Data Analytics With AI

This module equips learners with the essential skills to transform raw data into meaningful business insights. Starting with data literacy, statistics, and advanced Excel techniques, the program moves into SQL fundamentals and advanced querying for real-world business applications. Learners also gain hands-on exposure to Python and Jupyter notebooks, enabling them to build end-to-end workflows for data extraction, transformation, and analysis. Through integration workshops, industry case studies, and portfolio projects, participants develop practical expertise to solve business problems and showcase analytical insights that align with industry needs.

This module builds advanced skills in Python-based data manipulation, analysis, and communication. Learners begin with Pandas for data cleaning, transformation, and feature engineering, followed by Exploratory Data Analysis (EDA) techniques using NumPy and Pandas for profiling, correlation, and aggregation. Business statistics and hypothesis testing are then applied to real-world scenarios, including A/B testing for decision-making. The module concludes with mastering visualization tools like Matplotlib and Seaborn, enabling learners to present insights effectively through professional dashboards, case studies, and portfolio-ready projects.

This module focuses on mastering Business Intelligence tools and executive-level communication. Learners start with Power BI development, covering data modeling, DAX formulas, and dashboard creation, before advancing into cloud integration, automation, and enterprise-level features. The module then introduces Tableau, enabling comparisons between tools through hands-on projects and case studies in areas like HR, budgeting, and supply chain analytics. The program concludes with data storytelling, executive dashboard design, and presentation techniques, preparing learners to deliver impactful insights to stakeholders while also building certification-ready skills for PL-300.

This module emphasizes applying analytics for forecasting, experimentation, and domain-specific business impact. Learners begin with time-series forecasting and predictive analytics, progressing into customer segmentation techniques like RFM, cohort, and clustering analysis. The module also develops skills in experimental design and A/B testing, enabling participants to evaluate marketing or product strategies with statistical rigor. Finally, students choose a specialization track—Marketing, Finance, HR, or General Analytics—where they work on industry-specific case studies and a capstone project, building domain expertise and preparing for professional certifications.

This module is dedicated to a comprehensive capstone project where learners solve real-world business problems using a full analytics workflow, integrating SQL, Python, Excel, and BI tools to deliver actionable recommendations with measurable ROI. The project culminates in professional deliverables including a detailed report, interactive dashboard, executive presentation, and technical documentation, supported by daily mentorship and industry feedback.