Python Programming 1

Python Programing Seminar – Basic for statistical programmers and Statisticians

Presented: TBD

Presented by:
Kevin Lee is a Data Scientist, Machine Learning Leader/Instructor/Evangelist in Pharmaceutical Industry. Currently, Kevin is Assistant Vice President of AI/Machine Learning Consultant at Genpact and teaches Machine Learning/Python/CDISC/Oncology courses at conferences and university. Kevin has been a big advocate in leadership and innovative technologies, with which Kevin wants to innovate Pharmaceutical Industry. Kevin earned an M.S. in Applied Statistics at Villanova University following a B.S. from University of Pennsylvania.

Python is one of the most popular language nowadays. Python can be used to build just about anything, and it is a great language for back-end web development, data analysis, scientific computing, machine learning and many more.

The seminar is intended for Statistical Programmers and Statisticians who are familiar with SAS programming. It is not easy for programmers and biostatisticians to learn new language alone. The seminar will provide basic concept and foundation of Python programming, and the seminar will provide its comparison and similarity with SAS programming. Therefore, Statistical Programmers and Statisticians have easier time to understand how Python programming works.

The basic Python Programming seminar will cover basic Python programming. It is recommended for those who has a little or no experience in Python programming. It will help SAS programmers and statisticians how to start Python programming and how to use Jupyter Notebook/Lab (the most popular python platform).

    Agenda for the seminar: Python Programming Seminar – Basics

  • Introduction to Python for statistical programmers and statisticians
  • Jupyter Notebook (Python programming platform) download and implementation
  • Python Variables Type: Number, String, Lists, Dictionaries, Arrays, Data Frames
  • Simple variable manipulation – If & For statements
  • Python Function development and comparison with SAS Macro
  • Import external Modules/Functions
  • Reading and writing external data (excel, SAS datasets, Images)
  • Data manipulation using Python
  • Introduction of NumPy and Array
  • Introduction of Pandas and DataFrame: DataFrame vs SAS datasets
  • Basic data manipulation – merge, sort, variables drop/addition
  • Create SDTM DM dataset using SAS raw datasets