Ementorhub

What you'll learn

Create impactful visualizations using Matplotlib and Seaborn to represent complex datasets effectively.

Build dynamic, interactive charts and dashboards with Plotly and IPyWidgets for enhanced data exploration.

Deploy interactive data visualization applications seamlessly with Streamlit to share analysis results.

Skills you'll gain

NumPy

Statistical Visualization

Data Visualization

Web Applications

Data Analysis

Matplotlib

Data Visualization Software

Pandas (Python Package)

Seaborn

Exploratory Data Analysis

Histogram

Scatter Plots

Dashboard

Interactive Data Visualization

Plotly

Box Plots

Jupyter

There are 4 modules in this course

By the end of this course, you’ll be able to: - Understand the importance of various visualization techniques. - Select appropriate chart types for visualizing diverse datasets. - Create professional-quality visuals with Matplotlib, Seaborn, and Plotly. - Develop interactive dashboards and visuals with Plotly and IPyWidgets. - Perform EDA on complex datasets and deploy the results using Streamlit. This course is ideal for learners with foundational knowledge of Python programming and a basic understanding of data manipulation. Familiarity with libraries such as Pandas or NumPy is recommended. Whether you're a data analyst, aspiring data scientist, or Python programmer looking to sharpen your data visualization skills, this course equips you with the tools to transform raw data into meaningful stories. Elevate your data analysis journey—enroll in Data Visualization and Exploratory Data Analysis with Python today!

Data Visualization with Seaborn

Interactive Data Visualization

Course Wrap-Up and Assessment