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Online Course

Data Analysis with Python

IBM via Coursera

(1)
  • Provider Coursera
  • Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Effort 2 hours a week
  • Duration 7 weeks long
  • Learn more about MOOCs

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Overview

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.

Syllabus

Importing Datasets

Data Wrangling

Exploratory Data Analysis

Model Development

Model Evaluation

Final Assignment

IBM Digital Badge

Taught by

Joseph Santarcangelo

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Review for Coursera's Data Analysis with Python Based on 1 reviews

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Kurp K
Kurp completed this course, spending 5 hours a week on it and found the course difficulty to be medium.
It takes a few hours to complete. The course provides some basic lessons on working with data in Python. I think there are some better introductions available.
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