Introduction to Data Science using Python
- Offered byUDEMY
Introduction to Data Science using Python at UDEMY Overview
Introduction to Data Science using Python
at UDEMY
Learn Data science / Machine Learning using Python (Scikit Learn)
Duration | 2 hours |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Credential | Certificate |
Introduction to Data Science using Python at UDEMY Highlights
Introduction to Data Science using Python
at UDEMY
- 2.5 hours on-demand video
- Compatible on mobile devices and TV
- Certificate of Completion
- Full lifetime access
Read more
Introduction to Data Science using Python at UDEMY Course details
Introduction to Data Science using Python
at UDEMY
Skills you will learn
Who should do this course?
- Anyone who wants to learn about Data Science from absolute scratch.
- Anyone who wants to switch or make a career in Data Science and Analytics
- Anyone who is curious to know what is Data Science and what does a Data Scientist do in his/her day job.
What are the course deliverables?
- Understand how to use Python and Scikit learn
- Get a good understanding of all buzz words like "Data Science", "Machine learning", "Data Scientist" etc.
- 2.5 hours on-demand video
More about this course
- This course will the first data science course in a series of courses
- In this course understand the basics of Data Science and Analytics
Introduction to Data Science using Python at UDEMY Curriculum
Introduction to Data Science using Python
at UDEMY
Welcome
What is Data Science and Machine Learning?
Getting setup with Tools
Getting Started with Python and Scikit-Learn
Types of Machine learning algorithms
Playing Around with Anaconda and Jupyter
Playing with some Python Code
Getting Deeper into Machine learning frameworks and algorithms
Fitting a Machine Learning Model (KNN Algorithm) - Part 1
Fitting a Machine Learning Model (KNN Algorithm) Part 2
Fitting a Machine Learning Model (Logistic Regression Algorithm)
Validation using Model Selection (Train and Test)
Finalizing Your optimum algorithm (K-Fold Cross Validation)
Data Science - What's Next?
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