Projects from General Assembly Data Science Immersive course
Project 1: We took a look at aggregate SAT and ACT scores and participation rates in the United States, to identify trends in the data and combined our data analysis with outside research. The SAT and ACT are standardized tests that many colleges and universities in the United States require for their admissions process. This score is used along with other materials such as grade point average (GPA) and essay responses to determine whether or not a potential student will be accepted to the university.
Project 2: Created and iteratively refined a regression model. Using Kaggle to practice the modeling process. Providing business insights through reporting and presentation. Created a regression model based on the Ames Housing Dataset, to predict the price of a house at sale. The Ames Housing Dataset is an exceptionally detailed and robust dataset with over 70 columns of different features relating to houses. Secondly, we had a competition on Kaggle to give you the opportunity to practice the following skills
Project 3: In week four we learned about a few different classifiers. In week five we learned about webscraping, APIs, and Natural Language Processing (NLP). This project will put those skills to the test. For project 3, our goal is two-fold:Using an API, we collected posts from two subreddits of your choosing. We then use NLP to train a classifier on which subreddit a given post came from. This is a binary classification problem.
Project 4: A one day hackathon
Project 5: Renewable Energy Sector Momentum Analysis; with time series, ARIMA, and VAR modeling