Data Science Courses

IBM Data Science Professional Certificate (COURSERA)

I started to take notes from the 3rd Course: Data Science Methodology:

The Data Science Methodology aims to answer the following 10 questions in this prescribed secuency:

What is Data Science?:

1. What is the problem that your are triying to solve?
2. How can you use the data to answer the question?

Data Science Methodology:

1. What data do you need to answer the cuestion?
2. Where is the data coming from (identify all sources) and how you will get it?
3. Is the data that you collected representative of the problem to be solved?
4. What additional work is required to manipulate and work with the data?

Tools for Data Science:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

Tools for Data Science:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

Python for Data Science, AI & Development:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

Databases and SQL for Data Science with Python:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

Machine Learning with Python:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

Python Project for Data Science:

1. In what way can the data be visualized to get the answer that is required?
2. Does the model used really answer the initial question or does it need to be adjusted?
3. Can you put the model in the practice?
4. Can you get construtive feedback into answering the question?

From week 3 of the course: Data Science Methodology - IBM Data Science Professional Certificate