Career Focused Data Analytics Course with Practical Learning
Start your journey in the data field with our Data Analytics Course in Madurai. The course teaches you how to work with data using tools such as Excel, SQL, Python, Tableau, and Power BI. Through hands-on training, you will learn to process information, create reports, and build useful dashboards. The lessons are beginner-friendly and explained step by step. After completing the training, you will be prepared to pursue a data analyst role and discover career opportunities in Madurai and beyond.
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Duration
90 Days
Fee
INR 29,999/-
Mode
Online & Offline
Skill Level
Just Beginner
Duration
90 Days
Mode
Online & Offline
Fee
INR 29,999/-
Skill Level
Just Beginner
Trusted by Industry Leaders
Our students have successfully started their professional journeys in top organizations, contributing to analytics, data-focused, and technology-based teams across various industries
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Your Personal Learning Hub
Explore your own student portal — track progress, practice daily, stay organized, and manage your entire learning journey in one place.
Course Progress
Track every module, lesson, and milestone with clear
visual progress indicators.
Performance & Support
View your score dashboard, track
improvement, and raise grievances
for quick support.
Practice Zone
Sharpen your skills with coding challenges, MCQs, and regular practice tests.
Support Beyond the Classroom
Tools You'll Use
Here is a summary of the essential tools and technologies used in data analytics, describing how they are applied during the project workflow, from gathering and preparing data to analyzing results and producing clear reports
MS Excel
Python
SQL
Tableau
Power BI
In Partnership with
Working with top colleges to provide essential full stack development training for student success.
ANJAC, Sivakasi
SFRC, Sivakasi
PSG, Coimbatore
In Partnership with
Working with top colleges to provide essential full stack development training for student success.
ANJAC, Sivakasi
SFRC, Sivakasi
PSG, Coimbatore
Detailed Syllabus
Modern syllabus with practical learning and interview preparation to make you job-ready.
Week 1: Introduction to Data Analytics
- In Introduction to Data Analytics, we learn the basics of data types, data collection, cleaning, exploratory analysis, visualization, and the four types of analytics. We also get an overview of tools like Python, SQL, and dashboards used to turn raw data into meaningful insights.
Week 2: Excel Basics and Intermediate Functions
Excel Basics:
- Workbooks, Worksheets, Cells, and Ranges.
- Basic functions: SUM, AVERAGE, COUNT, MIN, MAX.
- Sorting, Filtering, and Formatting Data.
Intermediate Excel:
- Conditional Formatting, Data Validation.
- Lookup Functions: VLOOKUP, HLOOKUP, INDEX, MATCH.
- Working with Dates and Time functions
- Basic Charts and Graphs (Bar, Line, Pie)
Week 3: Python Basics and Data Structures
- Python syntax: Variables, Data Types (int, float, string)
- Data Structures and Methods
- Control flow: if-else, for loops, while loops.
- Functions
Week 4: Python Basic and Advanced OOPs Concept
- Basic OOPs
- Advanced OOPs
- File and Error Handling
- Modules, Packages and Libraries
Week 5: Pandas for Data Manipulation
- Pandas Basics: DataFrames, Series, loading data from CSVs and Excel.
- Data Cleaning: Handling missing values, duplicates, and transforming columns.
- Data Transformation: Filtering, grouping, and aggregating data.
- Data Visualization with Matplotlib & Seaborn: Basic charts (line, bar, scatter) and customizing plots.
Week 6: Intermediate SQL
- Introduction to relational databases and SQL.
- Basic SQL commands: SELECT, FROM, WHERE, ORDER BY.
- Filtering Data with AND, OR, NOT, and comparison operators.
- Aggregation Functions: COUNT(), AVG(), SUM(), MIN(), MAX().
- Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN.
- Subqueries: SELECT within SELECT.
- GROUP BY and HAVING: Aggregating data by groups.
- Advanced Filtering: Working with LIKE, IN, and wildcards.
- Data Cleaning: Handling NULL values and duplicates.
Week 7: Getting Started with Tableau
- Installing Tableau and connecting to data sources (Excel, SQL, etc.).
- Data Preparation in Tableau: Cleaning, filtering, and transforming data.
- Basic Visualization Types: Bar charts, line charts, scatter plots, and pie charts.
- Formatting and customizing visualizations (titles, labels, colors, etc.).
Week 8: Advanced Tableau Visualizations and Dashboards
- Calculations in Tableau: Basic calculated fields (e.g., profit margins, growth rates).
- Table Calculations: Running totals, percent of total, moving averages.
- Building Interactive Dashboards: Filters, parameters, and dynamic actions.
- Storytelling with Data: Creating data-driven narratives and dashboards.
Week 9: Introduction to Power BI
- Installing Power BI and connecting to data sources (Excel, SQL, web, APIs).
- Power Query for Data Transformation: Cleaning and reshaping data before analysis.
- Basic Visualization Types in Power BI: Bar, line, pie charts, maps.
- Introduction to DAX (Data Analysis Expressions): Basic calculations (e.g., sum, average, and count).
Week 10: Advanced Power BI Features
- Data Modeling: Relationships between tables, star schema, fact and dimension tables.
- Advanced DAX: Calculated columns, measures, and time intelligence functions.
- Building and customizing Dashboards: Filters, slicers, drill-through actions.
- Publishing and Sharing Reports: Export to PDF, share via Power BI Service.
Week 11: Integrating Python, SQL, Excel, Tableau, and Power BI
- Integrating Tools: Importing data from SQL and Excel into Python, Tableau, and Power BI.
- Data Pipeline: Understanding how to clean and preprocess data in Python and SQL, then visualize and report it in Tableau/Power BI.
- Automating workflows: Using Python scripts or Excel macros to automate repetitive tasks.
- End-to-End Project: Solving a real-world problem using the entire toolset.
Week 12: Capstone Project and Portfolio Development
Capstone Project: Choose a real-world dataset (e.g., sales, marketing, or customer data)
- Clean and preprocess the data (using Python or SQL).
- Analyze the data and generate insights.
- Create a dynamic report or dashboard (using Tableau or Power BI).
Portfolio Creation: Upload your projects to GitHub, LinkedIn, or a personal website.
- Write clear documentation for each project, explaining your process and insights.
- Highlight the tools and techniques used in each project.
Success stories from Our Students
Discover how our learners have reached their career milestones through the support and training provided in our data analytics program
Dharanya Selvaraj
Accenture
In the Information Technology field, staying updated with current skills is crucial, and Code Purple Academy ensured I was well-prepared.Read More
Shanjana Suresh
Billion Face
Code Purple Academy helped me learn new skills and coding languages while also giving me valuable insight into the IT sector.Read More
Sri Hari
Coastal Aquaculture Research Institute Pvt. Ltd
Joining Code Purple Academy has been a game-changer for me. I was able to stay updated with the latest trends in the development field.Read More
Kishore
Billion Face
The Full Stack Development course at Code Purple Academy provided me with a solid foundation in both front-end and back-end technologies.Read More
Subash
ResultueTechno
Code Purple Academy provided exceptional mentor support, daily tasks, and updates, which kept me on track throughout my learning journey.Read More
Sai
TCS
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Coming from an ECE background, Code Purple Academy helped me transition into coding, making me well-versed in Read More
Siva
Renault Nissan Technology & Business Centre India
Code Purple Academy played a significant role in securing my job at Renault Nissan Technology & Business Centre India.Read More
Andrea Lincy
Haashtag HSI Pvt Ltd
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Code Purple Academy played a key role in helping me secure my position at Haashtag HSI Pvt Ltd.Read More
S. Mano Priya
Brand Mindz Global Technology
I’m truly grateful for the valuable learning experience I gained through the Front-End & UI/UX Design course at Code Purple Academy.Read More
Amuthapriya K
Slash Lab
My journey with the Code Purple Full Stack Development course was very useful and confidence-building.Read More
Abiilesh
Quest global
Code Purple Academy’s Data Analytics program helped me build strong analytical skills and understand how to work with real-world data.Read More
S.Nandhakumar
Gamantic
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The Full Stack Development course at Code Purple Academy helped me understand how modern websites are built from start to finish.Read More
Harish T
Ascend Technologies
My experience with the Code Purple Full Stack with Python course was highly beneficial. The training helped me understandRead More
Sathya Sri
Stutzen Technologies
My experience with the Code Purple Full Stack with Python course was highly beneficial. The training helped me understand Read More
FAQ's
Explore the commonly asked questions below to understand more about the course format and training process. Feel free to contact us anytime if you need additional help.
1. What is the Data Analytics Course offered in Madurai?
During the program, learners are introduced to essential tools such as Excel, SQL, Power BI, and Python. These tools help students understand how data is gathered, cleaned, analyzed, and presented through meaningful reports and dashboards. Each topic is taught step by step so that beginners can easily follow the learning process.
The main purpose of this training is to help students become job-ready in the field of data analytics. By the end of the course, learners will be able to work with datasets, interpret information clearly, and present insights effectively. This prepares them to confidently apply for roles such as Data Analyst, Business Analyst, or Power BI Developer.
2. What is Data Analytics and why should I learn it?
In Madurai, learning data analytics can open many career opportunities because companies rely heavily on data to understand customers, improve performance, and plan future strategies. Data analysts help organizations by transforming complex information into clear reports and visual dashboards.
Choosing to learn data analytics is beneficial because it strengthens analytical thinking and problem-solving skills. As companies continue to depend on data-driven decision making, professionals with analytics skills are in high demand across multiple industries.
3. Who can join the Data Analytics course in Madurai?
Working professionals who are interested in switching careers into data analytics can also benefit from this training program. The course is designed to help learners understand important tools and develop analytical thinking that companies look for when hiring data professionals.
Even individuals without programming experience can join because the course begins with basic concepts and gradually progresses to advanced topics. With proper guidance and consistent practice, students can confidently develop the skills required for analytics roles.
4. Do I need coding knowledge to learn Data Analytics?
As the training progresses, learners are slowly introduced to basic Python for data analysis. However, the focus is not on becoming a programmer but on understanding how simple coding can help in working with large datasets more efficiently. Trainers explain each concept in a practical way so students can learn comfortably.
With consistent practice and proper guidance, even non-technical students can understand the tools used in data analytics. The course is designed to help learners develop logical thinking and analytical skills so they can confidently pursue roles such as Data Analyst or Business Analyst.
5. What tools will I learn in this course?
After building a strong foundation with Excel, students move on to SQL, which is used to manage and retrieve data from databases. SQL helps learners understand how large datasets are stored and how specific information can be extracted efficiently.
The course also includes Power BI for creating visual dashboards and reports that explain data trends clearly. In addition, basic Python is introduced to help students analyze data using simple scripts. By learning these tools together, students gain practical knowledge required for entry-level analytics roles.
6. Is this Data Analytics course job-oriented?
Instead of focusing only on theoretical concepts, the program includes practical exercises, assignments, and project work. Students learn how to analyze datasets, create dashboards, and present insights clearly using tools like Excel, SQL, Power BI, and Python.
The goal of this training is to prepare students for professional opportunities in the analytics field. By the end of the course, learners develop the technical knowledge and confidence required to apply for entry-level roles in data analytics.
7. How long does it take to complete the Data Analytics course?
During these three months, students gradually learn tools such as Excel, SQL, Power BI, and basic Python. Each topic includes practical exercises and assignments that help reinforce the learning process.
The aim is not simply to complete the syllabus but to ensure students feel confident using the tools independently. By the end of the training, learners gain enough knowledge and practice to start preparing for analytics job opportunities.
8. Will I get placement support after completing the course?
As part of this support, students receive guidance on creating professional resumes, explaining their projects clearly, and preparing for technical interviews. Trainers help learners understand the types of questions commonly asked in data analytics interviews.
Mock interview sessions are also conducted so students can practice answering questions confidently. Feedback is provided to help them improve their performance and communication skills. This support helps learners feel prepared when applying for entry-level roles such as Data Analyst or Business Analyst.
9. Will I receive a certificate after completing the course?
The certification indicates that students have gained practical knowledge in tools such as Excel, SQL, Power BI, and Python. It also reflects their participation in assignments, exercises, and project work during the course.
While the certificate is valuable for a resume, the most important factor is the knowledge and practical skills gained during the training. When students combine their certificate with strong project experience, it becomes easier for them to demonstrate their capabilities during interviews.
10. How do I enroll in the Data Analytics course?
During the initial discussion, students can learn about the three-month course duration, syllabus, training schedule, and other important details. This is also a good opportunity to clarify any questions regarding the program.
After deciding to join, students can complete the registration process to confirm their seat in the upcoming batch. Once enrolled, they can start learning data analytics through structured training, practical exercises, and guided projects.
