Your Capstone project is the culmination of your time at GA! You will produce a project on your own that demonstrates the skills you have learned throughout the course. This introductory document lays out the three constituent portions of the project.
1 - Topic Options 2 - Topic Proposal and Dataset 3 - Report and Technical Analysis 4 - Non-Technical Presentation
Get started by thinking of some possible topics that you could investigate for your project. You should write up between 2 and 4 options. For each possible topic, write a statement of the problem that you want to solve and an overview of your approach to solving that problem. Outline where you have data, or where you can get it from, for each option. The outcome of this part is that you should know which topic you’ll be working on.
Deliverable: Prepare a presentation with a maximum of 5 slides which gives an overview of the topics you have considered and present your topics to the class for a maximum of 10 minutes in a ‘Lightning Talk’.
Get started on your chosen topic by determining and describing your problem, goals, criteria for success, potential audience(s), and dataset(s). Provide a clear statement of the problem that you want to solve and an overview of your approach to solving that problem. Summarize your objectives, goals and success metrics, and any risks and assumptions. Outline any proposed methods and techniques you have.
Deliverable: Prepare a presentation with a maximum of 10 slides which introduces and describes your problem, goals, criteria for success, potential audience(s), and potential dataset(s). This will form the first part of your Report Writeup.
Develop a technical report that can be shared among your peers. Document your research and analysis including a summary, an explanation of your approach as well as the strengths and weaknesses in the process. Consider delivering a combination of SQL queries, data files, a Jupyter notebook and an interactive dashboard in Tableau.
Provide a clear statement of the problem, goals, and criteria for success, and an overview of your approach to solving that problem. Data Sources and Definitions in a Data Dictionary All data should be cleaned, with redundant, duplicate, and erroneous data removed. Data should be clearly defined in a data dictionary.
Data should be analyzed using statistical techniques, to identify patterns, trends, and insights. Include at least one interactive dashboard visualization to provide insights to the business decisions required by the intended audience.
Use historical data to conduct predictive analysis on new data sets based on the predictive model.
Find a solution to your problem - if there is one. Make recommendations for your client to move forward on. Outline any setbacks and make recommendations of any further data required or a new data model to be built (if required). Next steps - What would you do next?
Whether during an interview or as part of a job, you will frequently have to present your findings to business partners and other interested parties - many of whom won't know anything about data analysis! You should already have the analytical work complete, so now it's time to clean up and clarify your findings. Come up with a detailed slide deck or interactive demo (or both) that explains your data, visualizes your analysis, describes your approach, articulates strengths and weaknesses, and presents specific recommendations. You will present your deck to the class and a select audience of non-technical audience for 10 minutes. Be prepared to explain and defend your presentation to an inquisitive audience!
Deliverable: Presentation of 10 minutes of your findings with a non-technical audience in mind. Due: last day of the course
Instructors will evaluate student skill based on the following rubric. For each element, instructors will give one of the following: Incomplete (I) Does Not Meet Expectations (N) Meets Expectations (M)
You must receive a score of Meets Expectations in all categories to pass this project.
Good luck and have fun!