Practical AI On being humAIn
Aug 26, 2019
David Yakobovitch, a principal data scientist at Galvanize and host of the HumAIn podcast, dives deep into the evolution of data science and the tools shaping its future. He shares insights from his journey from math competitions to AI, emphasizing the importance of practical skills in tech education. The conversation highlights the need for empathetic design in AI as automation reshapes job markets, and explores how human-centered approaches can bridge the gap between technology and society.
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Adapting to Tech Change
- David Yakobovitch's father, an entrepreneur, saw his electronics repair business decline due to technological advancements.
- He then learned Python and applied it to robotics projects, demonstrating the importance of relatable learning.
Choosing Data Science Training
- When choosing a data science training program, consider your goals and background.
- Look for programs with evolving curriculums and ask specific questions about the tech stack and projects.
Data Science Evolving
- Data science is still evolving, with most roles focusing on data cleaning and preparation.
- Specialization within the field is increasing, leading to new roles like ML Engineer and Data Engineer, and the emergence of Data Science as a Service.
