- Review Excel, statistics, financial analysis, visualization, reporting, SQL, Python, and advanced analytics curriculum for accuracy, relevance, and appropriate depth.
- Recommend curriculum updates based on current analyst responsibilities, modern BI and data tools, and AI-assisted analytics practices.
- Align learning outcomes with entry-level and early-career analyst expectations.
- Write original learning content and use AI to develop learning aids and resources.
- Develop and review content on using AI to support analytics workflows while preserving analytical reasoning and human judgment.
- Create explainers for using AI to troubleshoot formulas, support analysis, draft summaries and chart explanations, and explore visualization approaches.
- Design AI-enabled exercises that reinforce core analytics skills and teach responsible AI use.
- Write or revise lessons, exercises, projects, case studies, quizzes, and assessments using realistic business scenarios and datasets.
- Review spreadsheet activities, SQL queries, Python scripts, visualizations, and AI-assisted workflows for technical accuracy and pedagogical effectiveness.
- Develop reporting activities that help learners interpret KPIs and communicate insights to operational and non-technical stakeholders.
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