Python is a high-level, interpreted, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. For approaching a data science project one must need to have an interest in data science. for that reason, they should have some previous knowledge about data science. The must need to have an idea of how data science work. What we can do in this field. Informed decision-making and prediction is the most important task of data science. Analyzing data in data science is the way to predict any scenario.
Before doing data analysis we need to complete some prior parts to continue with the project and need to understand the data clearly. Because without understanding data it’s not possible to work with the data. There I haven’t shown the actual data analysis part. That means this course is not on data analysis, It’s on the process that the data scientist use before go for analysing data. So, let’s see what is there for you.
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
Colab is a free Jupyter notebook environment that runs entirely in the cloud. Most importantly, it does not require a setup and the notebooks that you create can be simultaneously edited by your team members – just the way you edit documents in Google Docs. Colab supports many popular machine learning libraries which can be easily loaded into your notebook.
You may have a look at – How to prepare for studying online