I Thought Data Science Was About Models. I Was Wrong.

1. 1Reflect on your current understanding of data science using self-assessment tools to identify knowledge gaps
2. 2Explore the broader scope of data science beyond modeling, including data visualization and storytelling
3. 3Apply data science principles to real-world problems, considering both technical and business aspects
4. 4Discuss with colleagues or mentors the importance of interdisciplinary skills in data science
5. 5Evaluate case studies of successful data science projects to identify key factors beyond modeling

Data scientists and analysts on a team can benefit from recognizing the multidisciplinary nature of data science, which includes not only modeling but also data wrangling, communication, and business acumen

💡 Data science is a multidisciplinary field that requires a range of skills beyond machine learning modeling

💡 Data science is more than just models! #datascience #machinelearning