AI Data Analytics & Business Intelligence Specialist Certification Framework
An overview of the competencies, tools, curriculum, and pathways for aspiring AI Data Analytics & Business Intelligence Specialists.
🎯Learning Outcomes & AI Competencies
Learners who complete this certification will:
- Master Data Mining & Warehousing: Understand methods for extracting, storing, and managing large datasets.
- Apply Statistical Analysis with AI Augmentation: Use statistical methods combined with machine learning algorithms to identify trends, patterns, and insights.
- Leverage BI Platforms: Expertly utilize Power BI, Tableau, and AutoML features for data visualization and AI-enhanced analytics.
- Execute AI-Assisted Queries: Efficiently perform data queries using SQL integrated with AI-driven tools.
- Develop Predictive Dashboards: Build dynamic, interactive dashboards that incorporate predictive analytics for decision-making support.
- Utilize GPT-Based Analytics Tools: Employ GPT-powered analytics assistants to automate report generation and data summarization.
- Adopt Ethical Data Practices: Identify and address biases in data analysis, ensuring responsible and equitable use of AI tools.
🛠️Tools, Platforms & Software Mastery
Students will achieve proficiency in:
- BI Platforms: Power BI, Tableau, Google Looker
- AutoML Tools: Google AutoML, Azure AutoML
- Query Languages: SQL, enhanced by AI query assistants
- GPT-Based Analytics Assistants: ChatGPT for summarizing insights and automating reporting
- Data Warehousing: Microsoft Azure Data Warehouse, Amazon Redshift
- Programming & Analytics Tools: Python (Pandas, NumPy, Scikit-learn), Excel with advanced analytics add-ins
📚Course Structure & Instructional Sequence
Module 1: Data Analytics Foundations
Data collection, warehousing, and management fundamentals.
Module 2: AI-Augmented Statistical Analysis
Statistical methods with machine learning integration, trend detection, hypothesis testing.
Module 3: BI Platform Mastery
Advanced usage of Power BI and Tableau, leveraging embedded AI features.
Module 4: AI-Driven Database Querying
Enhanced SQL techniques, AI-assisted data retrieval and manipulation.
Module 5: Predictive Analytics Dashboards
Designing and building dashboards using predictive analytics and machine learning outputs.
Module 6: Capstone – AI Analytics Project
Practical project integrating all learned tools and methods, with a final presentation and ethical AI review.
📝Performance Assessments, Micro-Credentials & Capstone Projects
Data Analytics Challenges:
Real-world dataset analysis to identify actionable insights.
Micro-Credentials:
- "Data Warehousing Specialist"
- "AI Analytics Technician"
- "BI Visualization Expert"
Capstone Project Examples:
- AI-powered sales forecasting dashboard for retail businesses.
- Predictive tourism analytics platform to forecast visitor trends.
🔗Crosswalk to Florida CTE Courses & Certifications
CTE Course Alignment: Complements existing courses in Business Administration, IT, and Data Science pathways.
Industry Certification Alignment:
- Microsoft Certified: Data Analyst Associate
- Tableau Desktop Specialist
- Google Data Analytics Professional Certificate
🧑🎓Target Learner Levels
- High School: Grades 11-12 within CTE IT and Business clusters, providing foundational and specialized training.
- Adult Technical Centers: Professional upskilling programs for adults transitioning careers or enhancing skills.
- State Colleges: Included as College Credit Certificate within associate degrees in Business Analytics, Data Science, or Information Systems.
🧱Stackability & Articulation Pathways
- High School to College Credit: Articulates directly into associate degrees (Business Analytics, IT Data Science).
- College Credentials: Stackable into broader CCC programs, leading to an A.S. degree.
- Higher Education Transferability: Credits transferable toward a B.A.S. in Supervision and Management or B.S. in Data Analytics.
🤝Industry Partnerships & Alignment
- Employer Advisory Board: Includes local businesses, data-driven industries (finance, tourism, healthcare), and technology companies.
- Collaborations: Partnerships with Power BI, Tableau, Google Analytics, and AI-driven companies for software and project collaboration.
- Community-Integrated Projects: Participation in SmartTown.ai civic data dashboards, enhancing community decision-making through AI analytics.
- Internships and Experiential Learning: Structured internships with local analytics-focused employers and data-driven organizations.
- Industry-Driven Competitions: Employer-sponsored hackathons and analytics challenges, fostering practical skill application and innovation.