Machine Learning Python refers to the use of the Python programming language in the field of machine learning. Python is a popular choice due to its simplicity and large community. It offers various libraries and frameworks like Scikit-Learn, TensorFlow, PyTorch, and Keras that make it easier to develop machine-learning models. Building machine-learning Python skills involves learning Python programming, understanding machine-learning algorithms, and gaining proficiency in using these libraries and frameworks. This can be achieved through various online courses, tutorials, and hands-on projects.‎

1. Data Scientist: They use machine learning to analyze large amounts of raw data and convert them into actionable insights.

2. Machine Learning Engineer: They design and build machine learning systems, conduct software tests, and implement machine learning algorithms.

3. AI Engineer: They work on complex AI models using machine learning and deep learning.

4. Data Analyst: They use machine learning to interpret complex data and help businesses make decisions.

5. Research Scientist: They apply machine learning in scientific research to analyze and interpret complex data.

6. Business Intelligence Developer: They use machine learning to analyze complex business data and provide insights.

7. Big Data Engineer/Architect: They work with large amounts of data and use machine learning to analyze and interpret it.

8. Quantitative Analyst: They use machine learning in financial institutions to identify profitable investment opportunities and risks.

9. Computer Vision Engineer: They use machine learning to develop systems that can "understand" images and videos.

10. NLP Scientist: They use machine learning to create systems that can understand human language.

11. Robotics Engineer: They use machine learning to design and build intelligent and autonomous robots.

12. Bioinformatics Scientist: They use machine learning to analyze and interpret complex biological data.‎

To get started with Machine Learning using Python on Coursera:

1. Python Fundamentals: If new to Python, start with basic Python programming courses.
2. ML Basics: Enroll in introductory machine learning courses, ensuring they're Python-centric.
3. Dive into Libraries: Explore courses that cover Python ML libraries like scikit-learn, TensorFlow, and Keras.
4. Hands-on Projects: Opt for courses with practical exercises where you can apply machine learning concepts using Python.
5. Certify Your Skills: Finish courses and earn certificates to validate your expertise in machine learning with Python. ‎