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Dr. Gurinderjeet Kaur

Hands-on Computer Science tutor with engaging, problem-solving lessons

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Private tutor - Dr. Gurinderjeet Kaur

Doctorate degree

Rated 5 out of 5 stars.
★★★★★
Popular
Highly skilled & top-rated
86 ratings
Ratings

Dr. Gurinderjeet - Know your tutor

Hello, I am Dr. Gurinderjeet Kaur, a dedicated computer science educator with a Doctorate in Computer Science Engineering. I simplify complex concepts and emphasize a hands-on learning approach, guiding students through coding exercises and real-world projects. My goal is to help students build practical skills, confidence, and critical thinking. I specialize in Computer Science, CSS, Databases, HTML, Java, JavaScript, Matlab, Python, R, SQL, Artificial Intelligence, Microsoft Excel, C, C++, and Coding for Kids. Additionally, I teach Mathematics and Science up to grade 10 level. Whether you're a school student, a college learner, or a professional, I tailor lessons to fit your level. Additionally, I can also teach Mathematics and Science subjects up to grade 10 level. My teaching approach in these subjects emphasizes clarity of concepts, with a focus on making abstract theories understandable through real-world examples and practical exercises. I tailor lessons to the learning pace of each student, ensuring that they grasp every concept fully before moving on. My teaching is interactive, encouraging curiosity and active participation. I focus on helping students apply their knowledge practically, fostering problem-solving abilities, and creating a supportive environment where they feel comfortable asking questions. Tailoring Learning for Every Level Whether you are a school student, college student, or a professional looking to upskill, I can cater to learners at all levels. I have experience teaching students with varying degrees of expertise and can adapt my teaching style to suit their individual needs.

Meet Dr. Gurinderjeet

Dr. Gurinderjeet graduated from Thapar Institute of Engineering and Technology India

Dr. Gurinderjeet graduated from Thapar Institute of Engineering and Technology India
Dr. Gurinderjeet graduated from Thapar Institute of Engineering and Technology India

Programming tutor specialities

Project help icon

Project help

Test prep icon

Test prep

Debugging icon

Debugging

Common Core State Standards - CCSS (USA) icon

Common Core State Standards - CCSS (USA)

Next Generation Science Standards - NGSS (USA) icon

Next Generation Science Standards - NGSS (USA)

Australian Curriculum (AU) icon

Australian Curriculum (AU)

New Zealand Curriculum - NZC (NZ) icon

New Zealand Curriculum - NZC (NZ)

GCSE (UK) icon

GCSE (UK)

A-Levels (UK) icon

A-Levels (UK)

Upskilling icon

Upskilling

Homework help icon

Homework help

Exam prep icon

Exam prep

Programming class overview

My teaching style is designed to foster a supportive and interactive learning environment where students feel empowered to ask questions, share ideas, and collaborate with others. I firmly believe that the best learning happens when students are encouraged to think critically and apply their knowledge in real-world situations. I focus on: Interactive Learning: I regularly use live coding sessions, real-time problem-solving, and collaborative projects to ensure that students not only understand the material but can also apply it practically. This helps students stay engaged and gives them a sense of accomplishment when they see their code come to life. Encouraging Curiosity: I encourage students to ask questions and explore beyond the curriculum. In programming, learning never stops. I provide guidance on how to approach learning new languages, frameworks, or concepts on their own, fostering a spirit of curiosity that will benefit them long after the course ends. Practical Applications: Every concept I teach is paired with practical examples and real-world scenarios. Whether it's building a website, solving a complex algorithm problem, or developing an AI model, I ensure that students are ready to apply their skills in real-world environments.

keyLearning

Computer Science concept taught by Dr. Gurinderjeet

Student learned 5 days ago

The student and tutor reviewed functions to process lists of any, including calculating depth and removing elements. The student then worked on understanding expression trees and their evaluation using mutual recursion. The student will send notes for the next session, which will cover lambda and abstract functions.

List of Any Definition

Determining Depth of a List of Any

Atoms in Racket

Evaluating Expression Trees (Mutual Recursion)

Expression Trees

Removing Elements from a List of Any

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Student learned 5 days ago

The Tutor and Student reviewed advanced JavaScript concepts, including higher-order functions, callbacks, map, filter, and reduce methods. The Student was assigned practice questions related to these topics as homework. They scheduled their next session to continue practicing and increase the difficulty level.

Higher-Order Functions

Callbacks

Map Method

Filter Method

Reduce Method

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Student learned 8 days ago

The session involved an extra credit assignment focused on creating an ETL and ML pipeline for real-time fraud detection. The student and tutor reviewed the project requirements, data structure, and expected components. The student began setting up the project repository and folder structure, with plans to start filling in the code and addressing the 'todos' outlined in the assignment.

Synthetic Data Generation

Pydantic Schemas

AI Prompt Engineering

Git Branching Strategy

Data Quality Issues

ML Pipeline

ETL Pipeline

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Student learned 8 days ago

The session covered Bayesian statistics, including Poisson and Gamma distributions, and uniform distributions. The Student worked on problems involving finding posterior distributions with Gamma priors and uniform likelihoods. The Tutor assigned the Student the task of watching videos and creating cheat sheets for various distributions for future sessions.

Poisson Distribution

Gamma Distribution

Poisson-Gamma Conjugate Prior

Uniform Distribution

Posterior Distribution Calculation

Likelihood Function for Uniform Distribution

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Student learned 10 days ago

The session covered Bayesian inference, including prior distributions, likelihood, and posterior distributions. The Student worked through an example problem related to posterior probability and the tutor assisted with the concepts and formulas. The Student is expected to practice similar problems for the next session.

Prior Distribution

Likelihood Function

Joint Distribution

Bayesian Inference

Marginal Distribution

Location Normal Model Example

Posterior Distribution

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Student learned 11 days ago

The Student and Tutor reviewed and debugged caching implementations in a Python project, focusing on in-memory and Redis caching strategies. The Student implemented warm caching and clear caching functionalities, resolving errors in hit rate calculations and data storage logic. The session concluded with successful test runs after correcting the caching implementation and benchmark configurations, with plans to work on an ML pipeline ETL project next session.

Cache Clearing

Conditional Caching Logic

Warm Cache Implementation

In-Memory vs. Redis Caching

Cache Hit Rate Calculation

Debugging Caching Issues

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Your programming tutor also teaches

Computer Science

Computer Science

Databases

Databases

Web Development

Web Development

App Development

App Development

Artificial Intelligence

Artificial Intelligence

Learner for programming class

School icon

School

All Levels icon

All Levels

College icon

College

Adult / Professional icon

Adult / Professional

Home schooled icon

Home schooled

Teaching tools used by tutor

Android Studio image

Android Studio

Bitbucket image

Bitbucket

Jupyter Notebook image

Jupyter Notebook

NetBeans image

NetBeans

Dynamic programming classes

Chat for quick help icon

Chat for quick help

Note taking icon

Note taking

Parent feedback icon

Parent feedback

Mobile joining icon

Mobile joining

Pets are welcomed icon

Pets are welcomed

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