Data Analyst
9 comprehensive modules
📋 Learning Objectives
- 🧠 Understand the role of a Data Analyst
- 🔄 Learn the data analytics workflow
- 📊 Explore different types of analytics
- 📈 Grasp business metrics and KPIs
📚 Topics Covered
- 🟡 1.1 Introduction to Data Analytics
- 🔍 1.2 Types of Data Analytics
- 📁 1.3 Data and Information
- 🛠️ 1.4 Analytics Workflow (OSEMN Framework)
- 💼 1.5 Business Context
- 🧰 1.6 Tools Overview
🧪 Hands-on Activities
- 🧪 Lab: Understanding Data Sources
- 📊 Lab: Identifying KPIs
📌 Project: Business Problem Analysis
📋 Learning Objectives
- 📈 Master analytics in Excel
- 📊 Build dashboards & reports
- 🛠️ Use advanced functions
- 🤖 Automate tasks
📚 Topics Covered
- 📘 Excel Fundamentals
- ✨ Advanced Excel Functions
- 🧹 Data Cleaning & Preparation
- 📑 Pivot Tables & Analysis
- 📊 Statistical Functions
- 🎨 Visualization & Dashboards
- 🔍 What-If & Advanced Analytics
- 🤖 Macros & Automation
🧪 Hands-on Activities & Projects
- 📉 Pivot Table Creation
- 📊 Dashboard Design
- 📈 Sales Performance Analysis
📋 Learning Objectives
- 📊 Learn core statistical methods
- 🎲 Understand probability
- 📉 Perform hypothesis testing
- 📈 Apply statistical thinking
📚 Topics Covered
- 📌 Descriptive Statistics
- 🧮 Probability Theory
- 📊 Regression & Correlation
- 🔄 Time Series Analysis
- 🧠 Statistical Thinking
🧪 Hands-on Activities
- 📈 Statistical Analysis Lab
- 📊 Hypothesis Testing Lab
- 📉 Regression & Forecasting
📋 Learning Objectives
- 🗄️ Master database querying
- 🧠 Build complex SQL queries
- 🧩 Learn database design
- 🚀 Optimize performance
📚 Topics Covered
- 💽 Database Fundamentals
- 🔍 SQL Basics & SELECT
- 📊 Advanced Queries
- 🔗 Joins & Subqueries
- 📈 Window Functions
- ⚙️ Performance Optimization
🧪 Hands-on Activities
- 🧩 SQL Labs
- 📌 Database Analysis Projects
📋 Learning Objectives
- 🐍 Use Python for analytics
- 🧰 Work with Pandas & NumPy
- 📊 Build data workflows
- 📈 Visualize data
📚 Topics Covered
- 🖥️ Python Basics
- 🔁 Control Flow
- 📊 Data Structures
- 📥 File Handling
- 🧮 EDA & Visualizations
- 🧰 Regex for Data Cleaning
🧪 Hands-on Activities
- 🧠 Data Manipulation
- 📉 Visualization Projects
📋 Learning Objectives
- 🔍 Master Tableau dashboards
- 📈 Create interactive charts
- 🧠 Tell data stories visually
📚 Topics Covered
- 📊 Tableau Fundamentals
- 🖼️ Building Visuals
- 🎯 Dashboard Design
- 🔄 Interactivity & Filters
- 🗺️ Maps & Storytelling
🧪 Hands-on Activities
- 📊 Build Business Dashboards
- 📈 Data Storytelling Projects
📋 Learning Objectives
- 📈 Build interactive dashboards using Power BI
- 🔗 Connect multiple data sources
- 🧠 Apply data modeling concepts
- 📊 Share insights with stakeholders
📚 Topics Covered
- ⚡ Introduction to Power BI & Architecture
- 🔌 Data Connections & Importing
- 🧹 Data Cleaning using Power Query
- 🧩 Data Modeling & Relationships
- 🧮 DAX Basics & Calculated Measures
- 📊 Visuals, Charts & KPIs
- 🎯 Interactive Dashboards & Reports
- 🔐 Publishing & Sharing Reports
🧪 Hands-on Activities
- 📊 Sales & Finance Dashboard
- 📈 Business Performance Report
- 🧠 Real-world BI Use Case Project
📋 Learning Objectives
- 🤖 Use AI to speed up analysis
- 🧠 Improve decision-making with AI insights
- 📊 Automate reporting & analysis tasks
- 🚀 Increase productivity as a Data Analyst
📚 Topics Covered
- 🤖 Introduction to AI in Data Analytics
- 🧠 Prompt Engineering for Data Analysis
- 📊 AI-assisted Data Cleaning
- 📈 AI-based Insights & Forecasting
- 📝 Automated Reports & Summaries
- 🔍 AI Tools for SQL, Excel & Python
- ⚙️ Ethics & Responsible AI Use
🧪 Hands-on Activities
- 🤖 AI-assisted Excel & SQL Analysis
- 📊 Automated Dashboard Insights
- 🚀 Productivity Booster Mini Projects
📋 Learning Objectives
- 💼 Gain real-world project experience
- 📄 Build an industry-ready resume
- 🎤 Crack Data Analyst interviews
- 🚀 Become job-ready
📚 Topics Covered
- 🏢 Industry-Based Capstone Projects
- 📊 End-to-End Data Analysis Lifecycle
- 📄 Resume & Portfolio Building
- 🧠 Business Case Studies
- 🎤 Technical & HR Interview Questions
- 💬 Mock Interviews & Feedback
- 🔍 Job Search & Career Guidance
🧪 Hands-on Activities
- 📊 Capstone Project (Domain-Based)
- 📁 Portfolio & GitHub Setup
- 🎯 Interview Simulation Sessions
Career certifications validate expertise in a specific field, enhancing credibility and job prospects.
A Data Analyst collects, processes, and analyzes data to help organizations make informed business decisions. They use tools like Excel, SQL, Python, and BI platforms to uncover insights, trends, and patterns in data that drive strategic business decisions.
No! This course is beginner-friendly. We start from basics and gradually progress to advanced concepts. Basic computer knowledge is sufficient. No prior programming or data analytics experience is required to enroll.
Yes! The course includes career guidance, resume optimization, mock interviews, portfolio review, and job placement support to help you secure positions with leading IT companies and startups.
You will learn industry-standard tools including Microsoft Excel (advanced formulas, pivot tables, data visualization), SQL (MySQL, PostgreSQL, database design), Python (Pandas, NumPy, Matplotlib), Power BI, Tableau, and statistical analysis tools. All tools used are widely used in the industry.
The course is 5 months long with 130 days total duration. It includes 70 live classes and 370 total hours of learning content. You can access recorded sessions anytime after live class completion, making it flexible for working professionals.
No, this course is designed for beginners. No prior programming or Excel experience required.
Yes, you get 1 year access to all video lectures, labs, resources, and updates
We provide job placement assistance and connect you with hiring partners, but placement depends on performance and market conditions.
Yes, top performers get internship opportunities with partner companies.
Yes, our flexible evening and weekend batches are designed for working professionals.
Both are taught in the course. Your employer's preference may guide focus, but learning both increases opportunities.
Yes, we cover basics of cloud databases with AWS and Azure SQL examples.
