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Since February 2022
Instructor since February 2022
Data Science & Machine Learning ONLINE Class for all ages with at least 3 real-life projects per Algorithm
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From 18 € /h
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I'm a professional and young software engineer working as an Industrial Trainer in a reputed Training Institute.
I have completed many different enterprise projects that came to life and are accessed by thousands of users.
In this class, we can cover any general Data Science and Machine learning topic related to high school and university, as well as real-life enterprise project consultancy.
I have been teaching for many years and I have adopted a way of learning with "ELI5": "Explain Like I'm five".
I'm gonna explain hard concepts in easy and real-world examples. We're not just gonna learn a language or topic, but learn how to learn fast and adapt it in every aspect.
I'm a passionate software developer and I will make you love the subject by teaching it in a fun and successful way.
Please get in touch with me to let me know what kind of help you need. I'm here for you!
Extra information
Feel free to contact me at any time.
Location
location type icon
Online from India
About Me
Science and Math don't have to be hard. Taught correctly, sciences can be the most exciting subjects.

No matter if you struggle in middle school or with your A-Level preparation, I am an experienced and professional Data Science and Machine learning Trainer who will not only help you understand the topics but also fall in love with science.

My lessons are student-centered and active. I am using a vast array of tools and media to get the best learning experience possible.
Education
Bachelors of Engineering in Computer.
Masters of Science in Computer Applications.
And many more certificates in programming languages like SQL, Python, Data Science& Machine Learning and many more.
Experience / Qualifications
Teaching is my passion. I am a qualified and professional international school teacher with more than 6 years of experience teaching and tutoring hundreds of students.
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
30 minutes
45 minutes
60 minutes
90 minutes
120 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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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
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• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

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• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
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5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

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• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
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• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
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• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
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• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

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• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

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Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

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Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
verified badge
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:
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Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
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verified badge
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verified badge
Microsoft Excel is a powerful Microsoft corporation application that helps one do various mathematical, statistical and logic operations on data sets. It's a powerful tool for data analysis.

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verified badge
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I will guide you step by step through the fundamentals of HTML, CSS and JavaScript, helping you understand how websites are structured, styled and made interactive.

In this class, you will learn how to:

- Understand the basics of web development and how websites work
- Use HTML to create the structure of a webpage.
- Use CSS to add colours, layouts, fonts and styles.
- Get started with JavaScript and understand basic website interactivity.
- Write and organise simple code.
- Build your first basic webpage through practical exercises.

No previous coding experience is required. We will learn at your pace, with clear explanations, hands on practice and time to ask questions.

My goal is to help you build a strong foundation in web development and gain the confidence to continue learning and creating your own websites.
verified badge
Are you interested in learning Python but don't know where to start? This course is designed to help you understand the fundamentals of Python programming in a simple, practical, and enjoyable way.

Python is one of the most popular programming languages in the world. It is widely used in software development, automation, data analysis, artificial intelligence, and web development.

Whether you are a complete beginner, a student, or someone looking to develop new technical skills, these lessons will help you build a strong foundation in programming.

You will learn
1. Introduction to Python
2. Python Fundamentals
3. Conditional Statements and Loops
4. Working with Data
5. Functions and Practical Programming
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Good-fit Instructor Guarantee
favorite button
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Contact Sameer