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Packt

Data Visualization in Tableau & Python (2 Courses in 1)

via Coursera

Overview

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In this comprehensive course, you’ll master the art of data visualization using both Tableau and Python. Whether you are a beginner or looking to expand your skills, you will learn to create powerful visualizations that help communicate complex data insights effectively. From fundamental concepts to advanced techniques, you will discover how to use different visualization tools to enhance your data storytelling capabilities.

You will first dive into Tableau, where you’ll learn to set up your environment, connect to data sources, and create various types of visualizations, including bar charts, line graphs, pie charts, scatter plots, heat maps, and more. You’ll also explore interactive features like dashboards to display data dynamically, engaging viewers in insightful ways.

Next, you will shift focus to Python’s data visualization libraries: Matplotlib and Seaborn. You will learn how to create static and interactive visualizations, including 3D plots, histograms, and violin plots, while mastering techniques to customize and refine your graphics for a clearer representation of your data.

This course is ideal for anyone looking to enhance their data visualization skills. Whether you’re a beginner or an intermediate learner, this course offers practical knowledge that can be applied in real-world data analysis projects. The only prerequisite is a basic understanding of data handling.

By the end of the course, you will be able to create and present compelling data visualizations using both Tableau and Python. You’ll gain proficiency in connecting to different data sources, visualizing data with a variety of charts, and constructing interactive dashboards. Whether for business insights or research analysis, you’ll be able to communicate your findings with confidence.

Syllabus 6

  1. Introduction 10 minutes

    In this module, we will introduce you to the concept of data visualization. You’ll learn its importance, various techniques, and how data visualization is applied to simplify and communicate complex data for effective decision-making.

  2. Tableau Fundamentals 50 minutes

    In this module, we will cover the foundational aspects of Tableau, from installation to connecting various data sources. You will also learn how to create and format basic visualizations to get started with your data analysis journey.

  3. Designing Interactive Visualizations with Tableau 1.5 hours

    In this module, we will dive into creating interactive visualizations using Tableau. You’ll learn how to join data, choose the right chart types, and create dashboards and maps that allow for deeper insights into your data.

  4. Project Based Learning to Create Interactive Dashboards in Tableau 55 minutes

    In this module, we will guide you through a hands-on project to build an interactive dashboard using Olympic athletes' data. This will help you apply the concepts learned in previous modules and see how Tableau can bring real-world data to life.

  5. Data Visualization Using Matplotlib in Python 50 minutes

    In this module, we will introduce Matplotlib, a powerful Python library for data visualization. You will learn how to create various charts and graphs, from simple line charts to more complex 3D visualizations, all using Python.

  6. Data Visualization Using Seaborn in Python 2 hours

    In this module, we will focus on Seaborn, a Python library built on Matplotlib, to create compelling statistical visualizations. You will learn to create diverse plots such as violin plots and heatmaps, enhancing your ability to analyze and present data effectively.

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • Covers niche tools that universities don't teach.
  • Self-paced: start any time.
  • A clear syllabus (6 parts) you can see before you start.
  • Hands-on: you build or practise, not just watch.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
  • Many courses are produced quickly from slides and screen recordings; read the reviews first.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Packt - Course Instructors

Packt is in Tier 5: mass-produced or unclear of our institution ranking (40/100). Thousands of courses turned out quickly; check reviews first.

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