Sonali Kubde
Unlock Learning Potential with Expert Online Tutors Anytime, Anywhere!……………………
Loading...
Show all photos
Sonali Kubde
Bachelors degree
/ 55 min
About your coding tutor - Sonali
I am a passionate coding tutor with over 2 years of teaching experience. Armed in masters degree, I have excelled Java and spring boot. My expertise lies in Java, spring boot. I can do the assignments for Java in limited time. I am pretty good with Jenkins and postman which goes hand in hand with Java
Sonali graduated from Mumbai University
Coding tutor specialities
Debugging
Assignment help
Homework help
Project help
Exam prep
CoTutorAI modules
Summary
Podcast
Quiz
Learnings
Flashcard
Spotlight
Zero Risk Guaranteed
15-days refund
Free tutor swap
No cancel fee
1-yr validity
24/7 support
Learner types for coding classes
Coding for Kids
Coding for Adults
Coding for School students
Coding for College students
Coding for Beginners
Coding class highlights
My teaching style is clear, adaptive, and goal-focused. I simplify complex ideas into easy-to-understand steps, using real-world examples and analogies when helpful. I adjust the pace to match your learning speed and provide just the right amount of challenge to keep you engaged without feeling overwhelmed. I encourage active thinking and questions, helping you build a strong understanding rather than just memorizing. Whether you prefer visuals, practice problems, or step-by-step explanations, I tailor the approach to suit your learning style and goals. The focus is always on making learning effective, engaging, and empowering for you.
Coding concepts taught by Sonali
The student and tutor practiced Python programming, focusing on the `input()` function and data type conversions between strings, integers, and floats. They worked through coding exercises to reinforce these concepts, and the tutor offered to send additional resources for review.
Prime Numbers
Comments and Code Organization
Loops and Conditional Logic for Prime Numbers
Data Type Conversion (Casting)
Python Input Function
The session involved a tutor and student discussing the final module of an Artificial Intelligence course titled "Model Deployment." The student expressed a need to understand the practical application and coding associated with deploying AI models, and they planned to connect later in the week to work on the associated projects after the student reviewed some introductory material.
Hands-on Learning with Notebooks
Development vs. Deployment
Model Deployment in AI
The session focused on relational database concepts, specifically one-to-one, one-to-many, and many-to-many relationships between entities. The Student practiced identifying these relationships using real-world examples and learned about cardinality as a tool for determining relationship types. As homework, the Student was assigned to create one example for each relationship type (one-to-one, one-to-many, and many-to-many).
Cardinality in Relationships
One-to-One Relationship (1:1)
One-to-Many Relationship (1:M)
Many-to-Many Relationship (M:N)
Database Representation of 'Many'
Importance of Foundational Database Concepts
The session introduced the fundamental concepts of Relational Database Management Systems (RDBMS), specifically focusing on the types of relationships between tables: one-to-one, one-to-many, and many-to-many. The student practiced identifying and understanding these relationships through examples and learned about the importance of atomicity in database design, with a plan to cover normalization and Power BI modeling in subsequent sessions.
Atomicity in Databases
Database Relationships: Many-to-Many
Database Relationships: One-to-Many
Database Relationships: One-to-One
RDBMS: Relational Database Management System
The Student revised data analysis techniques using Pandas, focusing on data cleaning and preparation. They worked through a pre-existing notebook on Uber data, converting data types, handling missing values, and extracting date components. The next session will cover Matplotlib and Seaborn for data visualization.
Data Shape vs. Data Insights
Data Type Conversion: Datetime
Feature Engineering: Extracting Date Components
Handling Missing Values (NaNs)
Data Correlation with Heatmaps
The Student and Tutor reviewed cross-validation techniques, including different types like k-fold and stratified cross-validation. They also discussed methods for handling imbalanced datasets such as over-sampling and under-sampling. The Tutor assigned further review of sampling techniques and model tuning in preparation for the upcoming quiz.
Cross Validation
Holdout Validation
Leave-One-Out Cross Validation (LOOCV)
K-Fold Cross Validation
Stratified Cross Validation
Imbalanced Data Handling
SMOTE (Synthetic Minority Over-sampling Technique)
Approach & tools used by coding tutor
Xcode
Git & GitHub
Postman
Bitbucket
Visual Studio Code
Programming tutors on Wiingy are vetted for quality
Every tutor is interviewed and selected for subject expertise and teaching skill.