- Course type
- Paid course
- All Levels
- 7 hours
- 84 lessons
- Available on completion
- Course author
- Shivani Rajpoot
- Have a fundamental understanding of the Python programming language.
- Have a fundamental understanding of the machine learning.
- Understand and learn machine leaning and predictive model based on machine learning .
- Understand Python 3.
- Have the skills and understanding of Python to confidently apply for machine learning , data science , academics and Python programming jobs.
- Understand how to create your own Python programs.
- Understand how to create your own machine learning protective models and apply machine learning..
Welcome this comprehensive Machine learning and Python course! This course assumes you have NO prior knowledge in Python programming and Machine learning and by the end of it you'll be able to code in python and code like programming experts! and able to create machine learning models.
This course is highly practical but it won't neglect the theory. we'll start with python basics, and then understand the complete concept of environment , variables , loops , conditions and more advance concept of python programming and machine learning and we install the needed software (on Windows, Linux and Mac OS X), then we'll dive and start python programming straight away. From here onward you'll learn everything by example, by analyzing and practicing different concepts such as operator, operand, conditional statements, looping ,data management .....etc, so we'll never have any boring dry theoretical lectures.
The course is divided into a number of sections, each section covers a complete python programming field and complete machine learning field, in each of these sections you'll first learn basic python, and how to practically apply the concept of python on your lab, not only that but you'll also learn how to apply python for data science and machine learning. By the end of the course you will have a strong foundation in most python programmingand machine learning fields.