DATA ANALYTICS

About Course

The Data Analytics Professional Course is an industry-aligned training designed to equip participants with the practical skills required to collect, clean, analyze, interpret, and visualize data for decision-making. The course blends theory with hands-on training using modern tools such as Excel, Power BI, SQL, Python, and real-world datasets.

Participants will learn how organizations use data to solve complex problems, predict trends, identify insights, and make evidence-based decisions. The program includes a special module on Career & Job Opportunities in Data Analytics, salary expectations, industry pathways, and the latest global trends shaping the world of data.

Upon successful completion, learners will receive a globally recognized Professional Certification, positioning them for jobs in tech, business, finance, health, government, NGOs, and multinational companies.

🎯 Course Objective

The goal of this professional course is to:

Build practical skills required for modern data analytics roles.

Empower participants to collect, clean, and transform raw data.

Teach the use of powerful tools (Excel, SQL, Power BI, Python).

Enable learners to interpret data and generate actionable insights.

Teach dashboard and report development for management.

Prepare participants for global job opportunities, freelancing, and remote work.

Equip participants with real-life project experience for their portfolio.

Position learners for internationally recognized certifications and industry relevance.

Admission Requirements

No strict requirements. Applicable for both beginners and professionals.
However, having the following will be helpful:

Basic computer knowledge

Ability to understand English

A laptop (minimum 4GB RAM recommended)

Interest in tech, business, or problem-solving

Duration

3 Months (12 Weeks)
Includes:

Weekly learning modules

Live classes / recorded sessions

Practical tasks

Final project & assessment

🏅 Certification

Participants will be awarded an Internationally Recognized Professional Certification in Data Analytics upon completion of the program and the final assessment.

This certificate can be used for:

Job applications

Promotions

Career transition

International remote jobs

Freelancing

This course takes learners from foundational concepts to advanced techniques in data analytics. You will explore the full data lifecycle—from understanding business problems to analyzing data and building interactive dashboards that drive business decisions.
It includes professional career guidance, industry trends, and real-world projects to prepare you for competitive, high-income roles.
Learning Outcomes
By the end of this course, participants will be able to:
Understand the fundamentals of data analytics and business intelligence.
Collect and clean data using professional techniques.
Use Excel for analysis and reporting.
Write SQL queries to extract and manipulate data.
Use Power BI to create dashboards and visual analytics.
Use Python for deeper analysis (optional advanced track).
Convert raw datasets into meaningful insights.
Present insights using dashboards, charts, and reports.
Apply analytics to marketing, finance, operations, health, and public sector data.
Build a professional portfolio for employers.
Understand global data analytics job roles, salaries, and career pathways.

Course Content

Module 1: Introduction To Data Analytics
Data Analytics courses will give you insights into how to apply data and analytics principles in your business. Learning analytics, data visualization, and data science methodologies through this course will make you capable of driving better business decisions and ROI.

Course Introduction
Data Analytics Overview
Dealing with different types of Data
Data Visualization for Decision Making
Data Science, Data Analytics and Machine Learning
Data Science Methodology
Data Analytics in Different Sectors
Analytics Framework and latest trends
Summary & Reflection

Module 2: Boost your Data Analytics Career with MS Excel
Microsoft Excel remains one of the most powerful and versatile tools for data analysis. Beyond simple calculations, Excel provides a vast ecosystem for cleaning, transforming, visualizing, and analyzing datasets efficiently. In professional environments—whether in business, finance, research, or project management—Excel serves as the foundation for data-driven decision-making.

Introduction to MS Excel
Efficient Tools in MS Excel
MS Excel Best Practices
Data Cleaning and Preparation
Professional Formatting
Cells and references
Excel functions – if and nested
Functions, Array functions
H lookup, V lookup, Index and Matching
Advanced MS Excel functions
Analyzing Data with pivot tables
Data Analysis using MS Excel
MS Excel Charts and Visualization
Using Macros for Analytics

Module 3: PowerBI
This training program helps you master PowerBI, a world-wide utilized data visualization, reporting, and business intelligence tool.

Module 4: Data Extraction using SQL
Structured Query Language (SQL) is the global standard for communicating with databases. Whether you are analyzing customer trends, financial transactions, or operational metrics, SQL enables you to extract, organize, and summarize the data behind business decisions. This module takes learners from the conceptual foundations of databases through hands-on query design, data manipulation, and advanced analysis using SQL. Learning Outcomes By the end of this module, learners will be able to: 1. Understand the fundamentals of databases and SQL. 2. Distinguish between data models and recognize how relational models evolved. 3. Install and configure SQL tools (GUI and command-line). 4. Create, populate, and restore datasets. 5. Write efficient SQL statements for data retrieval and manipulation. 6. Apply aggregation, sorting, and filtering for data analysis. 7. Combine data from multiple tables using joins and subqueries. 8. Group and summarize data for business insights.

Understanding the fundamentals of SQL
Introduction to Databases (Types, Tools)
Data Models: Thinking about your Data
The evolution of Data Models
Relational vs Transactional Models
Installing SQL
Introduction to SQL GUI
Creating Tables
Restoring Data sets
Writing SQL Statements
SQL Commands and retrieving Data
SQL Aggregations
Advanced Filtering with SQL
Sorting with SQL
Using wildcards SQL Joins
SQL Subqueries
Grouping Data with SQL
Real-World Applications of SQL in Analytics
Summary

Module 5: Data Analyst Projects and Portfolio Building
Data Analyst caps projects will give you an opportunity to implement the skills you learned in this Data Analyst certification course.

Choosing the Right Capstone Project
Project Structure & Step-by-Step Workflow
Data Sourcing, Licensing & Ethics
Reproducibility & Version Control
Mentorship & Review Process
Communication, Storytelling & Presentation
Building an Online Portfolio (Platforms & Structure)
Project Examples & Mini-Capstones
Assessment Criteria & Rubric – ICBMD Data Analyst Capstone
Final Submission & Presentation Guidelines
How Employers Evaluate Portfolio Projects
Resources & Suggested Readings
Summary

Module 6: Python for Data Analysis
Learn how to perform Data Analytics with Python

Programming Basics and Data Analytics with Python
Introduction to Programming
Programming Environment Setup
OOPs Concept with Python
Programming Fundamentals of Python
File handling, Exception handling, and Package handling in Data Analytics
Statistical Computing
Mathematical Computing using NumPy
Data Manipulation using Pandas
Data Visualization with Python
Introduction to Model building
Python for Data Science – Python Basics
Python Data Structure
Python Programming Fundamentals
Working with Data in Python
Working with NumPy Arrays
Introduction to Visualization Tools
Basic Visualization Tools
Specialized Visualization Tools
Advanced Visualization Tools
Creating Maps and Visualizing Geospatial Data

Module 7: Career Blueprint

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About Course

What Will You Learn?

Course Content

Course Introduction

Data Analytics Overview

Dealing with different types of Data

Data Visualization for Decision Making

Data Science, Data Analytics and Machine Learning

Data Science Methodology

Data Analytics in Different Sectors

Analytics Framework and latest trends

Summary & Reflection

Introduction to MS Excel

Efficient Tools in MS Excel

MS Excel Best Practices

Data Cleaning and Preparation

Professional Formatting

Cells and references

Excel functions – if and nested

Functions, Array functions

H lookup, V lookup, Index and Matching

Advanced MS Excel functions

Analyzing Data with pivot tables

Data Analysis using MS Excel

MS Excel Charts and Visualization

Using Macros for Analytics

Module 3: PowerBI This training program helps you master PowerBI, a world-wide utilized data visualization, reporting, and business intelligence tool.

Introduction to MS PowerBI

Navigating PowerBI Interface

PowerBi Query Editor

Data Visualization in PowerBI

Creating interactive dashboards

Data Modelling

DAX Measures

PowerBI Projects

Summary

Understanding the fundamentals of SQL

Introduction to Databases (Types, Tools)

Data Models: Thinking about your Data

The evolution of Data Models

Relational vs Transactional Models

Installing SQL

Introduction to SQL GUI

Creating Tables

Restoring Data sets

Writing SQL Statements

SQL Commands and retrieving Data

SQL Aggregations

Advanced Filtering with SQL

Sorting with SQL

Using wildcards SQL Joins

SQL Subqueries

Grouping Data with SQL

Real-World Applications of SQL in Analytics

Summary

Module 5: Data Analyst Projects and Portfolio Building Data Analyst caps projects will give you an opportunity to implement the skills you learned in this Data Analyst certification course.

Choosing the Right Capstone Project

Project Structure & Step-by-Step Workflow

Data Sourcing, Licensing & Ethics

Reproducibility & Version Control

Mentorship & Review Process

Communication, Storytelling & Presentation

Building an Online Portfolio (Platforms & Structure)

Project Examples & Mini-Capstones

Assessment Criteria & Rubric – ICBMD Data Analyst Capstone

Final Submission & Presentation Guidelines

How Employers Evaluate Portfolio Projects

Resources & Suggested Readings

Summary

Module 6: Python for Data Analysis Learn how to perform Data Analytics with Python

Programming Basics and Data Analytics with Python

Introduction to Programming

Programming Environment Setup

OOPs Concept with Python

Programming Fundamentals of Python

File handling, Exception handling, and Package handling in Data Analytics

Statistical Computing

Mathematical Computing using NumPy

Data Manipulation using Pandas

Data Visualization with Python

Module 3: PowerBI
This training program helps you master PowerBI, a world-wide utilized data visualization, reporting, and business intelligence tool.

Module 5: Data Analyst Projects and Portfolio Building
Data Analyst caps projects will give you an opportunity to implement the skills you learned in this Data Analyst certification course.

Module 6: Python for Data Analysis
Learn how to perform Data Analytics with Python