J P Nagar, Bangalore 
501 per hour Details verified of Madhushree✕
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University of Essex 2024
Master of Science (M.Sc.)
J P Nagar, Bangalore, India - 560078
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Class Location
Online class via Zoom
Student's Home
Tutor's Home
BTech Computer Science subjects
Machine Learning, Object Oriented Programming & Systems, Data Structures and Algorithms, Software Project Management, Information Retrieval, Artificial Intelligence, Software Engineering and Architecture, Programming in C#
BTech Branch
BTech Computer Science Engineering
Type of class
Regular Classes, Crash Course
Class strength catered to
One on one/ Private Tutions, Group Classes
Taught in School or College
No
Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
1
Data science techniques
Machine learning, Artificial Intelligence, Python
Teaching Experience in detail in Data Science Classes
I have experience teaching and mentoring Data Science at both postgraduate and undergraduate levels, with a strong focus on building foundational understanding and practical application. My teaching approach emphasizes making complex concepts accessible, especially for learners transitioning from non-technical backgrounds. I have delivered structured sessions covering core Data Science topics including data types, data preprocessing, exploratory data analysis (EDA), data visualization, and introductory machine learning. I guide students through the complete data science workflow—from problem definition and data collection to cleaning, analysis, modeling, and interpretation of results. I provide hands-on training in Python using libraries such as NumPy, Pandas, Matplotlib, and Scikit-Learn, ensuring students gain practical coding experience alongside theoretical knowledge. I have also supported learners through lab sessions, coursework, and case studies, helping them debug code, understand model performance metrics, and improve analytical thinking. My mentoring style focuses on clarity, patience, and structured explanation of statistical concepts, including regression, classification, clustering, and model evaluation. Additionally, I incorporate real-world examples from healthcare, finance, and public datasets to help students understand industry applications. I encourage version control practices using GitHub and promote reproducible, well-documented work. My goal is to build both technical confidence and strong problem-solving skills in Data Science.
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Class Location
Online class via Zoom
Student's Home
Tutor's Home
BTech Computer Science subjects
Machine Learning, Object Oriented Programming & Systems, Data Structures and Algorithms, Software Project Management, Information Retrieval, Artificial Intelligence, Software Engineering and Architecture, Programming in C#
BTech Branch
BTech Computer Science Engineering
Type of class
Regular Classes, Crash Course
Class strength catered to
One on one/ Private Tutions, Group Classes
Taught in School or College
No
Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
1
Data science techniques
Machine learning, Artificial Intelligence, Python
Teaching Experience in detail in Data Science Classes
I have experience teaching and mentoring Data Science at both postgraduate and undergraduate levels, with a strong focus on building foundational understanding and practical application. My teaching approach emphasizes making complex concepts accessible, especially for learners transitioning from non-technical backgrounds. I have delivered structured sessions covering core Data Science topics including data types, data preprocessing, exploratory data analysis (EDA), data visualization, and introductory machine learning. I guide students through the complete data science workflow—from problem definition and data collection to cleaning, analysis, modeling, and interpretation of results. I provide hands-on training in Python using libraries such as NumPy, Pandas, Matplotlib, and Scikit-Learn, ensuring students gain practical coding experience alongside theoretical knowledge. I have also supported learners through lab sessions, coursework, and case studies, helping them debug code, understand model performance metrics, and improve analytical thinking. My mentoring style focuses on clarity, patience, and structured explanation of statistical concepts, including regression, classification, clustering, and model evaluation. Additionally, I incorporate real-world examples from healthcare, finance, and public datasets to help students understand industry applications. I encourage version control practices using GitHub and promote reproducible, well-documented work. My goal is to build both technical confidence and strong problem-solving skills in Data Science.
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Bangalore
