Introduction to Python

The course will focus on the essentials of coding in Python and ethical considerations of using algorithms. You will learn how to design functions, repeat code using loops, store data in lists, test and debug your code, and manipulate data using various data analysis and visualization tools such as Pandas, Matplotlib, Seaborn, and Plotly.

You will be taught to create and work in Python virtual environments. You will have discussions about the Tuskegee experiment, its long-term effects, and the trustworthiness of AI applications in disparate social systems.

The course will also develop the professional skills necessary to be a data scientist with a focus on machine learning. You will go through an industry overview, explore the job interview process, including potential technical questions, and receive additional resources.

Requirements

This course is designed for those who have a degree in something other than Computer Science/Statistics and are looking to enhance their data science skills for their career.

Learning Outcomes

  • The ability to design functions in Python following the Function Design Recipe
  • Various Python data types and their role in coding
  • How to test and debug Python code
  • How to interact with databases via Python
  • The ability to use Pandas and NumPy, and analyze a dataset in Jupyter Notebook
  • The ability to answer job interview questions with confidence

Delivery Format/Length

Online for 7 hours/week for 3 weeks (21 hours in total).

2022 Dates

  • Monday 28 November, 6pm-8pm: Getting started I (Introducing Python and programming)
  • Thursday 1 December, 6pm-8pm: Getting started II (Designing and using functions; working with text)
  • Saturday 3 December, 9am-noon: Dealing with reality I (True of False and control flow statements)
  • Monday 5 December, 6pm-8pm: Dealing with reality II (A modular approach; methods)
  • Thursday 8 December, 6pm-8pm: What we can do with data I (Lists, sets, tuples; Dictionaries)
  • Saturday 10 December, 9am-noon: What we can do with data II (Loops; read and write files)
  • Monday 12 December, 6pm-8pm: Developing efficiency, more on data, ethics
  • Thursday 15 December, 6pm-8pm: Professional skills: Industry case study
  • Saturday 17 December, 9am-noon: Python: Review and Practice