Module 01 · Data Foundations
Data Foundations & Business Metrics
Build the analytics mindset employers look for.
Start with the data lifecycle, analytics thinking, business KPIs, and the difference between descriptive, diagnostic, predictive, and prescriptive analytics. Build your first Excel dashboard and learn how analysts turn raw numbers into decisions.
Core Activities
- Data lifecycle management
- Analytics thinking: descriptive, diagnostic, predictive, prescriptive
- Business metrics and KPI definition
- Excel Pivot Tables, XLOOKUP, and dashboard basics
- Portfolio-ready business KPI dashboard
Labs & Tools
- Microsoft Excel
- Real sales and customer datasets
- Excel dashboards and Pivot Tables
- ChatGPT for KPI and insight drafting
ExcelKPIsDashboardsBusiness MetricsData Lifecycle
Module 02 · SQL & Data Preparation
SQL Querying & Data Preparation
Build the analyst's workbench. Master business querying.
Learn SQL from the ground up: SELECT statements, filters, joins, aggregations, CTEs, and window functions. Extract, transform, and prepare business data for analysis using real sales, customer, and operations datasets.
Core Activities
- SQL queries, filters, aggregations, and JOINs
- CTEs, window functions, and business query writing
- Data extraction, transformation, and loading
- Cleaning messy business data before analysis
- AI-assisted SQL debugging and query optimization
Labs & Tools
- SQL, MySQL, and PostgreSQL
- Real business database exercises
- SQL labs for business scenario analysis
- Claude and ChatGPT for query troubleshooting
SQLJOINsCTEsWindow FunctionsETL
Module 03 · Python & Statistics
Python, Statistics & Business Analysis
Think like an analyst. Test before you recommend.
Use Python, Pandas, NumPy, and Jupyter to clean, analyze, and automate data workflows. Learn descriptive statistics, probability, hypothesis testing, A/B testing, regression, and correlation analysis.
Core Activities
- Python for data manipulation and automation
- Descriptive statistics and probability
- Hypothesis testing and A/B testing
- Regression and correlation analysis
- Automated data cleaning notebooks
Labs & Tools
- Python and Jupyter Notebooks
- Pandas and NumPy
- Matplotlib and Seaborn
- Real customer and sales datasets
PythonPandasStatisticsA/B TestingRegression
Module 04 · Visualization & BI
Visualization & Business Intelligence
The core of the program: dashboards, storytelling, and executive-ready BI.
Build interactive dashboards in Power BI and Tableau using real business datasets. Learn chart selection, DAX basics, KPI communication, stakeholder storytelling, and AI-assisted dashboard design.
Core Activities
- Dashboard design and business storytelling
- Power BI and Tableau interactive reporting
- DAX formulas, measures, and business KPIs
- AI-assisted chart selection and layouts
- Executive reporting and insight presentation
Labs & Tools
- Power BI
- Tableau
- DAX and Power Query
- AI BI copilots and dashboard templates
Power BITableauDAXDashboardsStorytelling
Module 05 · AI-Assisted Analytics
AI-Assisted Analytics Workflows
Clean, visualize, and report faster with AI as your co-analyst.
Use ChatGPT, Claude, Copilot, and BI copilots to detect data issues, generate SQL and Python, summarize findings, and automate reporting. Learn prompt engineering for data tasks and build repeatable AI-powered analytics workflows.
Core Activities
- Prompt engineering for data tasks
- AI-assisted data cleaning and validation
- AI-powered code generation for SQL and Python
- Automated reporting workflows
- Business insight summaries with LLMs
Labs & Tools
- ChatGPT and Claude
- GitHub Copilot
- Power BI and Tableau AI copilots
- OpenAI, Claude, and business datasets
ChatGPTClaudeCopilotPrompt EngineeringAutomated Reports
Module 06 · Machine Learning
Machine Learning & Predictive Analytics
Move from explaining what happened to predicting what comes next.
Apply supervised and unsupervised machine learning to real business problems. Build regression, classification, clustering, churn prediction, and sales forecasting models, then translate model results into business recommendations.
Core Activities
- Supervised learning: regression and classification
- Unsupervised learning: clustering
- Customer churn prediction
- Sales forecasting and model evaluation
- Business interpretation and model storytelling
Labs & Tools
- Scikit-learn
- Google Colab
- Python ML notebooks
- Real sales and customer datasets
Scikit-learnRegressionClassificationClusteringForecasting
Module 07 · NLP & Customer Intelligence
NLP & Customer Intelligence
Turn unstructured text into business insight.
Analyze customer feedback, reviews, survey responses, and support tickets using NLP. Learn sentiment analysis, topic modeling, text classification, and LLM-assisted customer insight workflows.
Core Activities
- Sentiment analysis and topic modeling
- Customer feedback analysis
- Text classification and keyword extraction
- LLM-assisted text summaries
- Customer experience recommendations
Labs & Tools
- NLTK and spaCy
- HuggingFace models
- Customer review datasets
- ChatGPT and Claude for NLP
NLPspaCyNLTKSentimentTopic Modeling
Module 08 · Decision Intelligence
Decision Intelligence & AI-Powered Reporting
Use AI to move from analysis to action.
Build scenario models, what-if simulations, decision frameworks, and automated executive reports. Use prompt chaining to move from raw data to recommendations stakeholders can act on.
Core Activities
- Scenario modeling and what-if analysis
- Decision intelligence and optimization
- AI-powered report generation
- Prompt chaining for analytics workflows
Labs & Tools
- Claude and ChatGPT
- Power BI and Excel scenario models
- Real business datasets for report validation
Scenario ModelingWhat-If AnalysisAI ReportingDecision Intelligence
Module 09 · Capstone Project
Portfolio Capstone Project
The portfolio project that makes your skills visible.
Build a full, portfolio-grade analytics project using a real business dataset. Define the problem, clean the data, query it, visualize it, apply predictive techniques, and present recommendations in an executive-ready format.
Core Activities
- Problem definition and business requirements
- Data cleaning, SQL querying, and feature preparation
- Dashboard, forecast, and business recommendation
- Executive presentation and portfolio walkthrough
- Capstone project review
Labs & Tools
- Capstone dataset and project brief
- Power BI or Tableau dashboard
- Python notebook and SQL analysis
- ChatGPT for executive summary drafting
CapstonePortfolioDashboardForecastPresentation
Career Module · Job Search Support
Career Support & Analytics Job Readiness
Turn hands-on analytics work into a signed job offer.
Build an ATS-optimized LinkedIn profile and resume tailored to data analyst job descriptions. Create a portfolio with dashboards, notebooks, reports, and AI analytics workflows. Practice interviews, technical walkthroughs, and U.S. salary negotiation.
Core Activities
- LinkedIn, resume, and job portal build-up
- AI-optimized resume for data analyst roles
- Dashboard and GitHub portfolio positioning
- Mock technical interviews and case walkthroughs
- U.S. analytics salary negotiation with benchmark data
Labs & Tools
- LinkedIn, GitHub, Jobscan, and Teal
- Resume Worded and ATS optimization tools
- Glassdoor and data analyst career pathway research
- Claude and ChatGPT for resume tailoring and mock interviews
LinkedInAnalytics PortfolioATS OptimizationMock InterviewsSalary Negotiation