We are trying out a different format in this episode. Nima gave me a topic, which is Central Limit Theorem. I spent an hour learning about it. And then we have a little chat. You will hear why we are doing this in the episode. And if you like this format, please send us an email at hello [at] nds.show . That helps us decide if we are going to make more episodes like this in the future.Meanwhile, if you are not a data scientist yet, but want to become one, you should really attend our webinar....
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We are trying out a different format in this episode. Nima gave me a topic, which is Central Limit Theorem. I spent an hour learning about it. And then we have a little chat. You will hear why we are doing this in the episode. And if you like this format, please send us an email at hello [at] nds.show . That helps us decide if we are going to make more episodes like this in the future.Meanwhile, if you are not a data scientist yet, but want to become one, you should really attend our webinar....
24 - How to find interesting data science work everywhere
Naked Data Science
27 minutes
5 years ago
24 - How to find interesting data science work everywhere
What happens when you are not working on interesting work? It is boring, you feel stuck, and your skills and career stop developing. But it is also very bad for your company: they now have an employee who is not delivering good outcome while still requiring high effort to manage, So obviously, it would be great if you and your company can always find work that is interesting to you. In this episode, we are going to show you some simple ways to do exactly that.BTW, if you are not a data scient...
Naked Data Science
We are trying out a different format in this episode. Nima gave me a topic, which is Central Limit Theorem. I spent an hour learning about it. And then we have a little chat. You will hear why we are doing this in the episode. And if you like this format, please send us an email at hello [at] nds.show . That helps us decide if we are going to make more episodes like this in the future.Meanwhile, if you are not a data scientist yet, but want to become one, you should really attend our webinar....
