This is the code repository for Data Science and Machine Learning (Theory and Projects) A to Z [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

This course is crafted to teach you the most in-demand skills in the real world. This course aims to help you understand all the data science and machine learning concepts and methodologies with regard to Python.
When you take a quick look at the different sections of this course, you may think of these sections as being independent. However, these sections are interlinked and almost sequential. Each section is an independent concept and is like a course on its own. We have deliberately arranged these sections in a sequence as each subsequent section builds upon the sections you have completed. This framework enables you to explore more independent concepts easily.
At the end of every subsection, you are assigned homework to further strengthen your learning. All these assessments are based on the previous concepts and methods you have learned. Several of these assessment tasks will be coding-based, as the main aim is to get you up and proceeding to implementations.
By the end of this course, you will be able to easily tackle real-world problems and ensure steady career growth and will be equipped with the knowledge of all the essential concepts you need to excel as a data science professional.

This course is designed for people who want to become perfect in their data speak; people who want to learn data science and machine learning with real datasets in data science; people from a non-engineering background who want to enter the data science field; people who want to enter the machine learning field; people who want to learn data science and machine learning along with its implementation in realistic projects.
For this course, no prior knowledge is needed. You will start with the basic concepts and gradually build your knowledge of the subject.