My name is Preetha, and I am a dedicated Python and Data Science Trainer with strong hands-on expertise in Python programming, Machine Learning, Web Development, and Backend Development. I have trained school students, engineering students, and working professionals who want to upgrade their skills — even those from non-technical backgrounds.

My sessions focus on clarity, hands-on coding, structured assignments, and doubt-solving support. I emphasize practical implementation, real-time datasets, and portfolio development. My goal is to make complex concepts simple, interactive, and career-oriented through real-time projects.

Classes are available in English and Tamil, online with flexible scheduling options. I am committed to helping learners build strong technical foundations and advance confidently in the field of Python and Data Science.

Course Summary

This course is designed to provide strong conceptual clarity combined with practical implementation using real-world datasets. Students will gain hands-on experience in Python programming, data analysis, data visualization, statistics, and machine learning algorithms. The program includes end-to-end projects to help learners build a strong portfolio and gain job-ready skills.

With step-by-step guidance, doubt-clearing sessions, assignments, and project support, this course ensures practical learning rather than just theoretical knowledge. Whether you are a student, job seeker, or working professional, this program will help you confidently start your journey in Data Science.

Course Curriculum

This comprehensive curriculum covers Python programming, data analysis, visualization, machine learning, and real-time projects to help learners build industry-ready skills through hands-on training.

Module 1: Python Programming Fundamentals

• Core Python
• Object-Oriented Programming
• NumPy, Pandas, and Matplotlib
• Data handling basics

Module 2: Data Analysis with Python

• Data cleaning
• Data wrangling
• Exploratory Data Analysis (EDA)
• Working with real-world datasets

Module 3: SQL for Data Handling

• Database concepts
• Writing SQL queries
• Working with MySQL
• Data extraction and transformation

Module 4: Data Visualization with Python

• Data storytelling
• Creating charts using Matplotlib
• Advanced visualizations with Seaborn

Module 5: Data Visualization with BI Tools

• Dashboard creation using Microsoft Power BI
• Reporting with Tableau
• Building interactive business dashboards

Module 6: Machine Learning Fundamentals

• Introduction to Machine Learning concepts
• Types of Machine Learning
• Model evaluation techniques

Module 7: Supervised Learning Algorithms

• Linear Regression
• Logistic Regression
• Decision Trees
• Model training and evaluation using Scikit-learn

Module 8: Unsupervised Learning

• Clustering
• Dimensionality reduction
• Practical implementation

Module 9: Statistics & EDA

• Statistical foundations for data science
• Hypothesis testing basics
• Probability concepts
• Feature engineering

Module 10: Real-Time Projects

• End-to-end data science projects
• Model deployment basics
• Portfolio development
• Industry use-case simulations

Outcome: Upon completion, students will be able to confidently analyze real-world datasets, build and evaluate machine learning models, create interactive dashboards, and build job-ready portfolio projects.

Who Can Join?

• College Students

• Job Seekers

• Working Professionals

• Career Switchers

Benefits - What Students Will Gain?

• Strong Python & Data Science foundation

• Hands-on practical training

• Real-time datasets

• Industry-oriented projects

• Resume guidance

• Interview preparation support