Dr. Gurinderjeet Kaur
Hands-on Computer Science tutor with engaging, problem-solving lessons
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Dr. Gurinderjeet Kaur
Doctorate degree
/ 55 min
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


Programming tutor specialities
Homework help
State-Specific Standards (USA)
Next Generation Science Standards - NGSS (USA)
Exam prep
Australian Curriculum (AU)
Assignment help
Upskilling
Test prep
Advanced Placement (AP) Program (USA)
A-Levels (UK)
Job readiness
Debugging
AI 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 for programming class
College
Home schooled
All Levels
Adult / Professional
School
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.
Your programming tutor also teaches
App Development
Artificial Intelligence
Computer Science
Databases
Web Development

Computer Science concepts taught by Dr. Gurinderjeet
The student and tutor reviewed practice problems for an upcoming final exam, confirming which problems were completed and which remained. A new practice set for homework six was generated, with solutions to be uploaded by the tutor. The tutor provided motivational advice and best wishes for the exam.
Practice Problem Strategy
Homework Assignment Generation
Exam Preparation Mindset
MATLAB as a Tool
The student and tutor reviewed practice problems, with a significant portion of the session dedicated to explaining the concept and implications of truncation error in numerical methods. They also discussed the student's approach to a specific problem, with plans for a follow-up session to complete any remaining material.
Truncation Error
Numerical Method Accuracy
Approximation in Calculations
The student and tutor worked through MATLAB practice problems, specifically focusing on using `polyfit` for polynomial fitting and the `integral` function for numerical integration. The session concluded with the student successfully solving a problem, and they plan to continue practicing.
Numerical Integration with MATLAB
Polynomial Fitting in MATLAB
MATLAB's `integral` Function
The student and tutor focused on reviewing and debugging problem five, involving the Simpson's 3/8 rule. The student successfully identified and corrected a coding error after comparing their implementation with the tutor's provided solution, leading to a better understanding of the concept.
Simpson's 3/8 Rule
Numerical Integration vs. Analytical Integration
Code Debugging and Comparison
MATLAB Code Comments and Self-Explanation
The class covered type conversion and type casting in Python, including implicit and explicit methods. The student then practiced these concepts and transitioned to learning about Python lists, including their indexing and basic operations, with plans to work on textbook exercises.
Implicit Type Conversion
Explicit Type Conversion (Type Casting)
Lists in Python
The class focused on numerical integration, specifically the Simpson's composite 1/3 rule, within the context of thermodynamics problems. The student worked on a complex homework problem involving enthalpy calculation and practiced similar problems to solidify their understanding of the computational methods and formulas.
Numerical Integration: Simpson's Rule
Partial Derivatives in Thermodynamics
Compressibility Factor (Z)
Polynomial Fitting and Differentiation
Teaching tools used by tutor
Bitbucket
NetBeans
Android Studio
Jupyter Notebook
Dynamic programming classes
Open Q&A
Parent feedback
Mobile joining
Chat for quick help
Note taking
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