Advanced Data Science & Machine Learning Course Training
Our data science & machine learning course is designed to help you learn Python, MySQL, and machine learning with real-time practice, not just theory. You’ll work on real-world projects like sales forecasting and customer data analysis to understand how companies actually use data. By the end of the training, you’ll have practical skills, project experience, and job-ready knowledge to start a strong career in data science and machine learning.
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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 former students have successfully built their careers by securing positions in well-known and highly reputed organizations across the industry.
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Why choose Code Purple - Erode
With code purple, you gain the ideal mix of practical skills, expert support, and industry-focused training that helps you stand out from the crowd.
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Resume building that cracks ATS software
.02
Training by industry experts
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5hands-on projects
.04
Mock interviews & Group discussions
.05
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 Erode. Join Code Purple Academy’s Data Science Course in Erode 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 essential tools and technologies used in data science, explaining how they are applied throughout the project lifecycle, from collecting and cleaning data to analyzing information and building predictive models.
Machine Learning
Tableau
TensorFlow
Python
Scikit-Learn
MySQL
Launch Your
Data Science Career Today
Start moving towards your dream career in the IT field in Erode by joining code purple academy’s data science course in erode 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
We have listed some important questions and answers to help you understand the course clearly. For additional details, feel free to reach out to our team.
1. What is included in a Data Science & Machine Learning Course?
You will start by understanding data collection, data cleaning, and basic statistics. Then we move to hands-on coding using Python, which is one of the most in-demand skills in the data science industry. You will also learn how to store and manage structured data using MySQL. Step by step, I guide you in building machine learning models for prediction, classification, and trend analysis. You won’t just watch - you will practice daily and build real projects.
By the end of this data science and machine learning training, you will know how to analyze datasets, build predictive models, and present insights clearly. This course is designed to make you job-ready with practical skills, strong fundamentals, and the confidence to attend interviews and handle real-world data problems.
2. Is this Data Science & Machine Learning course suitable for beginners?
Throughout this data science and machine learning training program, you will learn how to handle real-world datasets, understand data analysis techniques, and build predictive models that businesses actually use. The course focuses on practical implementation, not just theory, so you gain hands-on experience in data cleaning, visualization, and model building. This makes it suitable for freshers, career switchers, and professionals looking for high-demand skills in the data science field.
By the end of the course, you will have the confidence to work on live projects, attend technical interviews, and apply for entry-level data science and machine learning job roles. With structured guidance, practical assignments, and industry-relevant examples, this beginner-friendly data science course helps you become job-ready and future-proof your career in the growing analytics industry.
3. What are the career opportunities after completing the Data Science & Machine Learning Course?
The skills you learn here - data cleaning, exploratory analysis, visualization, and predictive modeling - are highly sought after, even by small businesses and startups that want to make decisions based on insights rather than guesswork. By applying these techniques in real-world examples, you not only gain technical expertise but also learn how to present findings clearly so that managers and stakeholders can act on them immediately.
With hands-on projects, practical exercises, and exposure to live datasets, this course prepares you to step confidently into roles that require analytical thinking, problem-solving, and machine learning implementation. By the end of the training, you’ll be fully equipped to handle live projects, contribute to real business solutions, and build a strong, rewarding career in data science and machine learning.
4. How long does it take to complete a Data Science & Machine Learning training program?
By the end of 4 months, you will be able to handle real datasets, build your own machine learning models, and present insights clearly, giving you the skills and confidence to step into entry-level roles in data science and machine learning.
5. Do I need prior coding experience to join the Data Science & Machine Learning Course?
Practical examples make learning easy and relatable. For instance, you might analyze sales data from a small business to predict peak demand periods or study student performance to identify patterns and trends. These exercises help you understand how coding and machine learning are applied in real-world situations.
By the end of the course, you will be able to handle datasets confidently, write Python scripts, and build predictive models from scratch, giving you the skills, hands-on experience, and confidence needed to start a career in data science and machine learning, even if you have no technical background.
6. What tools and technologies will I learn?
Alongside this, you will get hands-on experience with popular machine learning libraries that allow you to create predictive models, perform classification, regression, and clustering, and identify patterns hidden within data. For instance, you could build models to forecast sales trends, analyze customer behavior, or detect patterns in student performance, giving you practical exposure to real-world applications. By the end of the course, you will have the skills to work with live datasets, implement machine learning solutions, and deliver insights that can drive data-backed decisions, making you job-ready in the growing field of data science and machine learning.
7. What is the mode of training?
The training focuses on active participation, so you’ll be coding, exploring datasets, and solving problems throughout the course, rather than just watching demonstrations. This mode of training is ideal for beginners, freshers, and working professionals alike, helping you gain industry-ready skills, build a strong project portfolio, and confidently step into data science and machine learning roles in any data-driven organization.
8. Is career guidance provided after joining?
In addition, the program provides guidance on choosing the right career path, whether it’s as a Data Analyst, Machine Learning Engineer, or Business Intelligence Developer, and emphasizes building a strong project portfolio that highlights real-world problem-solving skills. This combination of mentorship, hands-on experience, and strategic advice ensures you are well-prepared to enter the data science and machine learning job market, giving you a competitive edge and boosting your chances of landing your first role in this growing industry.
9. Is Data Science a good career option?
With roles like Data Analyst, Data Scientist, Machine Learning Engineer, and Business Intelligence Developer in high demand, a career in data science provides not only competitive salaries but also long-term growth and the chance to work with the latest tools and technologies. For those looking to build a future-proof career in a data-driven world, gaining hands-on skills, working on live projects, and developing a strong analytical mindset through training can open doors to exciting opportunities across industries.
10. How can I enroll in the Data Science course?
Throughout the course, you will work on real-world datasets, such as analyzing sales trends for small businesses, predicting customer behavior, or identifying patterns in student performance, making it easy to understand how data science and machine learning are applied in practical scenarios. By the end of the program, you will have the skills, confidence, and project experience needed to handle live data projects and step into entry-level roles in data science, analytics, or machine learning, giving you a strong foundation for a career in this rapidly growing field.
