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Our Courses
Create a Big Number KPI Dashboard in Tableau Public
Tableau is widely recognized as one of the premier data visualization software programs.
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Course by
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Self Paced
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2 hours
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English
Information Visualization: Programming with D3.js
In this course you will learn how to use D3.js to create powerful visualizations for web. Learning D3.js will enable you to create many different types of visualization and to visualize many different data types. It will give you the freedom to create something as simple as a bar chart as well your own new revolutionary technique.
In this course we will cover the basics of creating visualizations with D3 as well as how to deal with tabular data, geography and networks. By the end of this course you will be able to:
- Create bar and line charts
- Create choropleth and symbol maps
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Course by
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Self Paced
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18 hours
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English
Sales Reporting with HubSpot
In this course, you will use your business data and identify key metrics in order to report on sales with HubSpot’s dashboards. First, you will learn how to operate a data-driven business and how to audit, clean, and organize your data within HubSpot’s CRM. You will then learn to identify the key metrics used to analyze your data on sales and customer service success, within the stages of the Inbound Methodology. This will cover types of testing, using the Sales Hub tools, and reporting in each stage of the methodology.
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Course by
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Self Paced
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English
Visualizing Data in the Tidyverse
Data visualization is a critical part of any data science project. Once data have been imported and wrangled into place, visualizing your data can help you get a handle on what’s going on in the data set. Similarly, once you’ve completed your analysis and are ready to present your findings, data visualizations are a highly effective way to communicate your results to others.
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Course by
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Self Paced
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17 hours
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English
Getting Started with Tidyverse
In this project, you will learn about Tidyverse, a system of packages for data manipulation, exploration and visualization in the R programming language.
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Course by
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Self Paced
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4 hours
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English
Data Analysis and Visualization with Python
In this course, you will learn how to read and write data from and to a file. You will also examine how to manipulate and analyze the data using lists, tuples, dictionaries, sets, and the pandas and Matplot libraries. As a developer, it's important to understand how to deal with issues that could cause an application to crash. You will learn how to implement exceptions to handle these issues. You do not need a programming or computer science background to learn the material in this course. This course is open to anyone who is interested in learning how to code and write programs in Python.
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Course by
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Self Paced
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16 hours
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English
Deploying Machine Learning Models
In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g.
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Course by
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Self Paced
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11 hours
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English
From Excel to Power BI
Are you using Excel to manage, analyze, and visualize your data? Would you like to do more? Perhaps you've considered Power BI as an alternative, but have been intimidated by the idea of working in an advanced environment. The fact is, many of the same tools and mechanisms exist across both these Microsoft products. This means Excel users are actually uniquely positioned to transition to data modeling and visualization in Power BI! Using methods that will feel familiar, you can learn to use Power BI to make data-driven business decisions using large volumes of data.
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Course by
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Self Paced
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3 hours
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English
R Programming and Tidyverse Capstone Project
In this third and final course of the "Expressway to Data Science: R Programming and Tidyverse" specialization you will reinforce and display your R and tidyverse skills by completing an analysis of COVID-19 data! Here is a chance to apply your skills to a real-world dataset that has effected all of us. Throughout the capstone, you will import COVID-19 data; clean, tidy, and join datasets; and develop visualizations. You will also provide some analysis and interpretation to your results, preparing you for your journey into data science.
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Course by
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Self Paced
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10 hours
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English
Getting Started with Data Warehousing and BI Analytics
Kickstart your Data Warehousing and Business Intelligence (BI) Analytics journey with this self-paced course. You will learn how to design, deploy, load, manage, and query data warehouses and data marts. You will also work with BI tools to analyze data in these repositories.
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Course by
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Self Paced
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17 hours
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English
Data Visualization with Plotly Express
Welcome to this project-based course on Data Visualization with Plotly Express. In this project, you will create quick and interactive data visualizations with Plotly Express: a high-level data visualization library in Python inspired by Seaborn and ggplot2. You will explore the various features of the in-built Gapminder dataset, and produce interactive, publication-quality graphs to augment analysis. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser.
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Course by
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Self Paced
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3 hours
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English
Data-Driven Process Improvement
By the end of this course, learners are empowered to implement data-driven process improvement objectives at their organization. The course covers: the business case for IoT (Internet of Things), the strategic importance of aligning operations and performance goals, best practices for collecting data, and facilitating a process mapping activity to visualize and analyze a process’s flow of materials and information.
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Course by
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Self Paced
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9 hours
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English
COVID19 Data Visualization Using Python
By the end of this project, you will learn How you can use data visualization techniques to answer to some analytical questions.
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Course by
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Self Paced
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2 hours
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English
Design and Build a Data Warehouse for Business Intelligence Implementation
The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization.
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Course by
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Self Paced
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45 hours
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English
Explainable AI: Scene Classification and GradCam Visualization
In this 2 hour long hands-on project, we will train a deep learning model to predict the type of scenery in images. In addition, we are going to use a technique known as Grad-Cam to help explain how AI models think. This project could be practically used for detecting the type of scenery from the satellite images.
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Course by
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Self Paced
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3 hours
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English
Introduction to Statistics in Python
In this project, learners will get a refresher of introductory statistics, learn about different python libraries that can be used to run statistical analysis, and create visualizations to represent the results.
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Course by
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Self Paced
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2 hours
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English
Master the Art of Data Visualization With Tableau Public
Tableau is widely recognized as one of the premier data visualization software programs.
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Course by
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Self Paced
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3 hours
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English
Data Visualization using dplyr and ggplot2 in R
Welcome to this project-based course Data Visualization using ggplot2 and dplyr in R. In this project, you will learn how to manipulate data with the dplyr package and create beautiful plots using the ggplot2 package in R. By the end of this 2-hour long project, you will understand how to use different dplyr verbs such as the select verb, filter verb, arrange verb, mutate verb, summarize verb, and the group_by verb to manipulate the gapminder dataset.
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Course by
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Self Paced
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3 hours
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English
Information Visualization: Foundations
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis.
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Course by
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Self Paced
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12 hours
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English
Data Visualization with Power BI: Storytelling with Data
Data is the new lifeblood of business and visualization has emerged as the common language.
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Course by
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Self Paced
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2 hours
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English
Fundamentals of Data Visualization
Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives.
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Course by
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Self Paced
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15 hours
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English
Plots Creation using Matplotlib Python
By the end of this project, you will be able to add the data in the CSV file to Pandas data frame, plot the graph, and set marker type and color. You will also be able to apply labels, change font size, add grid lines and legends. Finally, you will be able to create the boxplot and save the graph as an image using the matplotlib and seaborn libraries, which are the most important libraries in python that are used for Data Visualization. You can create bar-plots, scatter-plots, histograms, and a lot more with them. This guided project is for people in the field of data and data analysis.
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Course by
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Self Paced
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3 hours
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English
Geospatial Data Visualization using Python and Folium
In this project, we are going to learn how to process and analyze geospatial data.
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Course by
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Self Paced
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3 hours
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English
Working with BigQuery
In this guided project, you will learn about working with Google's BigQuery which is allows easily work with and query massive datasets without worrying about time wasting or having the right infrastructure to analyze that data quickly. You will learn how to use big query to collect your data, query it with SQL and even do quick visualizations on it.
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Course by
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Self Paced
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2 hours
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English
AWS: Data Analysis and Visualization
AWS: Data Analysis and Visualization Course is the fourth course of AWS Certified Data Analytics Speciality Specialization. This course teaches Data Analysis and Visualization by exploring AWS Services such as Athena, Kinesis, QuickSight, Redshift and Kibana. The course is divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 4:00 Hours Video lectures that provide both Theory and Hands -On knowledge.
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Course by
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Self Paced
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8 hours
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English