1. Congratulations!
Great job! You have successfully completed this case study, and also completed the whole course! As the saying goes, "A chart is worth a thousand words", and in this course you have learned how to produce informative and powerful graphs of time series data. Hopefully, you will be able to apply some of the techniques that you have learned in this course to further your professional career.
2. Going further with time series
In addition, you should also feel comfortable moving forward and starting your own analysis or project. Let's go through a few examples of what you could do in order to hone your skills further. You could use the data made available by Zillow in order to explore trends and seasonalities in rental prices across US cities. You can participate in one of the many Kaggle competitions focusing on time series data. Finally, you can also explore the large Reddit data dumps to uncover interesting patterns, such as the frequency of comments over time for specific topics.
3. Going further with time series
Time series is omnipresent across many different industries and fields, and there are many opportunities for you to explore and even innovate within the scope of your professional work. For example, you could leverage your company's data to identify seasonal patterns and trends in order to uncover new information about your business. Additionally, you could leverage time series data to study past behavior or produce robust forecasts. For example, you could consider implementing a revenue forecast model to help inform your company's next year goals in a data-driven manner. Finally, the skills you have acquired in time series visualization could be leveraged as part of a project to evaluate and compare your company's achievements.
4. Getting to the next level
You also have the opportunity to extend your knowledge with additional courses right here on DataCamp. If you would like to continue studying time series, then you could take the "Manipulating time series data in Python" course or see how they can be applied in the Financial world by taking the "Importing & Managing Financial data in Python" course. Otherwise, you could also branch out into other areas of Statistics and Machine Learning by taking a look at the "Statistical thinking in Python" and "Supervised learning with Scikit-Learn" courses!
5. Thank you!
This is the final video, and I would like to thank you again for taking the time to go through this course. I hope it was helpful for you, and that you have learned what you were hoping to learn! Time series analysis is an incredible tool to have as part of your skillset, and with their widespread use across many industries, the knowledge you have acquired will surely be of use to you!