This 5-month intensive course is designed to make you a complete, job-ready Data Analyst β even if you're starting from scratch. Through structured pre-recorded video content, hands-on practice, real-world case studies, and resume-ready projects, you'll learn the most in-demand tools and techniques used by data professionals worldwide.
You'll start with Excel, the foundation for analysis, then move to SQL to query databases like a pro. With Python, youβll clean, analyze, and visualize data, then master Power BI to create stunning dashboards. Youβll also gain skills in statistics, business understanding, and data storytelling, which are critical for driving decisions with data.
Whether you're aiming for a new career, a promotion, or freelancing opportunities, this course equips you with everything you need to thrive in the modern data world.
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Beginner-Friendly to Pro-Level
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Pre-recorded, Self-Paced Lessons
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8+ Real-World Projects
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Interview Preparation & Resume Support
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Certificate of Completion
What is Data Analysis?
Role & Responsibilities of a Data Analyst
Overview of BI Tools & Data Ecosystem
Types of Data & Industries That Use Data Analytics
Excel Basics to Advanced
Pivot Tables & Pivot Charts
VLOOKUP, HLOOKUP, INDEX-MATCH
Data Cleaning & Validation
Conditional Formatting & Dashboards
Excel Project: Sales & Marketing Analytics
Introduction to Databases & SQL
SELECT, WHERE, ORDER BY, GROUP BY
JOINS (INNER, LEFT, RIGHT, FULL)
Window Functions & Subqueries
Data Aggregation & Filtering
SQL Project: Business Insights from E-commerce Database
Python Basics for Data Professionals
Working with Pandas & Numpy
Data Cleaning & Transformation
Data Visualization using Matplotlib & Seaborn
Exploratory Data Analysis (EDA)
Python Project: Customer Churn Analysis
Power BI Interface and Workflow
Loading & Transforming Data (Power Query)
Creating Interactive Dashboards
DAX Functions for Custom Calculations
Publishing Reports & Sharing Insights
Power BI Project: Financial Dashboard for Stakeholders
Descriptive vs. Inferential Statistics
Mean, Median, Mode, Standard Deviation
Probability Basics & Hypothesis Testing
A/B Testing and Business Applications
Data-Driven Decision Making
Retail: Sales Performance Analysis
Finance: Profitability Dashboard
HR: Attrition & Employee Data Insights
Healthcare: Patient Data Analytics
Final Capstone Project: End-to-End Data Analysis Report
Building a Data Analyst Resume & GitHub Portfolio
Key Interview Questions & Case Study Practice
LinkedIn Optimization for Job Search
Freelancing & Project Pitching Guidance
Excel, Power BI
SQL (MySQL/PostgreSQL)
Python (Jupyter Notebook, Pandas, Numpy, Matplotlib, Seaborn)
GitHub, Google Sheets, Google Data Studio .
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