Visualization for Data Science Training

Live Online & Classroom Enterprise Training

Visualization for Data Science focuses on transforming complex data into intuitive visual representations using tools like Matplotlib, Seaborn, and D3.js. It enhances data interpretation, pattern recognition, and decision-making through effective graphical analysis.

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What is Visualization for Data Science Training about?

This course explores the essential techniques and principles of data visualization specifically tailored for data science. It covers various visualization libraries and tools, including Matplotlib, Seaborn, Plotly, and Tableau, to create effective and insightful visual representations of data. The course also emphasizes storytelling with data, best practices in visualization, and the role of visual analytics in data-driven decision-making.

What are the objectives of Visualization for Data Science Training ?

Understand the principles and importance of data visualization in data science
Choose the right visualization techniques for different data types
Create static and interactive visualizations using Python (Matplotlib, Seaborn, Plotly)
Use Tableau for advanced business intelligence visualization
Implement best practices for effective data storytelling
Develop dashboards and reports for data-driven insights

Who is Visualization for Data Science Training for?

Data scientists and analysts
Business intelligence professionals
Researchers and students working with data
Anyone interested in advanced data visualization techniques

What are the prerequisites for Visualization for Data Science Training?

Basic knowledge of Python or R

Available Training Modes

Live Online Training

3 Days

Self-Paced Training

30 Hours

Course Outline Expand All

Expand All

Module 1: Fundamentals of Data Visualization

Importance of visualization in data science

Types of data and suitable visualization techniques

Overview of visualization tools and libraries

Module 2: Visualization with Matplotlib and Seaborn

Creating basic plots: line, bar, scatter, and histogram

Customizing visualizations: colors, labels, and annotations

Statistical data visualization with Seaborn

Module 3: Interactive Visualizations with Plotly

Introduction to Plotly for interactive charts

Creating interactive line, bar, and scatter plots

Enhancing interactivity with tooltips and animations

Module 4: Business Intelligence Visualization with Tableau

Connecting to datasets in Tableau

Creating dashboards and advanced visualizations

Sharing and publishing Tableau reports

Module 5: Data Storytelling and Dashboard Design

Principles of effective data storytelling

Designing interactive and user-friendly dashboards

Case studies on real-world data visualization projects

Module 6: Hands-on Project and Final Assessment

Implementing a complete data visualization project

Developing an interactive dashboard for data insights

Final presentation and feedback session

Who is the instructor for this training?

The trainer for this Visualization for Data Science Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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