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The ability to predict future outcomes is what got me interested in Data Science. It immediately drew me in and I knew it was the career I wanted to pursue. When the predictive modelling classes for my data science master’s program began, I wondered how accurate model predictions could be. Could predictions be 70%, 80%, or even 90% accurate? “That would be amazing!”, I thought to myself and the answer turned out to be yes but it didn’t end there; the more important questions

In a previous article, I shared the results from a survey I conducted to understand the biggest challenges Data Scientists face when it comes to Data Storytelling and collaborating with business stakeholders to successfully execute data science projects.   As a reminder, based on the survey, the biggest challenges Data Scientists face when it comes to collaborating with business stakeholders are:   Difficulty influencing decision making with data insights (30% of responses) A

I conducted a survey to understand the biggest challenges Data Scientists face when it comes to Data Storytelling and collaborating with business stakeholders to successfully execute data science projects.   In this survey, an anonymous respondent additionally shared this comment: “I've come to realise that stakeholders do not really   trust your analysis   sometimes when they realise there may be   errors from your data source . Some organisations don't really have a structu

AI's impact on professionals, businesses, and society as a whole continues to be a subject of active debate. After more than 8 years of doing the heavy lifting of coding myself, I began using AI more regularly over the past two months to help me write code for my data science projects. In this article, I will share how Data Scientists can benefit from using AI and also provide recommendations on how it (AI) can be used in a way that still allows for well-rounded skill develop