Data Visualization in AI-Driven BI
( 25 Modules )

Module #1
Introduction to AI-Driven BI and Data Visualization
Overview of AI-driven Business Intelligence, importance of data visualization, and course objectives

Module #2
Fundamentals of Data Visualization
Basic principles of data visualization, human perception, and visual encoding

Module #3
Data Preparation for Visualization
Data cleaning, preprocessing, and transformation for effective visualization

Module #4
Data Visualization Tools and Technologies
Overview of popular data visualization tools, libraries, and frameworks (e.g., Tableau, Power BI, D3.js, Matplotlib)

Module #5
Exploratory Data Analysis (EDA) with Visualization
Using visualization to explore and understand datasets, including summarization and aggregation

Module #6
Visualization Best Practices
Effective visualization design, color theory, and avoiding visual pitfalls

Module #7
Introduction to AI and Machine Learning in BI
Overview of AI and ML concepts, and their applications in Business Intelligence

Module #8
AI-Driven Data Preparation and Cleaning
Using AI and ML for automated data preprocessing, cleaning, and transformation

Module #9
AI-Powered Data Visualization
Using AI and ML to generate insights and recommendations for data visualization

Module #10
Predictive Analytics with Data Visualization
Using data visualization to communicate predictive models and results

Module #11
Deep Learning for Computer Vision in BI
Applying deep learning techniques to analyze and visualize image and video data in BI

Module #12
Natural Language Processing (NLP) for Text Visualization
Using NLP to analyze and visualize text data in BI

Module #13
Interactive and Dynamic Visualization
Creating interactive and dynamic visualizations using tools like Tableau, Power BI, or D3.js

Module #14
Big Data Visualization
Visualizing large-scale data using distributed computing and NoSQL databases

Module #15
Real-Time Data Visualization
Visualizing real-time data streams using tools like Apache Kafka, Apache Flink, or Apache Storm

Module #16
Geospatial Data Visualization
Visualizing geospatial data using mapping libraries like Leaflet, Mapbox, or Google Maps

Module #17
Storyboarding and Narrative in Data Visualization
Creating compelling stories with data visualization, including design principles and best practices

Module #18
Evaluation and Refinement of Data Visualization
Assessing and refining data visualizations for effectiveness and usability

Module #19
Ethics and Fairness in AI-Driven Data Visualization
Addressing biases and ethical considerations in AI-driven data visualization

Module #20
Case Studies in AI-Driven Data Visualization
Real-world examples and case studies of AI-driven data visualization in various industries

Module #21
Designing Dashboards and Reports with AI-Driven Insights
Creating effective dashboards and reports that incorporate AI-driven insights and visualizations

Module #22
Deploying and Scaling AI-Driven Data Visualization Solutions
Deploying and scaling AI-driven data visualization solutions in production environments

Module #23
Hands-on Project:Building an AI-Driven Data Visualization Solution
Guided hands-on project to build an AI-driven data visualization solution using tools and techniques learned throughout the course

Module #24
Advanced Topics in AI-Driven Data Visualization
Exploring advanced topics and emerging trends in AI-driven data visualization, including Explainable AI and Human-in-the-Loop systems

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Data Visualization in AI-Driven BI career

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Data Visualization in AI-Driven BI ( 25 Modules )

Data Visualization in AI-Driven BI
( 25 Modules )