The ‘Interactive Course: Use Python Dashboards with Plotly & Dash’ course will teach you about about basic data visualization with Plotly, including scatter plots, line charts, bar charts, bubble charts, box plots, histograms, distribution plots, heat maps, and more.

This course will teach you everything you need to know to use Python to create interactive dashboard’s with Plotly’s new Dash library. By taking this course you will be learning the bleeding edge of data visualization technology with Python and gain a valuable new skill.  The course is usually available for INR 2,799 on Udemy but students can click on the link and get the ‘Interactive Course: Use Python Dashboards with Plotly & Dash’ for INR 449.

Who all can opt for this course?

  • Python developers
  • Anyone interested in learning how to build interactive dashboards and visualisations

Course Highlights

Key HighlightsDetails
Registration LinkApply Now!
PriceINR 499 (INR 2,79985% off
Duration09 Hours
Student Enrollment44,683 students
InstructorJose Portilla
Topics CoveredPython, Plotly basics, Dashboard components, Callbacks with state
Course LevelIntermediate
Total Student Reviews8,205

Learning Outcomes

  • Learn how to make plots using Plotly, including Heat Maps, Scatter Plots, Bar Charts, and more!
  • Use Plotly’s Dash library to create layouts
  • Create interactive elements with Plotly by using Dash
  • See how to use a dashboard to connect various inputs and outputs
  • Live interactive graphs can be updated with clicks, hoverovers, and other actions
  • Link the interactive dashboard to the streaming information’s live updating data
  • See how to use App Authorization to safeguard your interactive dashboards
  • Use services like Heroku to publish interactive dashboards online

Course Content

S.No.Module (Duration)Topics
1.Course Introduction (32 minutes)Course Overview
Course FAQ
Overview of Notes and Guidebook
Installation Overview
2.Introduction to Data Basics (46 minutes)Plotly and Dash Overview
NumPy Crash Course
Pandas Crash Course
Exercise: NumPy/Pandas Practice
NumPy/Pandas Practice Exercise Solution
3.Plotly Basics (02 hours 41 minutes)Plotly Basics Overview
Scatter Plots
Line Charts
Line Charts Part Two
Line Charts Exercise
Line Charts Exercise – Solution Code Along
Bar Charts
Bar Charts Exercise
Bar Charts Exercise – Solution
Bubble Plots
Bubble Charts Exercise
Bubble Charts Exercise Solution
Box Plots
Box Plots Exercise
Box Plots Exercise Solution
Histograms Exercise
Histograms Exercise Solution
DistPlots Exercise
DistPlots Exercise Solution
Heatmaps Exercise
Heatmaps Exercise Solution
4.Dash Basics – Layout (40 minutes)Introduction to Dash Basics
Dash Layouts – Part One
Dash Layouts – Part Two – Styling
Converting Simple Plotly Plot to Dashboard with Dash
5.DashBoard Exercise (08 minutes)Exercise: Create a Simple Dashboard
Simple Dashboard Exercise Solution
6.DashBoard Components (32 minutes)Dash Components
HTML Components
Core Components
Markdown with Dash
Using Help() with Dash
7.Interactive Components (01 hour 22 minutes)Single Callbacks for Interactivity
Dash Callbacks for Graphs
Multiple Inputs
Multiple Outputs
Exercise: Interactive Components
Interactive Components Exercise Solution
8.Callbacks with State (11 minutes)Controlling Callbacks with Dash State
9.Interacting with Visualizations (01 hour 17 minutes)Hover Over Data
Click Data
Selection Data
Updating Graphs on Interactions
Updating Graphs on Interactions Part 2
Updating Graphs on Interactions – Part Three
10.Code Along Milestone Project (40 minutes)Code Along Milestone Project Overview
Milestone Project Part One – Imports and Graph Setup
Milestone Project Part Two – Input Box and Basic Callback
Milestone Project Part Three – Reading Data with Pandas Datareader
Milestone Project Part Four – Adding DatePickers for Choosing Dates
Milestone Project Part Five – Adding in Dash State
Milestone Project Part Six – Multiple Stock Option Dropdown
11.Live Updating (23 minutes)Layout Updating
Simple Live Update Example
12.Deployment (24 minutes)App Authorization
Deploying App to Heroku

Resources Required

  • Understanding of Python basics
  • Computer with access to the internet

Featured Review

Fábio Demo da Rosa (4/5) : An excellent course, my view is based on the fact that I already know Python and Pandas, so I even had an introduction to Numpy in the crash course. The only problem so far was on Plotly Basics, when creating the Distribution Plot (Distplot), I have encountered some errors that I was only able to solve by reading the comments from Q&A. To solve this problem and to avoid problems to newcomers to this course, I suggest to update the requirements.txt with “Scipy==1.0.1” and to set a warning before the video about Distplot starts, specifying the updated libraries including “scipy” on top of them (apparently Scipy needs to run before plotly in this case).


  • Mirjana Starcevic (5/5) : Excellent training for those who want to learn building Dash applications from scratch.
  • Jeremy Raven (5/5) : Ive listened to hundreds of tutorials and Jose is one of the best.
  • Duke Coulbanis (5/5) : I remain extremely happy I signed up, and have found value in the course already! This course also inspired me to purchase one of José’s data visualisation courses, which I am super-excited to start now that I’ve finished this one.
  • David Brantley (5/5) : All in all, this is one of the best courses I’ve taken here.


  • Jacob Mapson (2/5) : A lot of the libraries used in the course are outdated versions.
  • Gokul Gupta (1/5) : Worst instructor: Asked question and did follow up so many times, But didn’t get the response.
  • Prasanna Venkataraman (1/5) : When I go to, Iam not able to see the Repo for this Udemy Course.
  • Jacob Mapson (2/5) : The lesson video for one of the sections is missing core dependencies to allow it to work.

About the Author

The instructor of this course is Jose Portilla who is a Head of Data Science at Pierian Training. With 4.6 Instructor Rating and 1,022,369 Reviews on Udemy, he/she offers 60 Courses and has taught 3,290,752 Students so far.

  • Jose Marcial Portilla holds degrees in mechanical engineering from Santa Clara University (BS and MS), and he has years of experience working as a qualified instructor and trainer for Python programming, machine learning, and data science
  • He has written articles and received patents in a number of disciplines, including data science, materials science, and microfluidics
  • He has acquired a set of abilities for data analysis throughout the course of his career, and he wants to combine both his teaching and data science knowledge to educate others the power of programming, how to analyse data, and how to display the data in attractive visualisations
  • He currently serves as the Head of Data Science for Pierian Training, where he trains people at prestigious organisations like General Electric, Cigna, The New York Times, Credit Suisse, McKinsey, and others in data science and python programming on-site
  • Please click the website link to learn more about the available training options

Comparison Table

ParametersInteractive Python Dashboards with Plotly and DashREST APIs with Flask and Python in 2023Spark and Python for Big Data with PySpark
OffersINR 455 (INR 2,799) 85% offINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% off
Duration9.5 hours12 hours10.5 hours
Rating4.6 /54.6 /54.5 /5
Student Enrollments44,681110,492115,326
InstructorsJose PortillaJose SalvatierraJose Portilla
Register HereApply Now!Apply Now!Apply Now!

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