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Since November 2022
Instructor since November 2022
** Computer Science & Programming Made Simple – Learn, Practise and Build Skills **
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From 21 Fr /h
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Whether you are a complete beginner, a school student, a university learner, or a working professional, I can help you understand Computer Science and programming in a simple, practical, and structured way.

With over 26 years of teaching experience, I offer personalised lessons based on your learning goals, current knowledge, and pace. We can start from the basics and gradually develop your confidence through clear explanations, examples, coding exercises, and practical activities.

Topics may include Python, C, C++, Java, HTML, CSS, JavaScript, databases, data structures, algorithms, artificial intelligence, data analysis, and web development.

My aim is to make technical subjects easier to understand while helping you develop practical skills that you can apply independently.
Extra information
Students should have access to a computer or laptop for practical exercises. Please share your learning goals, current level, and any specific topics you would like to study before the first lesson.
Location
location type icon
Online from India
About Me
I am an experienced Computer Science tutor with over 26 years of teaching experience and a Master’s degree in Computer Applications. I work with students across school, university, and professional levels, helping them develop strong conceptual understanding along with practical skills.

My expertise spans Python with a focus on data science and libraries such as Pandas, complemented by Machine Learning and Data Visualization using Power BI and Tableau. I also teach core programming languages including C, C++, and Java, and work extensively with database technologies such as MySQL, Oracle, and MongoDB. Additionally, I provide structured guidance in web development (HTML, CSS, JavaScript, PHP, ASP.NET) and fundamental areas like Data Structures.

Over the years, I have taught more than 1,200 students from different countries, including the USA, UK, Canada, Australia, New Zealand, Germany, Malaysia, and the Middle East. I have supported learners across various curricula such as AP Computer Science (A & Principles), IB Computer Science (SL & HL), A-Level, GCSE, and university-level programs, as well as IT professionals seeking to strengthen their skills. I also assist with assignments, projects, and test preparation.
Education
Masters in Computer Applications ( MCA )
MTech ( Computer Science and Information Technology )
Bachelor in Computer Science (BSc Computer Science)
Pursuing PhD.
Experience / Qualifications
26 years Experienced Professional Online Tutor and Assignment Helper for Computer Science
Masters in Computer Applications
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Hindi
Panjabi
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
Hello,

I am 26 years experienced Online Tutor and Assignment Helper for Computer Science. I teach PHP, MySQL, Python, Machine Learning, Programming in C, C++, Java, ASP, C#.NET, Visual Basic, Oracle, HTML, VBScript, JavaScript, Data Structures, JQuery, Bootstrap , MS Office. I have teaching experience of teaching IT Professionals , students from different grades, graduate and post graduate classes for more than 22 years.

Presently I am teaching students online, providing homework assignment help, provide help in online tests for the students from USA ,UK, Canada, New Zealand, Germany, Australia, Malaysia, Austria, Malta, Saudi Arab etc. Also, I am in Software Development and Web Designing. I have helped more than 1200 students from different countries in last 26 years.

Regarding my teaching methodology, I always start teaching the concepts right from the scratch so that the students can learn concepts easily. I would like to describe you how do I teach through Internet . There is 100 % interaction between me and my students using Internet.

For starting the lessons with me all that you need is PC with Internet Connection and Headphone and Mic. Rest I will guide you about everything when you start learning with me. My lessons are also customized, planned and prepared according to the needs of individual student. I can also provide old student references if the student needs that.


If you join the course with me, I assure you that it will be value for your time and money.


Thanks
Harry
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Additional materials + practice qs | Lesson plans + regular feedback | Recording + session notes available

A common theme running through our lessons will be to simplify - even topics like electromagnetic induction can be reduced to small bits :)

Together, we'll:
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- Albert Einstein, while studying superposition of waves, I’m sure :)
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Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

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Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

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The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

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The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

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A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
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Pumping lemmas for regular and context-free languages
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verified badge
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1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

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"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?
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First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
- Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`.
- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

5. From hand to screen: AI at the service of LaTeX (30 min)

- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
- Concrete demonstration:
1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Additional materials + practice qs | Lesson plans + regular feedback | Recording + session notes available

A common theme running through our lessons will be to simplify - even topics like electromagnetic induction can be reduced to small bits :)

Together, we'll:
1. Find learning gaps
2. Break concepts into small bits
3. Apply to real world and exam questions
4. Work on exam technique - like the difference between "explain" and "describe" questions
5. Build mark-scheme friendly language

“It's not that I'm so smart, it's just that I stay with problems longer”
- Albert Einstein, while studying superposition of waves, I’m sure :)
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