Exploratory Data Analysis in Python

Name: Exploratory Data Analysis in Python
Brand: Careervira
Price: 71 USD
Availability: InStock
Rating: 5.0 (3 reviews)

DataCamp

(3)

Course Report

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Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

How can data be transformed into answers? Exploratory data analysis allows for you to examine datasets, answer queries, and visualize the results. This course will help you validate and clean data, visualize relationships between variables, answer questions, and use regression models for explaining and predicting. The course will cover data related to health and demographics, including the National Survey of Family Growth and the General Social Survey. These methods can be used in any field of science, engineering or business. Pandas is a Python library that lets you work with data. You can also find other core Python libraries, such as SciPy for regression or Matplotlib to visualize data. These skills and tools will enable you to make fascinating discoveries and work with real data.

Highlights

Pedagogy

Top 20 Percentile

Rating & Reviews

Top 30 Percentile

Parameters

Pedagogy

Acquire all major Python Programming for Data Science skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming for Data Science, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in Python Programming for Data Science, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming for Data Science.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Python Data Science Toolbox (Part 2)

What You Will Learn

Learn how to explore, visualize, and extract insights from data

You'll use Pandas, a powerful library for working with data, and other core Python libraries including NumPy and SciPy, StatsModels for regression, and Matplotlib for visualization

With these tools and skills, you will be prepared to work with real data, make discoveries, and present compelling results

Course Content

Expand all sections

Module 1: Read, clean, and validate

Module 2: Distributions

Module 3: Relationships

Module 4: Multivariate Thinking

Course Instructors

Allen Downey

Professor, Olin College

I am a Professor of Computer Science at Olin College in Needham MA, and the author of Think Python, Think Bayes, Think Stats and several other books related to computer science and data science. ...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%