AI-INTEGRATED DATA ANALYTICS & GENAI PROFESSIONAL PROGRAM Specialization.

Module 1: Data Analytics Foundations

• Core Concepts: Get introduced to data analytics, the overall analytics lifecycle, and business intelligence concepts.

• Frameworks: Understand the distinct types of analytics and the core principles behind data visualization.

• Application: Learn how data-driven decision making functions inside corporate environments.

Module 2: Advanced Microsoft Excel for Data Analytics

• Data Manipulation: Master advanced Excel functions, data cleaning, validation methods, and Power Query workflows.

• Aggregation: Build and structure data using Pivot Tables and Pivot Charts.

• Business Reporting: Develop interactive dashboards, Management Information Systems (MIS), and targeted KPI dashboards for reporting.

Module 3: Statistics for Data Analytics

• Mathematical Foundations: Study descriptive statistics, essential probability concepts, and correlation analysis.

• Predictive Modeling: Learn regression analysis and forecasting techniques to project business metrics.

• Strategy: Design business decision models based on mathematical logic.

Module 4: SQL for Data Analytics

• Database Programming: Learn database fundamentals and structure statements using SQL programming.

• Advanced Querying: Combine complex data structures utilizing joins, subqueries, and Common Table Expressions (CTEs).

• Optimization & Logic: Implement window functions, views, stored procedures, and practical business analytics scripts using SQL.

Module 5: Python for Data Analytics

• Programming Foundations: Learn Python fundamentals, Jupyter Notebook environments, and data structures.

• Data Engineering: Process, clean, and transform messy data arrays utilizing the NumPy and Pandas libraries.

• Analysis & Visuals: Conduct Exploratory Data Analysis (EDA), create graphs using Matplotlib and Plotly, and implement analytics automation.

Module 6: Microsoft Power BI

• Data Architecture: Import, clean, and transform raw files utilizing Power Query alongside structured data modeling.

• Calculations: Learn Data Analysis Expressions (DAX) fundamentals to process custom metric fields.

• Distribution: Publish interactive dashboards and KPI reports securely onto the Power BI Service.

Module 7: Tableau for Data Visualization

• Visual Environments: Master Tableau fundamentals and configure dynamic data connections.

• Design & Insights: Build interactive dashboards, map out forecasting lines, and generate corporate business reports.

• Narratives: Blend technical indicators into clear presentations using data storytelling techniques.

Module 8: Generative AI for Data Analytics

• AI Core Literacy: Understand Generative AI ecosystems and master professional prompt engineering.

• LLM Toolkits: Leverage tools like ChatGPT, Google Gemini, Microsoft Copilot, and Claude AI to optimize daily workflows.

• Smart Engineering: Perform AI-assisted data cleaning, automated AI-powered SQL generation, and smart report/dashboard building.

• Operations: Supercharge output speeds via automated AI productivity frameworks.

Module 9: Professional Development

• Employment Ready: Build a professional resume, assemble a code portfolio on GitHub, and optimize your LinkedIn presence.

• Soft Skills: Perfect your professional presentation skills and study real-world corporate case study discussions.

• Placement: Practice technical and personal workflows using targeted interview preparation strategies.