Data Analytics Course (Beginner)

Course Overview

• Course Duration:4-6 Months including Lab.
• Eligibility: Undergraduates Graduates Post-Graduates career Aspirants School Going learners Professionals.
• School Going learners.

Data Analytics course Program

• Enroll in our comprehensive Data Analytics Course Mentorship Program and master skills to analyze, visualize, and interpret complex data.
• Learn to work with Excel, SQL, Power BI, and Python to transform raw data into valuable business insights.
• Understand Data Cleaning, Visualization, and Reporting for real-world decision-making.
• Work on Live Data Analytics Projects using real industry datasets.
• Earn a recognized Data Analytics credential preparation and get complete career outcome Assistance from our experts.
• We also help you build a Professional Resume and prepare for Data Analyst Interviews.

Overview of Data Analytics Mentorship Program

The Data Analytics Mentorship Program is a hands-on, hands-on training course that helps you learn how to collect, process, and analyze data using modern tools and technologies. You'll gain expertise in Excel, SQL, Power BI, and Python to make data-driven decisions and create impactful business reports.

Whether you are a student, working professional, or career changer, this program provides you with guided mentorship, live projects, and industry-relevant analytics skills to become a professional Data Analyst.

Introduction to Data Analytics

Get familiar with data analytics concepts, workflow, and key tools.

• Understanding data analytics lifecycle.
• Types of data and sources.
• Introduction to Excel, SQL, and Power BI.
• Data-driven decision making.

Excel for Data Analytics

Learn to clean, organize, and analyze data using Excel functions and tools.

• Data cleaning with filters and formulas.
• Pivot tables and charts.
• Conditional formatting and dashboards.
• Data validation and lookup functions.

SQL for Data Management

Learn how to manage, query, and analyze structured data using SQL.

• Understanding databases and tables.
• Writing SELECT, WHERE, and JOIN queries.
• Aggregations and subqueries.
• Creating reports using SQL.

Power BI Data Visualization

Build stunning dashboards and reports using Microsoft Power BI.

• Connecting data sources.
• Data modeling and DAX formulas.
• Creating visual reports and KPIs.
• Publishing dashboards online.

Python for Data Analysis

Use Python to automate and analyze large datasets efficiently.

• Using Pandas and NumPy for data handling.
• Data cleaning and transformation.
• Data visualization using Matplotlib.
• Basic statistics and insights generation.