Inspired young students put their heads together to analyze data from Donorschoose.org. Each student defined their own problems and produced intriguing analysis reports based on exploratory and predictive analysis. With hands on experience on training and fine tuning models, the students gained valuable insights into data cleaning, training, modelling and analysis. They were backed by a team of dedicated mentors and undergraduate assistant.
Students learned how to install python and PyCharm. They imported various python libraries such as Pandas, Seagate and Scikit . They learned how to use a local environment as well as online notebooks to write, run and debug code.
Building customized programs to explore and analyze data. Debugging and modifying code to get meaningful results. Collaborating and comparing notes through teamwork.
Introductory to advanced courses in Data Science and Machine Learning. Building and optimizing models, exploratory analysis, hyper parameters and metrics to evaluate models and techniques.