This course will teach you how to leverage the power of Python and artificial intelligence to create and test hypothesis. We'll start for the ground up, learning some basic Python for data science before diving into some of its richer applications to test our created hypothesis. We'll learn some of the most important libraries for exploratory data analysis (EDA) and machine learning such as Numpy, Pandas, and Sci-kit learn. After learning some of the theory (and math) behind linear regression, we'll go through and full pipeline of reading data, cleaning it, and applying a regression model to estimate the progression of diabetes. By the end of the course, you'll apply a classification model to predict the presence/absence of heart disease from a patient's health data.
This course is part of the AI for Scientific Research Specialization
About this Course
What you will learn
Employ artificial intelligence techniques to test hypothesis in Python
Apply a machine learning model combining Numpy, Pandas, and Scikit-Learn
Skills you will gain
- Data Science
- Machine Learning
- Statistical Hypothesis Testing
- medical data
Syllabus - What you will learn from this course
Introduction to Python Programming for Hypothesis Testing
Creating a Hypothesis: Numpy, Pandas, and Scikit-Learn
Scikit-Learn Revisited: ML for Hypothesis Testing
Using Classification to Predict the Presence of Heart Disease
- 5 stars54.54%
- 4 stars15.15%
- 3 stars12.12%
- 2 stars9.09%
- 1 star9.09%
TOP REVIEWS FROM INTRODUCTION TO DATA SCIENCE AND SCIKIT-LEARN IN PYTHON
The topic is great, and the linkage and references provided are valuable.
The hands-on quiz should be supported with better instructions and descriptions regarding what to do.
meskipun agak eror dalam lab penugasan tapi alhamdulillah sudah bisa
It could be better if we can see where we did wrong after each assignment. Good and well-paced course otherwise
Good introduction. A bit too short for a 4-week course. The autograder is not very good, and some solutions are wrong.
About the AI for Scientific Research Specialization
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