We start the course with our very first module, Python Fundamentals, to help you get familiar with Python. Installing Python correctly is equal to half job done. This module starts with the installation of Python, IPython, and all the necessary packages. Then, we'll see the fundamentals of object-oriented programming because Python itself is an object-oriented programming language. Finally, we'll make friends with some of the core concepts of Python—how to get Python programming basics nailed down.

Then we'll move towards the analysis part. The second module, Data Analysis, will get you started with Python data analysis in a practical and example-driven way. You'll see how we can use Python libraries for effective data processing and analysis. So, if you want to to get started with basic data processing tasks or time series, then you can find lot of hands-on knowledge in the examples of this module.

The third module, Data Mining, is designed in a way that you have a good understanding of the basics, some best practices to jump into solving problems with data mining, and some pointers on the next steps you can take. Now, you can harness the power of Python to analyze data and create insightful predictive models.

Finally, we'll move towards exploring more advanced topics. Sometimes an analysis task is too complex to program by hand. Machine learning is a modern technique that enables computers to discover patterns and draw conclusions for themselves. The aim of our fourth module, Machine Learning, is to provide you with a module where we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. So, if you want to become a machine-learning practitioner, a better problem solver, or maybe even consider a career in machine learning research, I'm sure there is lot for you in this module!