Workshop Topic: Data Analytics and Machine Learning for Software Testers

Data Analytics is a crucial part in making important business decisions. In this session we will try to learn basics of Data Analytics, types, process of exploring the data, key libraries used, how to analyse data, clean and optimize, data pre-processing for machine learning model, etc. We will explore use cases to see how data analytics can be used for future predictions, and discover hidden patterns. Session will help software testers to understand machine learning model building steps. It will help in developing the skill for data analysis and interpreting the same. We will see libraries like pandas, NumPy, Matplotlib, scikit-learn, etc. Python coding will be performed in Jupyter notebook or google colab.

Key Takeaways:

• Understand Type of Analytics, Develop skills in analysis and interpretation of data
• How to use open-source tools, libraries for statistics How to use structured data and build machine learning model
• How to perform model validation and check accuracy on predictions.