Project Week: Showcasing Your Data Analysis Skills

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'll walk you through setting up a Jupyter notebook and running a data analysis on a dataset of your 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 information relevant to your interests or line of work. To stay motivated during the assignment, it is important 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 getting the 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 is where 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 your analysis using the techniques you've already learnt. Depending on how your data is formatted, you might need to tidy it up or merge it. Also, you should prepare to employ the text 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 to help verify that the data is accurate? Visualize the data to better understand it, and when you start gaining insight into an answer, be skeptical. What would someone critical of your result ask about your findings? If possible, try to answer those critical questions, or be upfront and admit 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 and give you feedback. We'll give you a template of a slide deck that you can use to put together your findings. It is your responsibility to communicate your findings in a clear and concise manner, 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 generally found people to be too harsh when they first undertake peer review. You can fill in any holes in your analysis with the aid of peer evaluation, which will also give you the chance to improve 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 a dataset, develop research questions, analyze data using machine learning and text analysis methods, and present your conclusions in an organized and understandable way. You should be pleased of this project and display it to your loved ones.