Data Analysis with Python
(July’19)
Learnt how to analyze data using Python. From the basics of Python to exploring many different types of data, I learnt how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!
Some features of the course- Import data sets Clean and prepare data for analysis Manipulate pandas DataFrame Summarize data Build machine learning models using scikit-learn Build data pipelines Data Analysis with Python is delivered through lecture, hands-on labs, and assignments. It includes following parts:
Data Analysis libraries: learnt to use Pandas DataFrames, Numpy multi-dimentional arrays, and SciPy libraries to work with a various datasets. Introduction to pandas, an open-source library, and used it to load, manipulate, analyze, and visualize cool datasets. Introduced to another open-source library, scikit-learn, and used some of its machine learning algorithms to build smart models and make cool predictions.
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