Data Analysis with Python Course Review

Online Course Highlights

IBM via Coursera
Learn for FREE, Up-gradable
25 hours of effort required
156,971+ already enrolled!
4.7 ★★★★★ (12,554 Ratings)
Skill Level: Beginner
Language: English

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.

LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate. Interested in cutting-edge development practices? Read our comprehensive tech course review here to see if this program matches your learning goals.

This course is part of multiple programs

This course can be applied to multiple Specializations or Professional Certificates programs.

Completing this course will count towards your learning in any of the following programs:

IBM Data Analyst Professional Certificate
IBM Data Science Professional Certificate
Applied Data Science Specialization

Syllabus

Week 1: Importing Datasets

Week 2: Data Wrangling

Week 3: Exploratory Data Analysis

Week 4: Model Development

Week 5: Model Evaluation

Week 6: Final Assignment

Week 7: IBM Digital Badge

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