Python is widely-used for data analysis, visualization and in application development due to its versatility, scalability and ease of learning, compared to other languages. To kick-off the programme, you will learn, or refresh, your Python programming skills in preparation for the subsequent modules. Statistics and probability concepts covered include measures of central tendency and variability, distributions and hypothesis testing.
By the end of this module, you will:
- Be able to map abstract workflows into efficient code
- Be able to understand how algorithms works in the real world inclusive of use of tools such as Github and bash, aside from the terminal
- Understand and manipulate basic data structures, flow control and requisite Python syntax
- Understand core statistical and probability concepts including descriptive statistics, distributions, statistical significance, hypothesis testing and confidence intervals