From Data to Dashboard: make an interactive model


Students typically create their portfolios out of simple, clean datasets. These projects are great to learn the basics, but they allow you to circumvent the most essential data science skills. Data on the job requires extensive cleaning, exploration, and feature engineering to become usable for your models. Projects in the professional space will also require steps beyond the initial creation and evaluation of a model. 
This hands-on skill-building webinar is for starting and intermediate data science students with a basic knowledge of Python. By the end of this session, you will know:
  1. Where and how to look for your data
  2. Some basic data engineering techniques to keep in mind
  3. How to use pandas to load, clean, and engineer your datasets
  4. How to use Matplotlib to plot and explore your data
  5. How to use Scikitlearn, and Tensorflow to model and evaluate your data
  6. How to use Pickle, Streamlit, and Matplotlib to turn your data into an interactive dashboard
Alexander Baker

Alexander Baker

Senior Federal Data Scientist at KPMG

Alexander Baker is a senior federal data scientist at KPMG. He has received two bachelor of engineering degrees (Biomedical and industrial engineering) with a minor (applied mathemUatics) and a master’s degree (industrial engineering) from the University of Virginia. He has been a federal consultant for the FDA, DHS, and DOD, working for Fortune 500 companies like Booz Allen Hamilton and KPMG. He is a mentor and manager for Illuminate AI as well as an ambassador for Deep-learning.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!


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