Self-taught Data Science.

The first day of my data science learning is over. Remember, I’m relying solely on YouTube and Notebooklm. Summary 1. Foundations of Data Science; Differences between 2 basic roles 1). Data Analyst / Focus on the past. 2). Data Scientist / Focus on predicting the future In the professional world, there is what is known as the "Data Science Project Lifecycle" a. Conceptual Study b. Data Preparation (Data Cleaning) c. Planning and Model Development d. Communication and Operationalization. 2. Mathematics and Statistics There are 2 branches that must be mastered 1). Descriptive statistics; (Mean, Median, Mode) 2). Inferential statistics. (Making predictions, forecasts, and conclusions) 3. Python Programming You must master two important libraries 1). Pandas 2). NumPy. That concludes today’s summary. (edited)