This course teaches Python developers how to perform data analysis with the language by taking advantage of the core data science libraries in the Python ecosystem. The learning objective is to understand how to locate, manipulate, and analyse data with Python, with the ability to analyse large and small sets of data using libraries such as Numpy, pandas, IPython and SciPy.
What You’ll Learn
- Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms
- Data analytics techniques to tease out unseen data relationships
- Visualize your data with open source libraries such as matplotlib, bokeh, and plotly
- Learn about various machine learning methods such as supervised, unsupervised, probabilistic, and Bayesian
- Get to grips with graph processing and social network analysis
- Dashboard application development to help share and monitor your progress/analysis
This course is for data analysts, data scientists, and machine learning developers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.x and its libraries. This course contains all the basic ingredients you need to become a data analyst.