PDAIML

Postgraduate AI & ML

Capstone Rubric

Develop a presentation on your analysis of the client data. The presentation should have a professional look.

Choose a template that looks professional

• Make certain that you use consistent fonts of appropriate size

• Convey the necessary information with the proper amount of detail for a presentation (primarily bullet form)

• Avoid typos and mis-spelling

• Use graphics when appropriate, label them clearly

The presentation should contain the following elements

Background (5%)

State the current situation that the company is facing. Why do they need data science assistance? Don’t be too wordy. The company knows their situation. You just need to convince them that you understand their situation.

Objectives (10%)

Be specific with respect to the objectives of your analysis. What can the client expect? What are the benefits?

Approach (15%)

Describe the process that you will go through: How you determined a solution, where you will get data, what the data includes, any processing/cleaning of the data, what the solution will include, how it will be implemented.

Analysis Results (50%)

Present the results of your analysis. Be clear and concise. Remember that your audience consists of business managers, not data scientists. Profile what your target audience looks like. Use graphics. Display important variables and possibly combinations of variables. Select the correct analytical technique. Briefly describe why this is the correct technique. Describe the variables used for your analysis and their importance. Show the results of your validation in a way that can be monetized or quantified by the client, include a Gains Chart. Use appropriate graphics. Clearly label all you axes. Be consistent with your use of color. Use bullet points to highlight the findings.

Recommendations (20%)

Provide clear recommendations as to how to utilize your analysis. Are there any concerns or anything that requires special attention?