Courses Taken:

• Special topics in Data Science: Causal Inference, Probabilistic Programming, Pyro, Pytorch

• Unsupervised Machine Learning: Frequent Item Set, FPGrowth, Apriori, Clustering

• Supervised Machine Learning: Regression, Classification, Neural Networks, Feature Extraction, P-value, t-statistics, Encoding, Scaling

• Data Processing and Management: Data Manipulation, Data Cleaning, Data Gathering, Data Mining

• Algorithms: Divide and Conquer, Network Flows, Time Complexities, NP-Hard, Dynamic Programming, Greedy Algorithm

• Natural Language Processing: SpaCy, Word Vectors, BERT, LSTM, Bi-LSTM

• Deep Learning: CNN, GAN, Keras, Pytorch, Image Processing

• Capstone Projects: Time Series Forecasting(Blue Bikes Capacity Planning) and Deep Learning(Road Sign Recognition)

Courses Taken:

• Database Management System: SQL, Entity Relationship, Microsoft SQL Server

• Object-Oriented Programming: Abstraction, Encapsulation, Inheritance, and Polymorphism

• Cloud Computing: AWS, Client-Server Architecture

• Engineering Mathematics: Calculus, Linear Algebra