Data Science with Python

Learning Objectives

Upon completion of this course, participants will be able to:

• Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics
• Understand the essential concepts of Python programming such as datatypes, tuples, lists, dicts, basic operators, and functions
• Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions
• Perform data analysis and manipulation using data structures and tools provided in the Pandas package
• Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
• Use the Scikit-Learn package for natural language processing and matplotlib library of Python for data visualization