Tutoring in IT / Programming (C#, C, C++, Python, Java, ...)

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From 31 £ /h

Hello! My name is Anabel, I'm 21 years old and I work as a software developer. My 5-year training at an HTL for information technology, as well as the professional experience I was able to gain in the IT industry, qualifies me as a tutor. I have been working as a tutor for 4 years. I offer online tutoring in a wide variety of programming languages (C#, C, C++, Python, Java, Scratch,...). My offer is aimed at all school levels. I also offer private lessons for complete beginners, advanced learners, students or adults. I also have some experience with younger children who are interested in technical concepts or who need a slow introduction to programming. Whether certain skills simply want to be learned in your free time, whether you need help at school or for an exam or just as homework/project support, I would be very happy to hear from you! If you have problems with programming, I usually recommend long-term tutoring, since the material is mostly constructive and a certain way of thinking is developed over time, which should also be preserved. Of course, short-term exam preparation is also useful in many cases! Especially now in the summer months, private tutoring is also a great way to repeat and consolidate the material from the previous year or to learn new skills. Of course, I'm also happy to help with a follow-up exam in the fall. One unit lasts 50 minutes, but double units can also be used for larger projects/homework/duties. I can also help with other IT topics, such as game design with Unity, system technology and a number of theoretical topics on request!

Extra information

If you are interested in tutoring with me, I would be happy to hear from you! It is best if you also send detailed information such as school level/semester/knowledge level, programming language, current topic, etc. I look forward to our cooperation!

Location

Online from Austria

About Me

Hello! My name is Anabel, I'm 20 years old and I'd love to hear from you! You can find more details about my tutoring in the advert.

Education

Higher Technical School (HTL) Krems Information technology with specialization in system technology, various workshops and further training (e.g. with the game engine Unity)

Experience / Qualifications

Private tutor for 4 years, technical training in IT, professional experience in IT and software development

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

German

English

Skills

Computer programming

Information technology

Video games

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Tutoring in game programming/games design with Unity C#

31 £ /h

Hello! I give tutoring or private tutoring in game development with Unity and C#. I teach beginners and advanced students. If you have any questions, please don't hesitate to contact me! I look forward to your inquiry!

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Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

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Alternating Currents: RLC circuits, resonance, impedance.

3. Thermodynamics:
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Ideal and real gases: Equations of state, thermodynamic transformations.

4. Industrial sciences:
Automatic Linear, Kinematic, Static.

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Good preparation and success in your studies!

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Unlock the power of one of the most influential programming languages in computing history! Whether you're an absolute beginner or looking to deepen your expertise, this comprehensive C/C++ course delivers structured learning from fundamentals to advanced concepts that power operating systems, game engines, and high-performance applications.

## **Why Choose This C/C++ Program?**

**Industry-Relevant Curriculum:** Learn expert guidance on the design of effective classes, functions, templates, and inheritance patterns that form the backbone of professional C++ development. Move beyond basic syntax to understand how to write clean, efficient, and maintainable code that stands the test of time.

**Templates & Generic Programming Mastery:** Go beyond introductory material with in-depth coverage of templates—the cornerstone of modern C++—enabling you to create robust, reusable code components that work across multiple data types. Discover how function templates, class templates, and variadic templates work to maximize your coding efficiency.

**Practical, Hands-On Approach:** This isn't just theory! You'll build real-world projects that demonstrate memory management, object-oriented programming, and system-level programming techniques used in today's technology landscape.

## **Your Learning Journey**

Our structured path takes you from writing your first "Hello World" program through advanced template metaprogramming, with special attention to modern C++ standards (up to C++20). You'll gain the confidence to tackle complex programming challenges and understand the "why" behind effective C++ practices—not just the "how."

## **Transform Your Career Today**

C/C++ skills remain in high demand across industries from finance to gaming to IoT. By mastering these foundational languages, you'll develop problem-solving abilities that translate to any programming environment.

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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
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• 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

3- DATA PREPARATION AND EXPLORATION
• 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
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

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

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
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• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
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• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• 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

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• 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

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

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.

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