Data Analytics – From Excel to Python, Power BI & ML Basics

This comprehensive Data Analytics course provides practical training on data handling and visualization tools used by analysts and decision-makers. You’ll begin with Excel and statistics, build database skills with SQL, advance to Python programming for data manipulation, and learn to create interactive dashboards in Power BI. It also introduces Machine Learning basics for predictive analysis and MIS reporting for structured business reporting.

By the end of the course, you’ll be confident in analyzing real-time business data and building data dashboards for impactful insights.

Tech Stack Covered :
Data Analysis & Visualization Tools:
Microsoft Excel (Advanced):
Perform data cleaning, use pivot tables, charts, dashboards, VLOOKUP/XLOOKUP, and macros for reporting.

SQL (Structured Query Language):
Query databases, perform joins, filters, subqueries, and aggregations to extract and analyze business data.

Statistics for Data Analysis:
Understand measures of central tendency, dispersion, correlation, regression, hypothesis testing, and statistical decision-making.

Python for Data Analytics:
Use Python with libraries like Pandas, NumPy, and Matplotlib to process and visualize large datasets efficiently.

Power BI:
Build and publish professional dashboards and interactive visualizations to communicate insights clearly.

Machine Learning (ML) Basics:
Introduction to Machine Learning

Supervised vs Unsupervised Learning

Real-world use cases (like predicting sales or customer churn)

Hands-on: Building your first simple ML model using Python’s Scikit-learn

Note: This module focuses on ML concepts and introductory level implementation suitable for analysts, not deep ML engineering.

MIS (Management Information Systems) Basics:
Overview of MIS in organizations

Creating automated Excel reports for business operations

Designing monthly/weekly MIS dashboards using Excel & Power BI

Real-time examples: Sales MIS, HR MIS, Finance MIS

Tools & DevOps:
VS Code / Jupyter Notebook / Excel

Git & GitHub – Version control and sharing code/data notebooks

PostgreSQL/MySQL Workbench – SQL Practice

Power BI Desktop – Data modeling & dashboard publishing