Introduction to Python and Machine Learning

Master the basics of Pythons and Machine Learning from scratch. If you are looking for good start in Machine Learning this is the course for you to start with. This course is design in such a way which need only minimum or no programming experience from participants.

This course will walk you towards every step of Python and Machine learning starting from the history, setup and exercises in Python and Machine learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course focuses more on practical aspect rather than theoretical aspect of programming.

In this course you will cover the following topics in much greater details.:

1. Introduction to Python
2. Python Data Types
3. Control Flow
4. Function, Modules and Packages
5. I/O errors and Exceptions
6. Classes
7. Standard Libraries
8. Numpy
9. Metplotlib
10. Pandas
11. Machine Learning
12. Introduction to Machine Learning
13. Introduction to Scikit
14. Installing Scikit – learn
15. Introduction and Installing Jupyter Notebook
16. Techniques Of Machine Learning
17. Supervised Machine Learning
18. Unsupervised Machine Learning
19. Types of Machine Learning Algorithms
20. Classifications
21. and many more.

Who is the target audience?

• Anyone interested in Machine Learning.
• Students who have at least high school knowledge in math and who want to start learning Machine Learning.
• Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
• Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
• Any students in college who want to start a career in Data Science.
• Any data analysts who want to level up in Machine Learning.
• Any people who are not satisfied with their job and who want to become a Data Scientist.
• Any people who want to create added value to their business by using powerful Machine Learning tools.