Data Structures and Algorithms classes, Preparation for Interviews at Google, Microsoft, among others

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From 26.81 £ /h

Master in Computer Science from the State University of Campinas (Brazil). He has participated in various programming contests and has been a coach of undergraduate teams for the ACM-ICPC contest. Some of the achievements:

- First place in Codesignal in Peru.
- Third place in LeetCode in Peru (+1000 problems solved).
- Top 1% of registered users on InterviewBit.
- More than 1000 problems solved in online judges like UVA, Spoj, HDU, etc.

I have participated in Topcoder, CodeJam and other international competitions that require knowledge of algorithms and data structures. I am the author of the blog "Algorithms and More" where I have written tutorials in Spanish with more than 300 daily views.

I have experience preparing interviews to apply to companies such as Google, Facebook, Microsoft, among others.

The methodology is didactic with a step-by-step explanation of the algorithms and coding. I can also give advice on studies abroad, job opportunities in large technology companies (Google, Microsoft, etc.) and many other opportunities.

If you want to improve your abstraction|logic and make your university projects easy to program, this is your opportunity.

I do not solve exams.

PS: If you are interested in artificial intelligence, you can look for my other ad about it.

Knowledge of C, C++, Python.

Location

Online from Peru

Age

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

Spanish

English

Portuguese

Skills

C - c++

Computer programming

Algorithms

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

Private or group classes of Machine Learning and Deep Learning

32.17 £ /h

Master in Computer Science from the State University of Campinas (Brazil) and university professor in Peru. He has participated in the most important Artificial Intelligence conferences including ACL, NeurIPS, ICML, ICLR, KDD, ICCV and CVPR, summer schools such as Machine Learning (MLSS), Deep Learning (DLRL) and Probabilistic ML (ProbAI). He has also participated in various programming contests and has experience preparing interviews for applications to companies such as Google, Meta, Microsoft, among others. He has extensive experience in the areas of Machine Learning and Deep Learning applied mainly to computer vision and natural language processing.

He has experience in teaching, providing illustrative explanations for a better understanding of both the theoretical and practical parts. Some examples of presentations given:

He has also advised students from different countries in their graduation and master's theses, providing them with a theoretical and practical base with examples that they can then use to continue their development.

Some of the things I can help you with:

- Machine Learning: Linear regression, logistic regression, regularization, LDA, QDA, SVMs, decision trees, random forest, boosting, PCA, clustering (K-means, DBSCAN, hierarchical, GMM), neural networks, model selection, metrics evaluation, MLE, Bayesian learning, data preprocessing, etc.

- Deep Learning: Multilayer Perceptron (MLP), backpropagation, activation functions, multiclass classification, optimizers (SGD, Adam, RMSProp, etc.), CNNs, architectures (ResNet, DenseNet, EfficientNet, Siamese, etc.), RNNs, LSTMs, Seq2seq, Attention, Transformers (BERT, GPT, ViT, etc.), autoencoders, generative models (VAE, GAN, Diffusion, etc.), etc.

- Languages: Python, C++
- Libraries and frameworks: PyTorch, Tensorflow, Keras, Huggingface, numpy, pandas, scikit-learn, sympy, etc.

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Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
Signal processing and data acquisition
Engineering Sciences

These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering

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As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

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In the training program, you will learn to:

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For any questions, you can contact me by PM.

See you soon,
Matthew

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What we cover, adapted to your level and goals:
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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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🧠 Learn by doing - real apps, real logic.
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Data science, statistics & mathematics – clearly explained, personally supported.
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With my structured, understandable, and motivating approach, I'll help you not only solve problems but also understand data, recognize connections, and make informed decisions. My lessons are personalized, efficient, and at eye level.

Who I am – and why I teach:
I teach in Bern and successfully completed the MAS program in Statistical Data Science at the University of Bern, focusing on statistics, mathematics, and data science. For several years, I have been passionately teaching, both in academic contexts and for professionals who want to think and work more data-driven.

In parallel to my teaching, I have implemented numerous data science projects – from exploratory analysis and data modeling to decision support in a business context. This combination of theory and practice makes my teaching particularly close to reality while remaining accessible.

I love making complex topics tangible, creating aha moments, and empowering people to handle data confidently. For me, tutoring isn't just about imparting knowledge—it's about developing their minds on equal terms.

-What you can expect from me:
One-to-one lessons with a focus on data comprehension, statistics & analytical thinking
Support with projects, assignments, exams or getting started in the data world
Practical explanations – step by step and adapted to your everyday life
Teaching modern methods for data analysis, modeling & interpretation
Long-term strategies for problem-solving & structured thinking
Flexible lessons in Bern or online – personal, competent & reliable

Why I can help you understand data science:
Because I work at the interface between science and practice. I know how quickly you can get lost in formulas and tools—and I'll help you see the common thread:
How data tells stories, how you analyze it, and how you make smart decisions.

With me, you won't just learn methods—you'll learn how to think with data. Whether in your studies or in your career, I'll guide you in truly understanding data and applying it confidently.
Learn data analysis.
Analyze and model complex data sets – understandable, practical and with structure.
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You’ll learn to:

Understand theory topics like algorithms, logic gates, and networks

Write, test, and debug programs step-by-step

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This course is designed for complete beginners, students, or enthusiasts who want to acquire a solid foundation without getting bogged down in overly complex theory. My goal is to make you independent quickly.

In the program :
The content is adapted to your pace, but generally follows this progression:

Installation & Setup: Configure your working environment (VS Code, PyCharm or IDLE).

The Fundamentals: Variables, data types (numbers, lists, dictionaries) and basic operations.

Programming Logic: Mastering conditions (if/else) and loops (for/while) to give intelligence to your code.

Functions & Modularity: Learn how to structure your code so that it is clean and reusable.

My Methodology
80% Practice: You learn better by typing code than by looking at slides.

Positive Pedagogy: No judgment, we move forward step by step. Every mistake is an opportunity to learn.

Personalized Support: I adapt to your specific objectives (homework help, personal project or intellectual curiosity).