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Since October 2022
Instructor since October 2022
Online Object Oriented Programming [OOP] using Java
course price icon
From 53 £ /h
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1) Focus on Conceptual Understanding of OOP terminology like Abstraction, Encapsulation, Polymorphism etc
2) Practical experience to teach syntax and logical way of thinking
3) Start with simple programs and graduate to complex programming using multiple classes
4) Customized teaching basis student requirements
5) Preparation for AP Computer Science A
Extra information
BlueJ API preferred for teaching
Location
location type icon
Online from India
About Me
I partner with students and parents to bring out the best in the student.

I adjust my pace of teaching to ensure that the student actually understands and there is enough time, freedom and positivity to repeat lesson and clarify doubts.

I endeavour to build a strong foundation with teaching, guided worksheets and assessments.
Education
I completed my schooling and graduation in India.

BSc in Physics [H],
St Stephen's College, Delhi

Masters in Computer Applications
[ MCA ] from University of Delhi
Experience / Qualifications
21 Years of experience in Information Technology Software Development and managing IT Assets.
5 years of teaching Computer Science
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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1. Introduction to Object-Oriented Programming 🧠
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What it's actually doing under the hood.
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Protect the internal state of objects.
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Choosing the right architecture.
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Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
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2- When to use it
3- and when not to use it

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a solid understanding of OOP
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Python for data science with NumPy, Pandas, Matplotlib and scikit-learn. Deep learning using TensorFlow and Keras. Core theory including regression, classification, clustering, decision trees, random forests, neural networks and CNNs, together with the linear algebra, calculus and statistics underneath them. Computer vision and image classification, which is my published research area. Model evaluation, overfitting and hyperparameter tuning. Writing machine learning work up to academic standard, covering methodology, results and critical evaluation.

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Good-fit Instructor Guarantee
favorite button
message icon
Contact Shalini