Industry Ready Data Science Course in Pondicherry
Advance your career with Code Purple Academy’s Data Science & Machine Learning program. The hands-on training approach helps you develop the ability to work with data, use machine learning techniques, and confidently solve real-world problems using modern data technologies.
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4.7 (350+ Google Reviews)
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Phone Number
How you find us ?
Current profile
Duration
4 Months
Mode
Online & Offline
Projects
5+ Industry-Grade Projects
Support
Lifetime
Duration
4 Months
Mode
Online & Offline
Projects
5+ Industry-Grade Projects
Support
Lifetime
Where Our Graduates Shine
Our alumni have successfully built careers with several leading companies in the industry, including.
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Why choose Code Purple - Pondicherry
Code Purple enables you to differentiate yourself with a powerful combination of the right skills, expert mentoring, and strong industry-focused preparation.
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Resume building that cracks ATS software
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Training by industry experts
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5hands-on projects
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Mock interviews & Group discussions
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HackerRank profile development
Santhosh
Full Stack Developer
Coimbatore, India
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LinkedIn profile
optimization
Take the first step towards your dream IT career in Pondicherry. Join Code Purple Academy’s Data Science Course in Pondicherry today!
Daily Life Clones:
Recreating Everyday Apps
for Practical Learning
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 Covered
An overview of the primary tools and technologies presented in the Data Science course, helping learners understand the methods, techniques, and workflows followed when working on real-world data science projects.
Machine Learning
Tableau
TensorFlow
Python
Scikit-Learn
MySQL
Launch Your
Data Science Career Today
Kickstart your path to a successful IT career in Pondicherry by enrolling in Code Purple Academy’s Data Science Course in Pondicherry today.
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Data Science Course
Explore our Data Science course: practical skills, real-world projects, and job-ready training.
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
Syllabus Overview
Modern syllabus with practical learning and interview preparation to make you job-ready.
Module 1: Introduction to Data Science
Learn the role of a Data Scientist and the significance of data in today's world.
Module 2: Excel
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)
Module 3: Python
- Python syntax: Variables, Data Types (int, float, string)
- Data Structures and Methods
- Control flow: if-else, for loops, while loops.
- Functions
- Basic OOPs
- Advanced OOPs
- File and Error Handling
- Modules, Packages and Libraries
Module 4: 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.
Module 5: 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.).
- 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.
Module 6: 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).
- 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.
Module 7: Statistic & Probability
Covers Central Tendency measures, variance, standard deviation, probability, key distributions, hypothesis testing, sampling, and A/B testing for data-driven decisions.
Module 8: Machine Learning
Introduces regression, classification, decision trees, random forests, clustering, PCA, ensemble methods like XGBoost, and hyperparameter tuning.
Module 9: Deep Learning & NLP
Teaches neural networks, CNNs, RNNs/LSTMs, training techniques, and NLP concepts including tokenization, embeddings, text classification.
Module 10: Capstone Project and Portfolio Development
Capstone Project: Choose a real-world dataset (e.g., sales, marketing, or customer data)
- Includes dashboards, prediction models, sentiment analysis, image classification, and recommendation systems to build industry-ready practical skills.
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.
Discover What Makes Us Unique
Key Features That Set Us Apart from the Rest
Leading Professionals
Hands-On Training
Career Guidance
Success stories from Our Students
Discover how our students transformed their skills into successful tech careers through hands-on training, mentorship, and real-world project experience.
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 understand Read 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
Here are several frequently asked questions and answers to guide you. If the information you need isn’t listed here, please feel free to contact us.
1. What is the Data Science Course offered at Code Purple Academy in Pondicherry?
During the program, students learn the core knowledge companies expect from entry-level data science candidates. This includes Python programming, statistics, data analysis techniques, machine learning fundamentals, and data visualization concepts. Instead of concentrating only on theory, the training highlights how these concepts are applied in real projects and technical interviews.
The training approach is completely practical. Learners work with real datasets, case studies, and industry-style projects similar to the tasks handled by data analysts and data scientists in real IT environments. By the end of the program, students gain strong fundamentals, hands-on experience, interview preparation, resume support, and placement assistance for roles such as Data Analyst, Junior Data Scientist, and Machine Learning Engineer.
2. How long is the Data Science course?
At the beginning of the course, students learn foundational topics such as Python programming, statistics, and data analysis. These fundamentals help beginners understand how data science works before progressing to more advanced topics. As the course continues, learners move into machine learning concepts, algorithms, and model development.
The training focuses strongly on practical learning. Students work with datasets, case studies, and real project tasks to understand how data science solutions are built in professional environments. By the end of the four months, students are ready to apply for entry-level roles and begin their careers in data science.
3. Are weekend batches not available for the Data Science Course in Pondicherry?
Data science concepts such as Python programming, statistics, and machine learning require regular revision and hands-on exercises. A weekday schedule allows students to practice concepts frequently and maintain better learning continuity without long gaps between sessions.
Weekday training also allows learners to interact regularly with trainers, clarify doubts quickly, and receive ongoing project guidance. This structured learning schedule helps students understand complex topics more effectively and complete the course within the planned timeframe.
4. Who can join this Data Science course?
College students, recent graduates, and working professionals can join the course to improve their technical knowledge and explore career opportunities in data-related roles. Even learners from non-technical backgrounds can participate because the course begins with fundamental concepts before progressing to advanced topics.
Throughout the training, students receive structured guidance that helps them understand programming, data analysis, and machine learning concepts step by step. This approach ensures that learners from different educational backgrounds can successfully develop the skills needed for entry-level data science roles.
5. What tools and technologies will I learn in the Data Science course?
During the training, students learn Python programming, data analysis methods, statistical concepts, machine learning fundamentals, and data visualization techniques. These skills allow learners to understand data patterns, build predictive models, and present insights clearly.
The program also emphasizes practical experience through exercises, datasets, and projects. By applying these tools and techniques in real scenarios, students gain the confidence needed to work on data science tasks commonly performed in professional environments.
6. Does the course include real-time projects?
Throughout the course, students work with datasets, coding exercises, and analytical tasks that help them practice the tools and techniques used in data science. These activities allow learners to explore how data is cleaned, analyzed, and interpreted in real scenarios.
In addition to exercises, students participate in project-based learning. These projects simulate real industry tasks and help learners gain hands-on experience, making it easier to understand how data science solutions are developed in professional environments.
7. Do you provide placement support after the Data Science Course?
As part of the placement support, students receive guidance in resume preparation, interview practice, and technical discussion sessions. Trainers help students highlight their project work, technical skills, and problem-solving abilities so they can present themselves confidently during job interviews.
In addition to technical training, students also receive tips on building professional profiles and preparing for common interview questions related to data science roles. This guidance helps learners understand industry expectations and improves their chances of securing entry-level positions such as Data Analyst or Junior Data Scientist.
8. What is the mode of training?
During the sessions, students learn important topics such as Python programming, data analysis, statistics, and machine learning concepts. Trainers explain each topic step by step and provide practical demonstrations so learners can understand how these concepts are applied in real scenarios.
The training also includes hands-on practice with datasets, assignments, and project work. This practical approach ensures that students develop both theoretical knowledge and practical experience required to work on real data science problems.
9. Is career guidance provided after joining the Data Science course?
Trainers guide students on important aspects such as career paths in data science, industry expectations, and the skills required for different job roles. This guidance helps learners understand how their training connects with real job opportunities in the industry.
Students also receive advice on improving their technical knowledge, preparing for interviews, and building strong project portfolios. With continuous guidance from trainers, learners can plan their career path more clearly and prepare themselves for professional opportunities in the data science domain.
10. How can I enroll in the Data Science Course in Pondicherry?
Before enrolling, prospective students can speak with the academy staff to understand the curriculum, training methodology, and learning outcomes. This interaction allows them to clarify any questions they may have about the program.
Once the enrollment process is completed, students can begin their training and start learning important data science concepts such as Python programming, data analysis, and machine learning. The structured course and practical learning approach help learners build the skills required to begin their journey in the data science field.
