine Learning Engineer role, skills, pros/cons, salary
10:59 Software Engineer role, skills, pros/cons, salary
13:20 Key decision factors
17:02 Common transition paths between roles
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🎥 Other videos you might like:
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https://www.youtube.com/watch?v=uakGF0DP-mk&t=43s
How To Learn Math for Machine Learning FAST (Even With Zero Math Background)
https://www.youtube.com/watch?v=KgolhE7p-KY&t=35s
Actually, Being a Data Scientist is Awesome (Motivation!)
https://www.youtube.com/watch?v=qEpmS_9tA9A&t=17s
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🦫 About me
I am an Applied Scientist (basically, a blend of Data Scientist/Machine Learning Engineer) at Twitch/Amazon. Outside of my full-time job I'm a technical mentor at a machine learning bootcamp, and a
1:1 career coach for people looking to break into the field, with a focus on those from non-traditional backgrounds.
I’m also a Certified Personal Trainer, always busy with too many interests, and really, deeply happy with my life. I hope to be able to help others achieve these things, too.
Instagram: / gratitudedriven
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✉️ Contact
Leave me a comment here on YouTube!
Business email:
[email protected]
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⚖️ Disclaimer
The views and opinions expressed in this video are my own and do not reflect the official policy or position of Twitch/Amazon or any other company I have worked for. All advice and insights shared here are based on my personal experiences and should be considered as such.
#datascience #machinelearning #swe #dataanalytics #dataengineering