Industry Skills Classroom Training

Data Analyst

By the end of this course, you will be fully equipped to work as a Data Analyst — capable of extracting, transforming, and analyzing data, building powerful visualizations and dashboards, and delivering actionable business insights using SQL, Python, Pandas, NumPy, Matplotlib, Seaborn, and Streamlit — ready to perform from Day 1 on the job.

5.0 (32 ratings)
59 enrolled 3 Months | 4 hours/day Professional Tamil

What You'll Learn

  • Master SQL & Python for Data Analysis
  • Transform Raw Data into Meaningful Insights
  • Build Stunning Visualizations
  • Develop Interactive Dashboards with Streamlit
  • Work on Industry-Based Case Studies
  • Go from Job Seeker to Job Ready

Requirements

  • Basic Computer Operating Skills
  • No need of previous Programming Knowledge

Tools & Technologies

MS Excel MS Excel
PostgreSQL PostgreSQL
Python Python
Pandas Pandas
Matplotlib Matplotlib
Seaborn Seaborn
Streamlit Streamlit

Course Description

A professionally designed, industry-aligned classroom program focused on real-world Data Analysis practices. Gain hands-on experience with end to end data analyis experience through practical scenarios, case studies, and tools used in live projects — building the skills required to perform effectively as a Data Analyst from Day 1.

Right for You?

Who This Course is For

  • Fresh Graduates Looking to Start Their Career in Data
  • Job Seekers Who Want Industry-Relevant, Tool-Based Skills
  • Candidates Who Prefer Structured Classroom Learning
  • Anyone Ready to Commit and Become a Data Analyst

Course Curriculum

13 modules • 125 lessons
Module 1: Excel for Data Analyst 7 lessons
  • Excel Basics
  • Formatting & Editing
  • Formulas & Functions
  • Lookup & Logical Functions
  • Data Analysis
  • Charts & Visualization
  • Module 1 Clearance Test
Module 2: SQL for Data Analyst 16 lessons
  • Introduction to Databases & SQL
  • SQL Syntax & Query Structure
  • Filtering & Sorting Data
  • Aggregate Functions & Grouping
  • Join Operations
  • Subqueries & Nested Queries
  • Conditional Logic & CASE Statements
  • Window Functions
  • Common Table Expressions (CTEs)
  • String, Date & Numeric Functions
  • Data Cleaning & NULL Handling
  • Views & Stored Procedures
  • Indexes & Query Optimization
  • Real Business Scenario Practice
  • SQL Interview Preparation
  • Module 2 Clearance Test
Module 3: Python for Data Analyst 11 lessons
  • Introduction to Python & Environment Setup
  • Python Syntax & Data Types
  • Variables, Operators & Expressions
  • Conditional Statements & Loops
  • Functions & Modules
  • Lists, Tuples, Sets & Dictionaries
  • File Handling & Exception Handling
  • Object Oriented Programming Basics
  • Python Libraries Overview for Data Analysis
  • Python Interview Preparation
  • Module 3 Clearance Test
Module 4: Data Analyst Fundamentals & Data Concepts 7 lessons
  • Introduction to Data Analytics
  • Role of a Data Analyst
  • Types of Data & Data Sources
  • Data Analytics Lifecycle & Workflow
  • KPIs, Metrics & Business Reporting Concepts
  • Introduction to Jupyter Notebook & Anaconda
  • Module 4 Clearance Test
Module 5: Data Extraction with Pandas 8 lessons
  • Introduction to Pandas
  • Series & DataFrame Basics
  • Reading Data from CSV, Excel & JSON
  • Reading Data from SQL Database
  • Reading Data from Web & APIs
  • Indexing, Selection & Slicing
  • Filtering & Querying Data
  • Module 5 Clearance Test
Module 6: Data Transformation with Pandas & NumPy 16 lessons
  • Introduction to NumPy & Arrays
  • NumPy Array Operations & Math Functions
  • NumPy Statistical Operations
  • Handling Missing Values & Null Data
  • Handling Duplicates & Inconsistent Data
  • Data Type Conversion & Formatting
  • Renaming, Reordering & Dropping Columns
  • Sorting & Ranking Data
  • Grouping & Aggregation
  • Merging, Joining & Concatenating DataFrames
  • Pivot Tables & Cross Tabulation
  • String Operations & Text Cleaning
  • Date & Time Operations
  • Apply, Map & Lambda Functions
  • Window Functions & Rolling Calculations
  • Module 6 Clearance Test
Module 7: Data Modeling in SQL 8 lessons
  • Data Modeling Concepts
  • Schema Design - Star & Snowflake
  • Fact & Dimension Tables
  • Relationships, Keys & Cardinality
  • Normalization & Denormalization
  • Building Analytical Queries for Reporting
  • SQL for Business Reporting & KPI Calculation
  • Module 7 Clearance Test
Module 8: Data Visualization with Matplotlib 11 lessons
  • Introduction to Matplotlib
  • Data Visualization Principles & Best Practices
  • Line Charts & Area Charts
  • Bar Charts & Horizontal Bar Charts
  • Pie & Donut Charts
  • Scatter Plots & Bubble Charts
  • Histograms & Distribution Plots
  • Box Plots & Whisker Charts
  • Subplots & Multiple Figures
  • Customizing Charts - Titles, Labels, Colors & Styles
  • Module 8 Clearance Test
Module 9: Data Visualization with Seaborn 10 lessons
  • Introduction to Seaborn
  • Distribution Plots - Histplot, KDE & ECDF
  • Categorical Plots - Barplot, Countplot & Boxplot
  • Violin & Swarm Plots
  • Scatter & Regression Plots
  • Heatmaps & Correlation Matrix
  • Pair Plots & Joint Plots
  • Facet Grid & Multi-Plot Grids
  • Styling & Themes in Seaborn
  • Module 9 Clearance Test
Module 10: Dashboard Building with Streamlit 12 lessons
  • Introduction to Streamlit
  • Setting Up Streamlit Environment
  • Streamlit UI Components - Text, Headers & Layout
  • Input Widgets - Slicers, Dropdowns & Filters
  • Displaying DataFrames & Tables
  • Integrating Matplotlib & Seaborn Charts
  • Connecting Streamlit to SQL Database
  • Building a Sales Analytics Dashboard
  • Building an HR Analytics Dashboard
  • Building a Finance Analytics Dashboard
  • Deploying Streamlit Application
  • Module 10 Clearance Test
Module 11: Performance Optimization 7 lessons
  • Performance Issues & Root Causes
  • SQL Query Optimization
  • Pandas Performance Optimization Techniques
  • NumPy Vectorization vs Loops
  • Memory Management in Python
  • Optimizing Streamlit Application Performance
  • Module 11 Clearance Test
Module 12: Data Analytics 10 lessons
  • Data Analytics Overview & Types
  • Exploratory Data Analysis (EDA)
  • Descriptive Analytics & Statistical Summary
  • Diagnostic Analytics - Finding Root Causes
  • Sales & Revenue Analytics
  • Finance Analytics
  • HR & Workforce Analytics
  • Storytelling with Data
  • End-to-End Business Case Study
  • Module 12 Clearance Test
Module 13: Projects 2 lessons
  • Mentored Project
  • Capstone Project
Our Advantage

Why Choose This Course

  • Exclusively Built for Job Seekers
  • Hands-On with Real Industry Tools
  • Classroom Training, Not Online Guesswork
  • From Raw Data to Job-Ready Portfolio

Your Instructors

Leelavathi Ramesh

Leelavathi Ramesh

Business Intelligence Analyst

9 Courses

4+ years of experience as a Business Intelligence Analyst, with hands-on expertise at Variablz Technology and Schneider Electric. Statistics graduate with practical experience across Marketing, Production, and Sales Analytics.

Parthiban Kannan

Parthiban Kannan

Co-founder & Manager

17 Courses

14+ years of experience in digital transformation, leading teams of 15+ members and delivering 160+ projects for organizations like Lakshmi Machine Works, Milacron, Schneider Electric, Aatomz Research, and Variablz Technologies. AI innovator with a patent approved by the Government of India, with strong expertise in Data Science, Data Analysis, Business Intelligence, and Software Development.

Course Outcomes

What Our Students Build

Articles, projects, research papers and more — real work by our learners applied beyond the classroom.

View All Outcomes
FAQ

Frequently Asked Questions

What is the duration of this course?

The course duration is 3 to 4 months, with classes held Monday to Friday from 10:00 AM to 2:00 PM.

What are the eligibility criteria to join this course?

Any graduate from any degree is eligible, provided their degree includes Mathematics as a subject.

What tools will I learn in this course?

You will get hands-on training in SQL, Python, Pandas, NumPy, Matplotlib, Seaborn, and Streamlit.

Is this course suitable for college students or working professionals?

No. This course is exclusively designed for job seekers who are actively looking to start their career in Data Analysis.

Is this an online or offline course?

This is a completely classroom-based training program conducted at our Cuddalore location.

What topics are covered in this course?

The course covers Fundamentals, Data Extraction, Data Transformation, Data Modeling, Data Visualization, Dashboard Building, Performance Optimization, and Data Analytics.

Will I get real-world experience during the course?

Yes. This is a fully industry-oriented course where every module is designed around real business scenarios and practical projects.

Will this course help me get a job?

You can submit your query through our contact form and one of our representatives will call you soon to guide you through the enrollment process.

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