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AI for Data & Business Analysts: Practical Enterprise AI Capability Building
A practical program that teaches Data and Business Analysts how to combine AI with analytics across the analytics lifecycle, from data preparation and exploration to visualization, insight generation, forecasting and executive storytelling. It uses AI as an analytical copilot while maintaining data quality, validation and responsible decision-making.
Six capabilities this program is built to give every data and business analyst working with AI.
Use AI to clean, transform and profile messy business datasets before analysis begins.
Generate, explain, debug and optimize SQL, Python and DAX using natural language.
Create AI-assisted Power BI or Tableau dashboards with natural-language exploration.
Investigate trends, anomalies and performance drivers to move from what happened to why.
Build scenario and forecasting models and stress-test the assumptions behind them.
Turn analysis into executive-ready narratives and validated, decision-ready recommendations.
How the program moves you from AI basics to a workflow you can defend in front of stakeholders.
Instructor-led sessions ground AI awareness in real analyst workflows.
Build reusable prompts grounded in your business definitions, metrics and data structures.
Practice AI-assisted data cleaning, SQL, Python, DAX and dashboard building.
Test AI outputs for hallucinations, wrong assumptions and misleading conclusions.
Solve realistic sales, finance, customer and operations problems as an analyst.
Design and present an AI-Augmented Analyst solution tied to a real business KPI.
Instructor-led sessions ground AI awareness in real analyst workflows.
Build reusable prompts grounded in your business definitions, metrics and data structures.
Practice AI-assisted data cleaning, SQL, Python, DAX and dashboard building.
Test AI outputs for hallucinations, wrong assumptions and misleading conclusions.
Solve realistic sales, finance, customer and operations problems as an analyst.
Design and present an AI-Augmented Analyst solution tied to a real business KPI.
The real analyst scenarios you'll practice, pulled directly from the program's applied curriculum.
Redesign a real analytical workflow using AI and present the current-state problem, AI opportunity, proposed workflow, human checkpoints and expected productivity impact.
The program focuses on solving analytical problems with the right capability, not on memorizing a list of tools.
ChatGPT Enterprise · Microsoft 365 Copilot · Gemini · Claude
Power BI + Copilot · Tableau + AI · Microsoft Fabric · Excel + Copilot
SQL · Python · Jupyter · Databricks · Snowflake · BigQuery
Power Query · Fabric · Alteryx · Databricks
Python · R · Azure ML · Databricks · Vertex AI
Excel · Teams + Copilot · Notion AI · SharePoint · NotebookLM · Power Automate · UiPath · Zapier · Make
A preview of the ten modules inside the program. See the full breakdown in the detailed curriculum.
AI, Generative AI, ML, AI agents and how AI is changing the analyst role.
Structured prompt frameworks for analysis, reporting, SQL and executive summaries.
Business context, metric definitions, data dictionaries, schemas and analytical constraints.
Hallucinations, data privacy, bias, validation, governance, explainability and security.
Data cleaning, transformation, missing values, duplicates, outliers, exploratory analysis and pattern detection.
Natural language to SQL, query explanation, debugging, optimization; Python and DAX assistance.
Data modeling, dashboard design, visualization selection, report summaries and natural-language exploration.
Trend, variance, segmentation, correlation, driver analysis, anomaly investigation and hypothesis generation.
Forecasting, trend analysis, scenarios, sensitivity analysis and predictive analytics with validation.
Insight narratives, executive summaries, recommendations; redesign the analyst workflow around AI copilots.
AI applications across talent acquisition, employee experience, policy drafting, workforce analytics, and responsible HR governance.
Design customized learning pathways, instructional assets, skills taxonomies, and adaptive learning experiences with AI.
Enhance financial analysis, variance commentary, forecasting models, policy compliance, and audit preparation using AI.
Accelerate account research, proposal drafting, RFP responses, discovery prep, and customer intelligence.
Scale high-quality content strategy, campaign personalization, audience research, creative exploration, and brand consistency.
Optimize vendor evaluations, SOP creation, root cause analysis, process documentation, and operational reporting.
Optimize project planning, risk tracking, stakeholder communication, and resource allocation using AI.
Elevate customer support with AI-driven inquiry resolution, sentiment analysis, and automated knowledge retrieval.
Accelerate code generation, architecture design, technical documentation, and code review processes with AI.
Enhance product strategy, user research synthesis, roadmap planning, and feature prioritization using AI.
Streamline contract review, regulatory research, policy drafting, and compliance monitoring with AI.
Improve vendor evaluation, contract analysis, spend analytics, and supply chain risk assessment with AI.
Generic AI training is failing the enterprise. A finance director, an HR manager, and a software engineer require fundamentally different AI capabilities. Discover why role-based enablement—anchored in actual workflows, decisions, and domain expertise—is the only sustainable path to enterprise AI value.
Most enterprises conflate AI literacy (knowing what AI is) with AI capability (knowing how to use AI effectively in your role). This confusion leads to generic training that fails to change behaviour or drive ROI. Discover how to build true AI capability.
Enterprise AI initiatives are failing at scale not due to technological flaws, but because traditional IT training models are entirely unsuited for probabilistic AI tools. Discover why a human-centred capability building approach is essential.
Every module, topic, activity and practical application, laid out in the detailed curriculum.