Hands-on Data Visualization With Python
Hands-on Data Visualization With Python, available at $49.99, has an average rating of 3.8, with 55 lectures, 2 quizzes, based on 58 reviews, and has 855 subscribers.
You will learn about Understand the most important components for data visualization Build various types of graphs using Python libraries Learn how to use Plotly, Matplotlib and Seaborn Build tools that can help you obtain new insights, explain data or findings clearly Create interactive visualizations This course is ideal for individuals who are Data Scientists who want to take their skills to the next level or ML/AI engineers that want to put together new sources of information or datasets or Data Analysts looking to understand how to present findings or BI Professionals desiring to level up their skills and create interactive graphs or Any one interested in programming or computer science or Software engineers or programmers looking to expand their skill set It is particularly useful for Data Scientists who want to take their skills to the next level or ML/AI engineers that want to put together new sources of information or datasets or Data Analysts looking to understand how to present findings or BI Professionals desiring to level up their skills and create interactive graphs or Any one interested in programming or computer science or Software engineers or programmers looking to expand their skill set.
Enroll now: Hands-on Data Visualization With Python
Summary
Title: Hands-on Data Visualization With Python
Price: $49.99
Average Rating: 3.8
Number of Lectures: 55
Number of Quizzes: 2
Number of Published Lectures: 48
Number of Published Quizzes: 2
Number of Curriculum Items: 57
Number of Published Curriculum Objects: 50
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand the most important components for data visualization
- Build various types of graphs using Python libraries
- Learn how to use Plotly, Matplotlib and Seaborn
- Build tools that can help you obtain new insights, explain data or findings clearly
- Create interactive visualizations
Who Should Attend
- Data Scientists who want to take their skills to the next level
- ML/AI engineers that want to put together new sources of information or datasets
- Data Analysts looking to understand how to present findings
- BI Professionals desiring to level up their skills and create interactive graphs
- Any one interested in programming or computer science
- Software engineers or programmers looking to expand their skill set
Target Audiences
- Data Scientists who want to take their skills to the next level
- ML/AI engineers that want to put together new sources of information or datasets
- Data Analysts looking to understand how to present findings
- BI Professionals desiring to level up their skills and create interactive graphs
- Any one interested in programming or computer science
- Software engineers or programmers looking to expand their skill set
Understanding our data is key to our success, whether it’s for analytical purposes or for our model building in AI/ML/DS or related domains. Moreover, being able to construct a captivating visualization to clearly help explain findings to teams, managers, stakeholders and more is a valuable skill necessary for the world of DS.
And in a world where presenting data is the new big thing, data visualization tools are a must in your data science toolkit. By building visualizations in the most popular visualization libraries, we can gain a deeper level of understanding and create mesmerizing presentations.
Hands-on Data Visualization With Python will help present the core concepts and structure of working with Matplotlib, Seaborn, and Plotly so that you will be able to impress even the toughest managers with your ability to draw insights from data.
And once you’re done with the course you’ll be able to understand the most important components of data visualization after constructing various types of graphs, and solving practical challenges. This will allow you to stand out in your careers, build tools that can help you obtain new insights, explain data or findings clearly, create interactive visualizations and animations and more.
And if that´s not enough, you’ll also become more familiar with some of the most used visualization libraries, and help practice Python programming in the meantime!
So, are you ready to take your career onto the next level? Enroll now!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Welcome
Lecture 2: Get To Know Your Instructor
Chapter 2: Getting Started!
Lecture 1: Get The Files Here!
Lecture 2: Storytelling With Data
Lecture 3: Matplotlib vs Seaborn vs Plotly
Lecture 4: Google Colab
Lecture 5: Cleaning Data – Numerical vs Categorical
Lecture 6: Cleaning Data – NaNs
Lecture 7: Cleaning Data – Encoding
Lecture 8: Cleaning Data – Converting Data
Lecture 9: Pandas Tips
Lecture 10: Data Types
Lecture 11: Choosing Graph Types
Chapter 3: Matplotlib Visualizations
Lecture 1: Get The Files Here!
Lecture 2: Matplotlib – Getting Started
Lecture 3: Matplotlib – Basics
Lecture 4: Matplotlib – Bar Chart
Lecture 5: Matplotlib – Stacked Bar
Lecture 6: Matplotlib – Subplots
Lecture 7: Matplotlib – Single Subplot
Lecture 8: Matplotlib – Practical Challenge!
Lecture 9: Matplotlib – Practical Challenge Note
Lecture 10: Matplotlib – Practical Challenge Solution!
Chapter 4: Seaborn Visualizations
Lecture 1: Get The Files Here!
Lecture 2: Seaborn Introduction
Lecture 3: Seaborn Part 1
Lecture 4: Seaborn Part 2
Lecture 5: Seaborn Part 3
Lecture 6: Seaborn Part 4 – Lineplot Stocks
Lecture 7: Seaborn Part 5 – Relplot
Lecture 8: Seaborn – Challenge Intro
Lecture 9: Seaborn – Challenge Solution
Lecture 10: Seaborn – Practical Challenge Note
Lecture 11: Seaborn EXTRA – Save Figure
Chapter 5: Plotly
Lecture 1: Get The Files Here!
Lecture 2: Plotly Intro + Bar Graph
Lecture 3: Plotly Bar Customized
Lecture 4: Plotly Scatter
Lecture 5: Plotly – Stock Visualization Part 1
Lecture 6: Plotly – Stock Visualization Part 2
Lecture 7: Plotly 3D
Lecture 8: Plotly Challenge Intro
Lecture 9: Plotly Challenge Part 1
Lecture 10: Plotly – Practical Challenge Note
Lecture 11: Plotly Challenge Part 2
Chapter 6: Plotly Reward
Lecture 1: Plotly Animations
Chapter 7: Course Vault
Lecture 1: Notes
Chapter 8: Congratulations!! Don't forget your Prize 🙂
Lecture 1: Bonus: How To UNLOCK Top Salaries (Live Training)
Instructors
-
Jordan Sauchuk
Senior AI Advisor & Cybersecurity Engineer -
Ligency Team
Helping Data Scientists Succeed -
SuperDataScience Team
Helping Data Scientists Succeed
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 3 votes
- 3 stars: 5 votes
- 4 stars: 16 votes
- 5 stars: 33 votes
Frequently Asked Questions
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