This course has been designed in two phases. Phase one introduces Python as a programming language and phase two surveys the foundational topics of data science such as data manipulation (using Numpy, Pandas), data communication and visualization (using Matplotlib, Seaborn), and data analysis with Statistics and Machine Learning (using Scikit-Learn).
Basic Knowledge of Statistics will be helpful
She is a technology and data enthusiast. She is currently working as a Data Scientist at S&P Global Market Intelligence, one of the leading providers of real-time data and analytics to institutional investors and corporations. She has over 3 years of experience in the field of Data Mining and Analytics. She likes to explore interdisciplinary Data Science to utilize technical skills borrowed from computer science and statistics to tackle real-world problems in social media, healthcare, and finance.
Professional Skills: Probability and Statistics, Linear Algebra, Machine Learning, Natural Language Processing, Deep Learning using Python