Applied Data Science with Python

Colleagues, Applied Data Science with Python from the University of  Michigan over 263k students enrolled equips you for exceptional career and income growth. Glassdoor’s salary range for Data Scientists is $65k-$165k..Training modules include: 1)  Introduction to Data Science in Python - take tabular data, clean it, manipulate it, and run basic inferential statistical analyses, 2) Applied Plotting, Charting & Data Representation in Python - information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations, visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework, 3) Applied Machine Learning in Python - dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models, apply the Scikit learn predictive modeling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting), 4) Applied Text Mining in Python - text mining and manipulation basics. The course begins with an understanding of how text is handled by Python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text, common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes, natural language processing methods to text, and demonstrate how text classification is accomplished, and  advanced methods for detecting the topics in documents and grouping them by similarity (topic modeling), and 5) Applied Social Network Analysis in Python - network analysis through tutorials using the NetworkX library, connectivity and network robustness, centrality of a node in a network, and models of network generation and the link prediction problem. 

Register today (teams & execs welcome): https://tinyurl.com/y2k3pq6u 

Much career success, Lawrence E. Wilson -  Artificial Intelligence Academy