Advanced Data Analytics Course with Practical Projects
Kickstart your career in the fast-growing data field with our Data Analytics Course inTrichy. The program helps you understand how to collect, manage, and examine data using tools like Excel, SQL, Python, Tableau, and Power BI. The training is designed with practical sessions so you can work with real datasets and build clear dashboards. Even beginners can easily follow the step-by-step learning process. After completing the course, you will have the knowledge required to begin a career as a data analyst.
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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
Many of our learners have launched their careers with well-known companies, taking up roles in analytics, data analysis, and technology-driven departments
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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
This section introduces the important tools and technologies involved in data analytics, explaining their role across the entire project lifecycle, including data collection, data cleaning, analysis, and presenting useful insights through 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
Explore the success stories of our students who have accomplished their career ambitions after completing our data analytics training 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
Review the frequently asked questions listed below to know more about the course structure and learning approach. If you need more information, you can contact us anytime
1. What is the Data Analytics Course offered in Trichy?
Students learn important tools including Excel, SQL, Power BI, and Python, which are commonly used by data analysts. Through guided exercises and practical examples, learners understand how to organize data, build reports, and create dashboards that explain business performance.
The goal of this program is to help students gain confidence in working with data and preparing for analytics roles. After completing the course, learners are able to analyze datasets independently, present meaningful insights, and attend interviews for positions such as Data Analyst or Business Intelligence professional.
2. What is Data Analytics and why should I learn it?
In Trichy, gaining data analytics knowledge is considered a valuable career step because organizations depend on data professionals to analyze performance and identify opportunities for improvement. Data analysts play a key role in presenting information through reports and visual dashboards.
Learning this skill can significantly improve career prospects. It not only increases job opportunities but also develops logical thinking and analytical abilities. As businesses continue to rely on data insights, data analytics remains a highly valuable skill in the modern job market.
3. Who can join the Data Analytics course in Trichy?
Professionals who wish to transition into data-focused roles such as Data Analyst or Business Analyst can also enroll in the course. The training program focuses on practical learning so that learners gain real-world knowledge rather than just theoretical information.
No advanced technical background is necessary to start the course. The training begins with fundamental concepts and gradually introduces advanced tools. This approach allows beginners to learn comfortably and progress toward becoming skilled data analysts.
4. Do I need coding knowledge to learn Data Analytics?
The learning journey usually begins with tools like Excel and SQL, which help students understand how to organize and examine data. Once learners become comfortable with these tools, the course introduces Python in a simple and practical manner for analyzing datasets.
The aim is not to turn students into software developers but to teach the coding necessary for data analysis tasks. With clear explanations, practice exercises, and trainer support, learners gradually gain confidence and develop the skills required to work in the analytics field.
5. What tools will I learn in this course?
Once students are comfortable with Excel, they are introduced to SQL, a database language used to access and organize large datasets. This tool helps learners understand how data is stored and retrieved in professional environments.
Later in the program, Power BI is taught for building interactive dashboards and visual reports. The course also includes an introduction to Python for data analysis. These tools together form a strong foundation for anyone aiming to begin a career as a data analyst.
6: Is this Data Analytics course job-oriented?
Students learn how to work with datasets, build visual reports, and interpret data using practical tools. The training also includes assignments and projects that simulate real-world data analysis tasks.
By the time students complete the program, they gain both technical knowledge and practical experience. This preparation helps them confidently apply for positions such as Data Analyst or Business Analyst in the growing analytics industry.
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?
Students receive support in preparing resumes that highlight their project experience and technical skills. Trainers also guide learners on how to explain their analytical work and demonstrate their understanding during interviews.
Practice interviews are conducted to help students become familiar with real interview situations. Constructive feedback is provided so they can improve their confidence and communication. This guidance helps learners approach job opportunities in the analytics field more effectively.
9. Will I receive a certificate after completing the course?
The certificate represents the skills developed during the course, including working with Excel, SQL databases, Power BI dashboards, and basic Python for data analysis. It serves as proof of structured learning and practical exposure.
However, the true value comes from the knowledge and confidence students gain while working on real data tasks. When combined with hands-on experience and project work, the certificate strengthens a candidate’s profile when applying for analytics roles.
10. How do I enroll in the Data Analytics course?
Prospective students can discuss the course structure, training modules, batch timings, and other important details before completing their registration. This helps them understand how the program will support their career goals.
Once the registration is completed, students can join the next available batch and begin their training. The course provides structured learning, practical assignments, and hands-on experience to help learners build strong analytics skills.
