Full Stack Data Analytics equips learners with the technical, analytical, and problem-solving skills needed to transform raw data into actionable insights. This practical, industry-driven program covers data cleaning, analysis, visualization, and reporting—preparing students for high-demand roles in today’s rapidly evolving data-powered economy.
#420,000
#700,000
The Full Stack Data Analytics Program is a comprehensive, career-focused training designed to equip learners with the technical and analytical skills required to thrive in today’s data-driven world. Over four intensive months, students gain hands-on experience across the entire analytics pipeline—from data collection and cleaning to analysis, visualization, and insight communication.
The program blends advanced Excel, SQL, Python programming, and Business Intelligence tools such as Power BI or Tableau to build a strong analytical foundation. Learners also explore statistics, predictive analysis, ETL processes, and the essentials of data engineering, ensuring they understand both the analytical and structural components of modern data systems.
Through real-world case studies and practical industry projects, students develop the ability to interpret complex datasets, build dashboards, automate reports, and convert raw data into meaningful business insights. Each participant completes a capstone project and a professional portfolio to showcase their skills to employers.
Ideal for beginners and career switchers, this program prepares students for high-demand roles such as Data Analyst, Business Intelligence Analyst, Product Analyst, and Reporting Specialist. Graduates leave with confidence, technical competence, and job-ready skills to excel in today’s competitive digital economy.
Topics
Introduction to Data Analytics & Data Ecosystem
Types of Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
Data Lifecycle & Data Value Chain
Business Intelligence vs Data Science vs Data Engineering
Data Ethics, Privacy & Governance
Analytical Thinking & Problem-Solving
KPIs, Metrics & Business Requirements Gathering
Practical
Designing analytics use cases
Hands-on exploratory analysis
Topics
Advanced Excel Functions (LOOKUPs, IFs, TEXT, DATE, Statistical functions)
Pivot Tables & Pivot Charts
Data Cleaning & Formatting for Analytics
Power Query Basics
Excel Dashboards
Practical
Build a business dashboard using Pivot Tables & Charts
Topics
Understanding Databases & Data Warehouses
SQL Basics (SELECT, WHERE, GROUP BY, HAVING)
Joins, UNION, Subqueries, CTEs
Window Functions (ROW_NUMBER, RANK, LAG, LEAD)
Data Manipulation (INSERT, UPDATE, DELETE)
Performance Optimization
Building Complex Analytical Queries
Practical
Analyze sales database using SQL
Write optimized queries for real-world scenarios
Topics
Python Basics for Analytics
Data Structures & Control Flow
Working with Pandas & NumPy
Data Cleaning, Wrangling & Transformation
Exploratory Data Analysis (EDA)
Data Visualization (Matplotlib, Seaborn, Plotly)
Automated Reporting
Introduction to APIs & Web Scraping
Practical
Build an EDA report using Pandas
Visualize trends using Seaborn & Plotly
Topics
Connecting to Data Sources
Data Modeling (Star Schema & Snowflake)
DAX Formulas (Power BI)
Calculated Columns & Measures
Building Interactive Dashboards
Publishing & Sharing Reports
BI for Business Decision-Making
Practical
Build a fully interactive BI dashboard
Topics
Descriptive & Inferential Statistics
Probability, Distributions & Hypothesis Testing
Correlations & Regression Analysis
Forecasting Models
A/B Testing
Feature Importance & Intro to Machine Learning
Practical
Build a regression model
Run an A/B test simulation
Topics
ETL vs ELT
Understanding Data Pipelines
Cloud Analytics (AWS/GCP/Azure overview)
Data Warehouses (BigQuery, Snowflake, Redshift)
Introduction to Big Data Tools (Spark concept)
Practical
Build a simple ETL pipeline
Load data into a mini warehouse
Activities
Choose a real-world dataset (finance, e-commerce, health, marketing, logistics, etc.)
Perform Data Cleaning & EDA
SQL and Python analysis
Build BI Dashboard
Deliver business recommendations
Data Analyst
Business Intelligence (BI) Analyst
Data Scientist (Junior/Associate)
Data Engineer (Entry-Level)
SQL Database Analyst
Power BI / Tableau Developer
Machine Learning Analyst (Junior)
Operations / Product Data Analyst
Marketing / Growth Data Analyst
Financial Data Analyst
Business Analyst (Tech-Focused), etc.
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