Data Analysis

Data Analysis is a career-focused programme designed to teach learners how to collect, clean, organize, analyze and visualize data to discover meaningful insights.

The course provides practical exposure to spreadsheets, SQL, Python, data visualization and business analytics. Learners work with real-world datasets and practical projects to understand how data can be transformed into useful information for business and decision-making.

The Data Analysis programme provides a structured learning path from basic data concepts to practical analytical techniques.

Learners will understand how to work with structured datasets, clean and transform raw data, perform exploratory analysis, write SQL queries, use Python for data analysis and create interactive dashboards and visual reports.

The programme emphasizes hands-on learning through exercises, case studies and portfolio projects so that learners can demonstrate their analytical skills in practical scenarios.

Course Name: Data Analysis

Training Level: Beginner to Advanced

Mode: Classroom + Practical Training

Learning Approach: Theory + Hands-on Practice + Projects

Key Training Areas:

• Data Analysis Fundamentals
• Excel for Data Analysis
• Advanced Excel
• Data Cleaning & Preparation
• SQL & Database Queries
• Python Fundamentals
• Python for Data Analysis
• Pandas & NumPy
• Exploratory Data Analysis
• Data Visualization
• Power BI
• Dashboard Development
• Business Intelligence Basics
• Data Interpretation
• Real-World Case Studies
• Portfolio Projects

Practical Training:
Learners work with real-world datasets and build analytical reports, dashboards and projects.

Project-Based Learning:
Students create portfolio-ready projects to demonstrate practical data analysis and visualization skills.

Basic computer knowledge and an interest in numbers, technology and problem-solving are recommended.

No advanced programming experience is required to begin. Learners should be comfortable with basic mathematics and willing to practice using analytical tools and datasets.