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    Managing a company in the food and beverage industry is a fascinating task. Food and beverage products are so deeply rooted in the culture of most countries that making and selling them is not only a matter of making and selling good and tasty products, but products that nurture people's body, soul, and heart. Given this, it's not difficult to see that the task quickly becomes complex. read more...

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Data Analysis with Python

$38.00

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! read more…

Level

Beginner

Rating

4 Stars

Duration

7 – 16 Hours

Language

English

Subtitle

Arabic, English, Korean

Feature

Captions, Certification, Exercises, On-Demand, Quizzes

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Categories: Business, Data & Analytics Tags: Data Analysis, Data Visualization (DataViz), Model Selection, Predictive Modelling, Python Programming
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Description

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

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