With this course, gain insight into key statistical concepts and build practical analytics skills using Python and powerful third-party libraries. Instructor Michele Vallisneri covers several major skills: cleaning, visualizing, and describing data, statistical inference, and statistical modeling. All concepts are introduced by analyzing intriguing real-world datasets and discussed from a machine-learning perspective—which assumes that powerful computation can replace complex mathematics.

Topics include:

• Installing and setting up Python
• Importing and cleaning data
• Visualizing data
• Describing distributions and categorical variables
• Using basic statistical inference and modeling techniques
• Bayesian inference

About the Author

Michele Vallisneri is a theoretical astrophysicist at NASA Jet Propulsion Laboratory.

He obtained his PhD in physics at the California Institute of Technology in 2002. His research spans the detection and interpretation of gravitational waves with LIGO, in space, and with pulsar timing. He is an expert in data analysis, Bayesian inference, and computational physics, and he believes that elegant, transparent programming can illuminate the hardest problems. He is a Fellow of the American Physical Society, and he was awarded the NASA Exceptional Scientific Achievement Medal.

Product Details

• Full Video Tutorials
• Video File Format: MP4
• Skill Level: Intermediate
• Video Duration: 2h 58m
• Instructor: Michele Vallisneri

The post Python Statistics Essential Training appeared first on EASY Digital Pro.

Cut down on your development time by learning how to write elegant code in an efficient manner, specifically in Python—the popular and pragmatic computer language. Michele Vallisneri explains how to make your Python code more expressive and concise, and leverage the most powerful features of the language. He shines a spotlight on some of the strongest third-party packages you can take advantage of, discusses object-oriented and functional programming, and shares strategies for improving the performance of your code. Michele illustrates these concepts with many intriguing examples, showing how to make 3D images and animations of the sun, draw fractals, implement a graphical programming language, and more.

About the Author

Michele Vallisneri is a theoretical astrophysicist at NASA Jet Propulsion Laboratory.

He obtained his PhD in physics at the California Institute of Technology in 2002. His research spans the detection and interpretation of gravitational waves with LIGO, in space, and with pulsar timing. He is an expert in data analysis, Bayesian inference, and computational physics, and he believes that elegant, transparent programming can illuminate the hardest problems. He is a Fellow of the American Physical Society, and he was awarded the NASA Exceptional Scientific Achievement Medal.

Product Details

• Full Video Tutorials
• Video File Format: MP4
• Skill Level: Intermediate
• Video Duration: 2h 19m
• Instructor: Michele Vallisneri

The post Python: Programming Efficiently appeared first on EASY Digital Pro.

Data science is transforming the way that government and industry leaders look at both specific problems and the world at large. Curious about how data analysis actually works in practice? In this course, instructor Michele Vallisneri shows you how, explaining what it takes to get started with data science using Python.

Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas—two popular third-party packages designed specifically for data analysis. He also walks through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you've learned.

Note: This version of the course was updated to reflect recent changes in Python 3, NumPy, and pandas.

Topics include:

• Describe how to install and start Python, and load necessary libraries.
• Explain examples of uses for lists and ranges in Python.
• Explain string processing methods in Python.
• Describe the characteristics and specifications of NumPy arrays.
• Explain examples of uses for NumPy methods in generating and analyzing data.
• Use matplotlib to create xy plots.
• Describe the characteristics and specifications of DataFrames in pandas.

About the Author

Michele Vallisneri is a theoretical astrophysicist at NASA Jet Propulsion Laboratory.

He obtained his PhD in physics at the California Institute of Technology in 2002. His research spans the detection and interpretation of gravitational waves with LIGO, in space, and with pulsar timing. He is an expert in data analysis, Bayesian inference, and computational physics, and he believes that elegant, transparent programming can illuminate the hardest problems. He is a Fellow of the American Physical Society, and he was awarded the NASA Exceptional Scientific Achievement Medal.

Product Details

• Full Video Tutorials
• Video File Format: MP4
• Skill Level: Intermediate
• Video Duration: 2h 30m
• Instructor: Michele Vallisneri

The post Python Data Analysis appeared first on EASY Digital Pro.