Python for Machine Language
This course covers fundaments of important python libraries like Pandas, Numpy, Scipy and Matlabplot which are used in Machine Learning.
Machine Learning and Data Science are most important career options for the future. As we generate billions of data each day, there is rising demand of data scientists to process them. Python is most popular language used in machine learning. Its popular libraries provides required support for collating and processing data. In this course for Python for Machine Learning, we will covers basics of important python linraries like Pandas, Numpy, Scipy and Matplotlib and cover their usage in Machine Learning and Data Science. This course is necessary for candidates who want to build their career in data science field. In this course, we will provide video lectures material, practice test module along with teacher support for doubt resolution.
1. Good internet connection
2. Python environment set up
3. IDE like Jupyter notebook or Spyder
4. Text Editor like Sublime Text or Atom
5. Basics of Python programming
- Introduction to Pandas
- Working with data
- Pandas functionality
- Introduction to Numpy
- N dimension array
- Array Classes
- Universal functions
- Introduction to Scipy
- Mathematical functions
- Scientific functions
- Special functions
- Introduction to Matplotlib
- Matplotlib classes
- Working on Axes and Grid
- Practice Module
yes this course was a good match for me because i actually learned things i had no clue about which will help me later and to also teach others.
This course is designed keeping in mind applications in Data Science. This course covers all the important Python libraries required in Machine Learning.
This course is designed for begineer in Data Science and Machine Learning. If you college students or want to shift to Data Science career, you can take this course.
You need to have understanding of Python language and its syntax.
This course is designed and created by team of IIT IIM graduates having rich experience in data science and machine learning.
We will in touch via Email support and whatsapp
An average student cover this course in 2 months.