Data Analysis with Python

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


Audience


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.

Getting Started with Python Libraries

Retrieving, Processing, Manipulating and Storing Data

Presenting stories via simple visualizations

Signal Processing and Time-series

Analyzing Textual Data and Social Media

Predictive Analytics and Machine Learning

Performance Tuning, Profiling and Concurrency

Program Details
Duration 1 Day
Capacity Max 12 Persons
Training Type Classroom / Virtual Classroom


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