What you'll learn
Importing Datasets
Data Wrangling
Exploratory Data Analysis
Model Development
Model Evaluation
Final Assignment
IBM Digital Badge
Description
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered:
1) Importing Datasets
2) Cleaning the Data
3) Data frame manipulation
4) Summarizing the Data
5) Building machine learning Regression models
6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments.
It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
Requirements
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are new to this field
Students willing to put in a couple hours to learn about Data Analysis with Python
Advanced students wanting to add another skill to their portfolio
Content Creator
Joseph Santarcangelo – Ph.D., Data Scientist at IBM – IBM Developer Skills Network
This course includes
Participation Confirmation/Certificate
Option for learning at your own pace
Videos and reading material about the course
Practice tests
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks