Professional Data Science Course in Karur.
Strengthen your professional journey with Code Purple Academy’s Data Science & Machine Learning course. This practical training method builds your skills in analyzing data, applying ML techniques, and tackling real-world challenges using modern data-driven tools and technologies.
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4.7 (350+ Google Reviews)
I'M INTERESTED
Name
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
Many of our past students are now working in well-established top companies, including.
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Why choose Code Purple - Karur
Code Purple equips you to rise above the crowd with a balanced mix of practical abilities, professional guidance, and readiness for real industry demands.
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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 Karur. Join Code Purple Academy’s Data Science Course in Karur 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
A brief introduction to the key tools and technologies included in the Data Science course, allowing learners to understand the methods, techniques, and workflows used during real-world data science project development.
Machine Learning
Tableau
TensorFlow
Python
Scikit-Learn
MySQL
Launch Your
Data Science Career Today
Start shaping your future in the IT industry by joining Code Purple Academy’s Data Science Course in Karur 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 have achieved their career goals with the support and training from our 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 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
Below are some commonly asked questions along with their answers to assist you. If you’re unable to find what you’re searching for, feel free to reach out to us.
1. What is the Data Science Course offered at Code Purple Academy in Karur?
The curriculum covers essential skills expected from entry-level data science professionals. Students learn Python programming, statistical concepts, data analysis methods, machine learning basics, and data visualization techniques. The course emphasizes understanding how these skills are applied in real-world industry situations rather than focusing only on theoretical explanations.
Learning in this program is highly practical. Students work on datasets, industry-based case studies, and live project scenarios that resemble real IT workflows. By completing the course, learners develop strong technical foundations, practical project experience, and interview preparation support, helping them confidently pursue roles such as Data Analyst, Junior Data Scientist, or Machine Learning Engineer.
2. How long is the Data Science course?
The course begins with fundamental topics like Python programming, statistical methods, and data analysis techniques. These concepts build the base required for understanding machine learning algorithms and predictive modeling later in the program.
Throughout the course, students work on hands-on exercises, case studies, and real-time projects using practical datasets. This training approach helps learners develop analytical thinking and real problem-solving abilities. By completing the program, students gain the knowledge and experience required to pursue entry-level data science roles.
3. Are weekend batches not available for the Data Science Course in Karur?
Learning data science requires regular coding practice, data analysis exercises, and continuous project work. Conducting sessions during weekdays ensures that learners stay engaged with the concepts and improve their skills steadily.
This weekday model also allows trainers to guide students more effectively through assignments and projects. As a result, learners build stronger technical foundations and complete the training more efficiently while preparing for industry roles.
4. Who can join this Data Science course?
Students who are currently studying, recent graduates seeking job opportunities, and working professionals planning a career transition can enroll in the program. Since the course starts with basic concepts, even beginners without prior programming knowledge can learn comfortably.
The training provides step-by-step learning, practical exercises, and project experience to help students understand real industry workflows. This makes the program accessible for learners who want to build a strong foundation and pursue a career in data science.
5. What tools and technologies will I learn in the Data Science course?
Learners gain experience in python programming, statistical analysis, machine learning concepts, and data visualization tools. These skills help them analyze large datasets, identify trends, and develop models that support data-based decision-making.
Hands-on projects and real-world datasets are included throughout the training. This practical exposure helps students understand how data science techniques are applied in real industry situations and prepares them for entry-level data science positions.
6. Does the course include real-time projects?
During the training, learners practice Python programming, data analysis, and machine learning techniques using real datasets. These exercises help students understand how analytical methods are applied to solve real-world problems.
Project-based learning is also included in the curriculum. By working on industry-style projects, students gain experience in handling data, building models, and presenting insights, which helps them develop the practical skills required in data science roles.
7. Do you provide placement support after the Data Science Course?
Placement assistance includes resume building, interview preparation, and technical guidance. Trainers work closely with students to help them present their projects effectively and improve their confidence while attending interviews.
Along with technical knowledge, students also receive advice on professional communication and interview strategies. This support helps learners understand how recruitment processes work and prepares them to apply for roles such as Data Analyst, Junior Data Scientist, or other data-related positions
8. What is the mode of training?
The course covers essential topics including Python programming, statistical analysis, data visualization, and machine learning techniques. Trainers focus on explaining how these tools and methods are used to analyze data and generate insights.
Students also participate in practical activities such as working with datasets, solving analytical problems, and developing small projects. This combination of theoretical explanation and practical learning helps students gain a strong understanding of data science workflows.
9. Is career guidance provided after joining the Data Science course?
During the training program, instructors share insights about industry trends, job roles, and the skills required to succeed in data-related careers. This helps students gain a clear understanding of how their learning can translate into professional opportunities.
Students also receive guidance on building strong project portfolios, improving technical communication, and preparing for interviews. This support helps learners stay focused on their career goals and develop the confidence required to pursue roles in the data science industry.
10. How can I enroll in the Data Science Course in Karur?
Students can speak with the academy team to learn about the course syllabus, training format, and class schedule. This discussion helps them understand how the program can support their career goals in the field of data science.
After completing the admission process, students can start attending training sessions where they learn key concepts such as Python programming, data analysis techniques, and machine learning fundamentals through structured lessons and practical exercises.
