During the internship at CGI, the given tasks included predicting batch size and runtime for process estimation and also developing a chatbot for improved data interaction.The task included leveraging LSTM model for accurate batch size predictions and Random Forest Regressor for precise runtime estimations along with parsing of various datasets to feed into llama index and implementing RAGs to construct a chatbot.The outcome included the development of predictive models with different performance metrics and theintroduction of a chatbot that enhanced data accessibility.

During the internship at Allstate, the assigned project involved assessing client propensity for purchasing pet insurance based on client information and demographics. The responsibilities encompassed data preprocessing, exploratory data analysis, and model development using PySpark, Pandas, NumPy, Matplotlib, along with acquiring basic knowledge in image processing and deep learning. The outcome of the project comprised the development of predictive models exhibiting strong performance metrics and the creation of a presentation that conveyed actionable insights for targeted marketing strategies.