As AI continues to integrate into an increasingly diverse set of applications, the role of an AI project manager becomes increasingly complex and crucial. This post aims to provide a glimpse into the role of AI project management and tries to underscore the effort required to ensure the success of […]
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Data Analytics vs Data Science – Is there a difference between these two fields? With the explosion of the need to analyze data, it can be confusing to understand what the distinction is between the different related fields of data science and data analytics. While data science and data analytics […]
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Not stopping at merely utilizing apps like ChatGPT, many companies are building, or exploring the possibility of building, their own Generative AI bots for internal use as well as for use by their clients. However, since Generative AI is so new, people wonder if managing Generative AI projects is different […]
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In the rapidly evolving world of artificial intelligence (AI), project management can be as complex as the technology itself. A staggering number of AI projects fail, not due to a lack of technical prowess, but because of ineffective project management. Implementing a well-defined AI project life cycle can significantly improve […]
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Generative AI, used in ChatGPT and Bard, will provide innovative ways for teams to collaborate and execute projects, transforming the way data science teams operate and interact. In short, as these models evolve, their potential impact on how teams execute data science projects will be substantial. More generally, generative AI, […]
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Do data science teams use (or think they use) an agile data science team process framework? To help find out, my student (Sucheta Lahiri) recently presented an academic paper that reported on data science agility across 16 organizations. The key takeaway was that even if your team thinks you are […]
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To deliver useful data science projects, it is important to effectively manage the data science team. But what does it mean to manage a data science team? How is it different from managing other teams? These are the questions I’ll explore in this post. Way back in 2018, an article […]
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Machine learning predictive models are often used in data science projects. These models often deliver significant value. Examples of these AI models range from identifying skin cancer to optimizing when to milk cows. Unfortunately, there are many examples of AI (machine learning algorithms) not working as desired. For example, a […]
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A data science team’s process is a key driver to their projects’ success. However, as will be discussed below, there is not an existing AI / data science maturity model that is focused on how to evaluate (and improve) a team’s process. Hence, after reviewing several Analytics / Data Science […]
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The machine learning process defines the flow of work that a data science team executes to create and deliver a machine learning model. In addition, the ML process also defines how the team works and collaborates together, to create the most useful predictive model. A High Level Machine Learning Process […]
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Data science projects are unique. It’s time to start managing them as such.
Get the jumpstart guide to better manage your next project.