Fundamentals of Data Science: History and Future of Data Science


Capability increased due to decreasing cost of data storage, cpu, and bandwidth.

Demand increased due to large amount of data being generated.


  • Demand for talent
    • “The future is so bright, Ada would need shades” – Joseph Burton
  • Emerging subdisciplines
    • Machine Learning Engineer
    • Data Visualization Engineer
    • Data Journalist
    • Big Data Engineer
  • Continued reduction in technical learning curve
    • Automation around machine learning and data wrangling
  • Ethics
    • risk of discrimination in “Black Box” models
    • machine learning can be used for bad as well as for good