
19 - How to fast-track your domain knowledge
08/09/20 • 35 min
How domain knowledge can supercharge your data science work. The half-life of truth at three levels of business domain knowledge. Why it is important to follow the money in data science work. Three ways to acquire new domain knowledge fast.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.
How domain knowledge can supercharge your data science work. The half-life of truth at three levels of business domain knowledge. Why it is important to follow the money in data science work. Three ways to acquire new domain knowledge fast.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.
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18 - The 7 habits of thinking in questions
How thinking in questions can help you communicate your work effectively, especially to non-data-scientists. Avoid getting lost when finding your path to a solution. Three reasons why you should always ask more questions when you hear a question. How to think like a detective.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.
Next Episode

20 - Systems thinking in data science
Systems thinking to make sense of your data science work. The similarity between dead fishes and recommender systems. Effect of time and feedback loop on your models. Look beyond your dataset. Applying systems thinking to people and teams. How to change a system without breaking your back.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.
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