Microsoft DAT273x: Data Science Research Methods: Python Edition

I passed the DAT273x exam, and obtained the certification. The topic of the certification is called "Data Science Research Methods: Python Edition". I want to share my experience about the exam.

There are five modules: 1. The Research Process, 2. Planning for Analysis, 3. Research claims, 4. Measurement and 5. Correlational and Experimental Designs.

First, we need to understand what is the research process? And how to identify the research type? When we have a topic of study, then it's important that identify the study, such as Analytics, Basic research, applied research, etc.

Second, to understand the relation between the sample and the result. What kind of the information in the confidence interval? What is FP, FN, TP, and TN (false positive, False Negative, True Positive, and True Negative).

Third, we need to understand what is frequency claims, association claims and causal claims? The video provides explain on the YouTube (https://www.youtube.com/watch?v=PvkmEi65gIc).

Fourth, the module provides the knowledge about the measurement. What is the Likert scale, Reliability and Validity?

Fifth, the correlational and experimental design module provide more detail about the design. There have bivariate and multivariate designs. The topics have the between and within-groups experimental designs, and the factorial designs. Let research be able for reliability.

Summarily, the exam is not hard. There are good video tutorials. You just follow the tutorials, then answer these questions. However, you should understand the tutorials, and know these define about the knowledge of the research field.

Figure 1 This is my grade.

Figure 2 This is my certificate of the DAT273x.