2024 Data Visualization in Tableau & Python (2 Courses in 1)

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What you’ll learn

  • Understanding the principles of data visualization
  • Proficiency in Tableau
  • Data preparation and manipulation
  • Creating static visualizations with Matplotlib
  • Exploratory data analysis with Seaborn
  • Designing interactive visualizations
  • Visual storytelling and communication
  • Critically evaluating visualizations
  • Project-based learning

Requirements

  • Proficiency in Python: Since Matplotlib and Seaborn are Python libraries, a solid understanding of Python programming is necessary. Students should have a good grasp of Python syntax, variables, data structures (such as lists, dictionaries, and arrays), control flow (loops and conditionals), functions, and file I/O operations.
  • Knowledge of data manipulation: It is beneficial to have some experience with data manipulation and cleaning techniques, such as loading data from different file formats (CSV, Excel, etc.), handling missing values, and performing basic data transformations (filtering, grouping, merging, etc.). This can be achieved through libraries like pandas.

Description

Welcome to the comprehensive course on “Data Visualization in Tableau & Python with Matplotlib and Seaborn.” In this course, you will learn how to create captivating and informative visualizations using two powerful tools: Tableau and Python libraries, Matplotlib and Seaborn. Whether you’re a beginner or an experienced data analyst, this course will provide you with the necessary skills to effectively visualize data and communicate insights.

Course Features:

  1. Practical Approach: This course focuses on hands-on learning through practical exercises and real-world examples. You will work on various datasets, allowing you to apply the concepts and techniques learned directly to relevant scenarios.
  2. Comprehensive Coverage: The course covers both Tableau and Python libraries, providing you with a well-rounded understanding of data visualization. You will learn the fundamentals of each tool and progressively advance to more advanced techniques, ensuring a thorough grasp of the subject matter.
  3. Tableau Proficiency: You will gain proficiency in Tableau, a widely used data visualization tool. Starting with the basics, you will learn to create interactive dashboards, design captivating visualizations, and explore advanced functionalities for data analysis and storytelling.
  4. Python Visualization: Explore the capabilities of Python libraries, Matplotlib and Seaborn, for data visualization. You will learn to create static visualizations, customize plots, handle data manipulation, and leverage advanced statistical visualization techniques.
  5. Data Preparation and Cleaning: An essential aspect of data visualization is data preparation. This course covers techniques for data cleaning, manipulation, and transformation to ensure high-quality data for visualization purposes.
  6. Storytelling and Communication: Learn how to tell compelling stories through data visualization. Discover effective techniques for communicating insights visually and creating impactful narratives that engage and persuade your audience.
  7. Real-World Projects: Apply your skills to real-world projects and datasets, allowing you to showcase your abilities and build a portfolio of impressive visualizations. Gain practical experience and confidence in creating visualizations that address real-world challenges.
  8. Support and Resources: The course provides continuous support through Q&A sessions and a dedicated community forum, where you can interact with the instructor and fellow learners. Additional resources, such as code samples, datasets, and reference materials, will be provided to supplement your learning.
  9. Lifetime Access: Gain lifetime access to the course materials, including updates and new content. You can revisit the course anytime to refresh your knowledge, access new resources, and stay up-to-date with the latest advancements in data visualization.
  10. Certificate of Completion: Upon completing the course, you will receive a certificate of completion, validating your skills in data visualization with Tableau and Python libraries.

Whether you are a data analyst, data scientist, business professional, researcher, or anyone interested in mastering data visualization, this course will equip you with the necessary tools and knowledge to create impactful visualizations that drive insights and enhance data-driven decision-making.

Enroll now and embark on a journey to become a proficient data visualization expert with Tableau, Matplotlib, and Seaborn!

Who this course is for:

  • Data Analysts: Professionals working in data analysis roles who want to enhance their data visualization skills. They may already have experience with data manipulation and analysis and want to effectively communicate their findings through visually engaging charts and graphs.
  • Data Scientists: Individuals involved in data science who wish to add data visualization to their skill set. They understand the importance of effective data communication and want to leverage visualization techniques to convey complex insights to a non-technical audience.
  • Business Intelligence Professionals: Those responsible for collecting, analyzing, and presenting data to support decision-making in an organization. They seek to develop expertise in creating interactive dashboards and visualizations using Tableau, Matplotlib, and Seaborn.
  • Researchers and Academics: Researchers, scientists, and academics from various domains who deal with large datasets. They want to learn how to visually explore and communicate their data effectively, enabling them to present their findings in a visually compelling manner.
  • Data Enthusiasts: Individuals who have a strong interest in data visualization and want to explore the power of Tableau, Matplotlib, and Seaborn to create impactful visualizations. They may come from diverse backgrounds and want to acquire practical skills to showcase data in a meaningful way.
  • Students and Aspiring Data Professionals: Students pursuing degrees or courses in data-related fields, such as data science, analytics, or business intelligence. They aim to acquire a comprehensive understanding of data visualization techniques early in their careers to excel in their future roles.
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