Personalized Syllabus: Data Visualization (3-Month Plan)

Goal: Personal Growth Daily Commitment: 2 hours

Month 1: Week 1: Day 1:

Introduction to Data Visualization

Learn about the importance and benefits of data visualization.
Explore different types of data visualizations.
Understand the role of data visualization in decision-making.
Best source: "Data Visualization for Beginners" by Tableau - https://www.tableau.com/learn/articles/data-visualization

Day 2: 2. Data Types and Preprocessing

Learn about different data types (numerical, categorical, time-series, etc.) used in data visualization.
Understand how to preprocess and clean data for effective visualization.
Best source: "Data Preprocessing for Data Mining" by University of Illinois at Urbana-Champaign - https://www.coursera.org/learn/data-preprocessing

Day 3: 3. Principles of Visual Perception

Explore the principles of visual perception and how they influence data visualization design.
Learn about encoding data using visual cues (position, color, size, shape, etc.).
Best source: "The Science of Data Visualization" by University of Toronto - https://www.coursera.org/learn/dataviz

Day 4: 4. Choosing the Right Visualization

Understand which visualization types are suitable for various data scenarios.
Learn how to match the data characteristics with appropriate chart types (bar, line, scatter plots, etc.).
Best source: "Chart Choosing Guide" by Microsoft - https://docs.microsoft.com/en-us/power-bi/guided-learning/chartchoosingguide

Day 5: 5. Tools for Data Visualization

Explore popular data visualization tools (Tableau, Power BI, Python libraries, etc.).
Gain an overview of their features and capabilities.
Best source: "Data Visualization Tool Comparison" by The Data School - https://www.thedataschool.co.uk/anna-harrower/data-visualisation-tools/

Week 2: Day 6:

Understanding Color Theory

Learn about color perception and how to effectively use colors in visualizations.
Understand color schemes, harmonies, and palettes.
Best source: "Data Vis Color Guide" by Lisa Charlotte Rost - https://blog.datawrapper.de/beautifulcolors/

Day 7: 7. Exploratory Data Visualization

Learn techniques for visually exploring data to gain insights.
Understand how to identify patterns, outliers, and relationships using visualizations.
Best source: "Exploratory Data Analysis" by Johns Hopkins University - https://www.coursera.org/learn/exploratory-data-analysis

Day 8: 8. Storytelling with Data

Explore the art of telling compelling stories through visualizations.
Learn techniques to communicate insights effectively.
Best source: "Storytelling with Data" by Cole Nussbaumer Knaflic - https://storytellingwithdata.com/

Day 9: 9. Interactive Data Visualization

Understand the importance of interactivity in visualizations.
Learn how to create interactive charts and dashboards.
Best source: "Interactive Data Visualization" by D3.js - https://d3js.org/

Day 10: 10. Evaluation and Critique - Learn how to evaluate data visualizations for accuracy, effectiveness, and clarity. - Explore real-world examples and critique them. - Best source: "The Functional Art: An Introduction to Information Graphics and Visualization" by Alberto Cairo - https://www.albertocairo.com/thefunctionalart

Month 2: Week 3: Day 11:

Telling Time-Series Stories

Understand the visualization techniques for time-series data.
Learn how to visualize trends, seasonality, and anomalies in time-series data.
Best source: "Working with Time Series Data" by DataCamp - https://www.datacamp.com/courses/working-with-time-series-data-in-python

Day 12: 12. Geospatial Data Visualization - Explore techniques for visualizing data on maps. - Understand choropleth maps, point-based maps, and heatmaps. - Best source: "Introduction to GIS Mapping" by Esri - https://www.esri.com/training/catalog/57630435851d31e02a43b1cd/introduction-to-gis-mapping/

Day 13: 13. Network and Graph Visualization - Learn how to visualize relationships and networks using graph-based visualizations. - Understand network analysis concepts and their visualization. - Best source: "Graph Visualization" by University of Illinois at Urbana-Champaign - https://www.coursera.org/learn/graph-visualization

Day 14: 14. Big Data Visualization - Understand techniques for visualizing large-scale datasets. - Learn about data reduction, aggregation, and interactive approaches. - Best source: "Big Data Visualization" by D3.js - https://d3js.org/

Day 15: 15. Best Practices in Data Visualization - Learn about design principles, color accessibility, and data storytelling best practices. - Understand how to avoid common mistakes and create impactful visualizations. - Best source: "Data Visualization Best Practices" by Tableau - https://www.tableau.com/learn/articles/best-practices-visualization

Week 4: Day 16-20:

Project: Apply Data Visualization Skills

Select a dataset of interest and create meaningful visualizations.
Practice storytelling and interactivity in your visualizations.
Seek feedback and iterate on your work.

Month 3: Week 5-12: Day 21-60:

Personal Project: Data Visualization Portfolio

Identify a domain or topic of interest to focus your data visualization skills.
Explore various datasets, analyze information, and create a portfolio of visualizations.
Continuously seek feedback, improvements, and iterate on your portfolio.
Share your work on platforms like GitHub, Tableau Public, or personal blog.

Day 61-90: 18. Mentorship and Real-world Applications - Connect with experienced data visualization professionals or join online communities. - Learn from their expertise and seek advice for real-world scenarios. - Apply your visualization skills to practical projects or freelance opportunities.

Celebrate your accomplishments and continue to explore advanced topics in data visualization to further enhance your skills and expertise.

Note: The suggested sources are a starting point, but additional resources such as books, tutorials, or other online platforms can be used to further deepen your learning journey. Monitor your progress regularly and adjust the syllabus as needed to suit your needs. Enjoy your data visualization learning experience!

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