AI-INTEGRATED BUSINESS ANALYTICS & INTELLIGENCE PROFESSIONAL PROGRAM Specialization.

Module 1: Business Analytics Foundations

·        Core Literacy: Fundamentals of Business Analytics and Business Intelligence.

·        Frameworks: Exploring the different types of analytics, Key Performance Indicators (KPIs), and target business domains.

·        Application: Utilizing structured evaluation methods for data-driven corporate decision making.

Module 2: Advanced Excel

·        Data Functions: Mastering advanced operations and multi-tier lookup functions.

·        Reporting & Power Query: Transforming raw data with Power Query to construct custom Pivot Tables and interactive dashboards.

·        Automation: Learning baseline macro configurations and designing corporate Management Information Systems (MIS) reporting layouts.

Module 3: SQL for Business Analytics

·        Database Programming: Designing databases and writing structured SQL programming scripts.

·        Complex Intersections: Joining data tables, nesting subqueries, and maintaining clean virtual views.

·        Business Analytics Queries: Writing highly targeted query scripts to evaluate customer behavior and sales trends.

Module 4: Statistics & Data Analysis

·        Mathematical Basics: Learning descriptive statistics and evaluating dataset relationships through correlation.

·        Predictive Trends: Implementing regression analysis and quantitative forecasting rules.

·        Strategy Models: Structuring logic-backed business decision models.

Module 5: Python for Business Analytics

·        Environment & Syntax: Understanding Python basics inside interactive Jupyter Notebook workflows.

·        Data Manipulation: Leveraging the core NumPy and Pandas libraries for data cleaning operations.

·        Visual Discovery: Creating data visualizations and conducting in-depth Exploratory Data Analysis (EDA).

Module 6: AI for Business Analytics

·        Ecosystem Training: Working with Generative AI architectures and studying professional prompt engineering.

·        Large Language Models: Utilizing industry-leading assistants including ChatGPT, Gemini, and Microsoft Copilot.

·        Smart Enhancements: Implementing modern tools to accelerate AI research, automated AI report generation, and daily workplace productivity.

Module 7: Microsoft Power BI

·        Data Architecture: Modeling complex relationship schemas and processing ingestion stages using Power Query.

·        Metric Logic: Learning Data Analysis Expressions (DAX) script formulas to compile calculations.

·        Corporate Reporting: Designing interactive KPI dashboards and deploying finished assets securely onto cloud publishing spaces.

Module 8: Tableau

·        Pipelines: Navigating server data connections and establishing primary baseline visualizations.

·        Executive Delivery: Constructing clean tracking dashboards paired with analytical forecasting lines.

·        Communication: Structuring presentation methodologies using data storytelling techniques.

Module 9: Financial Analytics

·        Accounting Principles: Reviewing baseline accounting fundamentals and dissecting financial statements.

·        Health Evaluation: Measuring performance trends through ratio analysis, cash flow patterns, and budgeting matrices.

·        Revenue Metrics: Designing analytics monitors to trace operational revenue channels.

Module 10: Professional Development

·        Communication Skills: Perfecting daily corporate business communication and polished presentation skills.

·        Identity Branding: Crafting technical resumes and maximizing networking results on LinkedIn.

·        Placement Success: Practicing interview preparation techniques for employment readiness.