Project Week You've gained a lot of knowledge about data analysis already. The next step is to combine all of your knowledge into a final project that demonstrates your data analytic abilities. We'llwalk you through setting up a Jupyter notebook and running a data analysis on a dataset ofyour choice in this article. Finding the Right Dataset Finding a dataset in which you are interested is the first step in this procedure. Use the list of resources with useful datasets that we will present in our reading, or look for informationrelevant to your interests or line of work. To stay motivated during the assignment, it isimportant to identify facts that you are enthusiastic about. Exploring the Dataset Once you have found a dataset, the next step is to explore it using a Jupyter notebook. In this process, you will get a feel for what kinds of questions are answerable with the data.This step often involves data cleaning as well, so be prepared to spend some time gettingthe data into a format that is easy to work with. Identifying Research Questions After exploring the dataset, you should have a good idea of what questions you want to answer with the data. What do you want to know that the data might help answer? This iswhere you will need to identify a research question that you will use to guide your analysis. Continuing with Data Analysis The next stage is to continue working with your chosen dataset once you have your dataset and research topic in place. In week 10, you'll largely concentrate on developing youranalysis using the techniques you've already learnt. Depending on how your data isformatted, you might need to tidy it up or merge it. Also, you should prepare to employ thetext analysis and machine learning techniques that you acquired in the course's latter weeks. Visualizing Data
As you continue to analyze the data, you will want to look at it in multiple ways to put together an answer. Is the data reasonable? If appropriate, what checks did you perform tohelp verify that the data is accurate? Visualize the data to better understand it, and when youstart gaining insight into an answer, be skeptical. What would someone critical of your resultask about your findings? If possible, try to answer those critical questions, or be upfront andadmit your results may be limited because they're based on certain assumptions. Communicating Findings Once you are comfortable with the results and understand and document the limitation or supporting findings, you will put together a presentation for another learner to review andgive you feedback. We'll give you a template of a slide deck that you can use to put togetheryour findings. It is your responsibility to communicate your findings in a clear and concisemanner, using your analysis to support your conclusions. Importance of Peer Review The significance of treating peer review seriously cannot be overstated. You must be critical yet fair, just like in week six. If you must err, err on the side of fairness because I've generallyfound people to be too harsh when they first undertake peer review. You can fill in any holesin your analysis with the aid of peer evaluation, which will also give you the chance toimprove your presentation. This final project will, in the end, be the pinnacle of all the knowledge and abilities you have learned throughout this course. It will serve as an example of your capacity to locate adataset, develop research questions, analyze data using machine learning and text analysismethods, and present your conclusions in an organized and understandable way. Youshould be pleased of this project and display it to your loved ones.