Data Visualization with Python
Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. It is a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this course you will learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.
About This Course
«A picture is worth a thousand words». We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large data sets. Data visualization plays an essential role in the representation of both small and large scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.
The main goal of this course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, seaborn, and Folium.
Course Syllabus
Module 1 – Introduction to Visualization Tools
Introduction to Data Visualization
Introduction to Matplotlib
Basic Plotting with Matplotlib
Dataset on Immigration to Canada
Line Plots
Module 2 – Basic Visualization Tools
Area Plots
Histograms
Bar Charts
Module 3 – Specialized Visualization Tools
Pie Charts
Box Plots
Scatter Plots
Bubble Plots
Module 4 – Advanced Visualization Tools
Waffle Charts
Word Clouds
Seaborn and Regression Plots
Module 5 – Creating Maps and Visualizing Geospatial Data
Introduction to Folium
Maps with Markers
Choropleth Maps
You May Like
Autoencoders and Regularization – Learn and Implement
In this course, you'll explore how Autoencoders compress, denoise, and derive valuable features from data. You'll also delve into regularization to curb overfitting and...
Learn Recurrent Neural Networks Hands-On
In the real world, data often comes in sequences: text, speech, time-series data, and more. RNNs are the key to understanding and working with...
Convolutional Neural Networks with PyTorch
In this course you will gain practical skills to tackle real-world image analysis and computer vision challenges using PyTorch. Uncover the power of Convolutional...
Serverless Computing using Cloud Functions – Developer I
This course is designed to teach you serverless computing essentials which include how to develop serverless applications composed of loosely-coupled, microservice-like functions. You will...
Classification with PyTorch
Designed for students and enthusiasts, this course equips you with the knowledge and practical skills to build powerful and accurate classification models using PyTorch....
Course Features
- Lectures 0
- Quizzes 0
- Duration 10 horas
- Skill level Principiante
- Language English
- Students 0
- Assessments Yes