Description

• Python is a free, a general-purpose, and portable programming language. It is easy to use with its simple syntax and readability, which makes the code easy to understand and maintain (see the Berkeley blog). Python can be extended via libraries that can be used to tackle problems in machine learning, data analysis, and beyond. It has a vast ecosystem and a dynamic user’s community that make Python accessible to everyone.

• The focus of this course will be on Data Science. According to Wikipedia, Data Science is a concept to unify statistics, data analysis, machine learning and their related methods in order to understand and analyze actual phenomena with large volumes of data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science. It aims to find unseen patterns, derive meaningful information, and make decisions based on the data.

• Because of its features, Python is one of the preferred programming languages that data scientists can use to explore and analyze their datasets. The growth of Python in Data Science has gone hand in hand with that of its Pandas library, which opened the use of Python for data analysis to a broader audience by enabling it to deal with row-and-column datasets, import CSV files, and much more.

• This course introduces the fundamental concepts of the Python programming language. In addition, it presents Python packages (Numpy, Matplotlib, and Pandas) used for data manipulation and visualization. The basics of Python combined with the Data Science topics, provide the necessary foundations for Exploratory Data Analysis and Machine Learning.

Objectives

This course series is divided in two sessions:

Introductions to Python: Meant for interns who are familiar with basic computer programming, but are new in Python. Python for Data Science: Meant for interns who have Python knowledge and plan to work on a project involving Data Science. In the Introduction to Python, you will learn:

• Python basic syntax, variables, and types
• Conditional statements and loops
• Data structures: list, tuple, dictionary, set
• Functions and modules
• I/O with text files
• Scripting and packaging

At the end of the Introduction to Python sessions, learners will be able to write a basic Python application using functions and modules.

In the Python for Data Science, the following will be covered:

• Numpy arrays
• Basic visualization with Matplotlib
• Web scraping

Data manipulation (reading data file, performing statistical analysis, visualization, handling time series data) with Pandas Those with some knowledge of Python when they start the Python for Data Science session will be able to write their own Python scripts to access web resources, read remote text files or tables, perform data wrangling, carry out basic data analytics and visualize data.

Which Session to Select? Selecting a Session

• Teaching Platforms
• Cloud Platforms

Sessions

• Starting Point
• Introduction to Python
• Data Science Tools

Acknowledgement

ASTG provides Python related courses to enable NASA scientists and engineers to gather and manipulate their data better and faster. A variety of courses are given in the Fall and Spring, as well as summer bootcamps for incoming NASA interns. Some introductory self-guided exercises or beginner courses are also provided below to help prepare you for the courses.

ASTG Python Courses

The Advanced Software Technology Group (ASTG) provides a number of software and hardware support services to the NASA Goddard community. ASTG services include Level 2 help desk support, user training, code migration, performance tuning, parallelization, algorithmic development, software engineering, and code modernization. ASTG works closely with NCCS to assess code performance and system configuration as new hardware systems are integrated. Additionally, ASTG supports developmental projects to research beneficial impacts of emerging technologies on Earth science code performance and advancing software tools to enhance community use of NASA models.

ASTG aims to provide training opportunities in areas such as high-level computing languages, debugging tools, and parallelization of codes. Beginning in September 2020, ASTG plans to provide a series of Python training classes that focus on the followings:

• Knowledge of the language
• Data manipulation and visualization
• Data Science
• Machine Learning
• Data Parallelism

All the classes are meant for people who are already familiar with another programming language and quickly want to learn Python. Some of the courses here could be taken as SATERN credits and the registration process will be handled through SATERN.