1. Advanced Excel for Data Analysis

• Advanced Formulas and Functions (VLOOKUP, INDEX-MATCH, IF, SUMIFS, etc.)
• Data Cleaning and Formatting Techniques
• Pivot Tables & Pivot Charts
• Conditional Formatting and Dynamic Dashboards
• Data Validation and Protection
• Introduction to Power Query
• Automating Reports with Macros (Basic VBA Concepts)

2. Power BI (Business Intelligence & Visualization)

• Introduction to Business Intelligence Concepts
• Connecting and Transforming Data (Power Query Editor)
• Data Modeling and Relationships
• DAX (Data Analysis Expressions) Formulas
• Creating Interactive Dashboards & Reports
• Publishing Reports to Power BI Service
• Sharing and Collaborating in Power BI Workspace

3. SQL (Structured Query Language)

• Introduction to Databases & SQL Basics
• Data Retrieval with SELECT, WHERE, ORDER BY, GROUP BY
• Joins, Subqueries, and Set Operations
• Aggregate and String Functions
• Data Modification (INSERT, UPDATE, DELETE)
• Database Design & Normalization
• Practical Query Optimization Techniques

4. Python for Data Science

• Introduction to Python Programming
• Data Types, Variables, and Control Structures
• Working with Libraries: NumPy, Pandas, Matplotlib, Seaborn
• Data Cleaning, Wrangling & Manipulation
• Exploratory Data Analysis (EDA)
• Reading/Writing Data from Excel, CSV, and Databases
• Basic Data Visualization Techniques

5. Alteryx (Data Preparation & Automation)

• Introduction to Alteryx Designer Interface
• Input/Output and Data Blending Tools
• Data Cleansing, Filtering, and Transformation
• Formula, Summarize, and Join Tools
• Workflow Creation and Automation
• Output and Report Generation
• Integration with Excel and Databases

6. Machine Learning (Fundamentals & Applications)

• Understanding Machine Learning Concepts
• Supervised vs. Unsupervised Learning
• Regression and Classification Models
• Model Evaluation and Validation
• Working with Scikit-learn and Pandas
• Feature Engineering & Data Preprocessing
• Real-world Predictive Modeling Projects

7. Data Governance & Ethics

• Introduction to Data Governance Frameworks
• Data Quality, Privacy & Security Principles
• Regulatory Compliance (GDPR, HIPAA Basics)
• Role of Data Stewardship and Ownership
• Data Lifecycle Management
• Best Practices in Ethical AI & Responsible Data Use

8. Capstone Project

• End-to-End Data Analysis Project
• Integrating Excel, SQL, Python, and Power BI
• Building Dashboards and Predictive Models
• Presentation & Reporting of Findings