IBM - Data Analysis with Python
4.6 /5- Offered byCoursera
Data Analysis with Python at Coursera Overview
Duration | 7 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Analysis with Python at Coursera Highlights
- Earn a Certificate of completion from IBM on successful course completion
- Instructor - Joseph Santarcangelo
- Learn how to analyze data using Python.
- Earn a Certificate of completion from IBM on successful course completion
Data Analysis with Python at Coursera Course details
- This course is designed for those who want to learn the basics of Python and apply it in the real world.
- If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
- This is one of the best courses to learn Data Analysis using Python on Coursera. This beginner-level course will take learners from the fundamentals of Python to exploring different types of data. Some of the major topics covered in this course include importing datasets, cleaning data, data frame manipulation, creating machine learning regression models, and building data pipelines
- In this course, you will be taught by Joseph Santarcangelo, a Data Scientist at IBM. The instructor delivers the course through a variety of methods including lectures, labs, and assignments. This 15-hours course requires no prior experience to get started
Data Analysis with Python at Coursera Curriculum
Week 1 - Importing Datasets
The Problem
Understanding the Data
Python Packages for Data Science
Importing and Exporting Data in Python
Getting Started Analyzing Data in Python
Accessing Databases with Python
Understanding the Data
Python Packages for Data Science
Importing and Exporting Data in Python
Getting Started Analyzing Data in Python
Importing Datasets
Week 2 - Data Wrangling
Pre-processing Data in Python
Dealing with Missing Values in Python
Data Formatting in Python
Data Normalization in Python
Binning in Python
Turning categorical variables into quantitative variables in Python
Model Development
Dealing with Missing Values in Python
Data Formatting in Python
Data Normalization in Python
Turning categorical variables into quantitative variables in Python
Data Wrangling
Week 3 - Exploratory Data Analysis
Exploratory Data Analysis
Descriptive Statistics
GroupBy in Python
Correlation
Correlation - Statistics
Analysis of Variance ANOVA
Descriptive Statistics
GroupBy in Python
Correlation
Correlation - Statistics
Exploratory Data Analysis
Week 4 - Model Development
Model Development
Linear Regression and Multiple Linear Regression
Model Evaluation using Visualization
Polynomial Regression and Pipelines
Measures for In-Sample Evaluation
Prediction and Decision Making
Model Development
Week 5 - Model Evaluation
Model Evaluation and Refinement
Overfitting, Underfitting and Model Selection
Ridge Regression
Grid Search
Quiz: Model Refinement
Week 6 - Final Assignment
Week 7 - IBM Digital Badge
Data Analysis with Python at Coursera Admission Process
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