Yeriko Vargas
Computer Science Tutor — Stop Feeling Lost in Python & ML, Start Building Real Projects (Music, Video, AI)
Show all photos
Yeriko Vargas
Masters degree
/ 55 min
Yeriko - Know your tutor
Hello there , I’m Yeriko. I teach Python, stats, and machine learning through real, exciting projects: sound, video, even game-style systems — so it actually clicks. I’ve built models at Ford Motor Company and Chrysler, and I bring that same real-world energy into how I teach. We’re not just learning, we’re building cool things with data. Here, you won’t just “coding” — you’ll use it to build, experiment, and think like a data scientist. From predicting trends to designing machine learning systems, we’ll break things down so they actually make sense — no fluff, no confusion. Lately, I’ve been building a music recommendation system that treats audio like data you can understand. Instead of guessing songs, the system breaks music down into energy, texture, and dynamics using signal processing, then organizes it with PCA and clustering to create “states” of sound. From there, it selects the next track using similarity + rules like BPM, key, and energy flow — basically thinking like a DJ but powered by machine learning. It’s a perfect example of how we take something creative and turn it into a structured, intelligent system — and that’s exactly how I teach. Also — I’m strong in SQL and tools like Tableau/Studio, so we don’t just build models, we learn how to work with real data end-to-end.
Meet Yeriko
Yeriko graduated from Oakland University
Programming tutor specialities
Homework help
Job readiness
Paired coding
Code Review
Assignment help
Debugging
Project help
CoTutorAI modules
Summary
Podcast
Quiz
Learnings
Flashcard
Spotlight
Zero Risk Guaranteed
15-days refund
Free tutor swap
No cancel fee
1-yr validity
24/7 support
Learner for programming class
ADHD
High School students
College students
Programming class overview
I specialize in tutoring students for homework, exams, and especially big exams, building understanding from the ground up. My approach is comprehensive, covering both theory in statistics and mathematics and practical Python coding. This ensures you're not just exam-ready but also equipped with essential programming skills. I emphasize Python solutions alongside statistical concepts, offering a dual-track learning path. My aim is to prepare you not just for academic success but for a thriving career in data science. With me, you get the tools and knowledge to excel in both the classroom and the professional world.
Your programming tutor also teaches
Artificial Intelligence
Computer Science
Databases
Machine Learning
Python
R
Computer Science concepts taught by Yeriko
The student and tutor worked on various website development tasks, including image optimization, affiliate link integration, and content/styling adjustments on a WordPress site. They planned follow-up sessions to continue these improvements and discuss the potential implementation of a chatbot feature.
Website Image Optimization
Website Content Renaming and Hyperlinking
Responsive Design and Alignment
Affiliate Disclosure Banners
User Interface Elements: Pop-ups and Zoom Features
AI Chatbot Development Stages
The Student presented their WordPress website, detailing specific requirements for mobile optimization of H1 headings, integration of Amazon affiliate banners, and removal of embedded theme text from image banners. The Tutor provided an initial assessment and outlined a plan to implement these web development and design changes, with a follow-up session scheduled to transfer the updated files.
Mobile Responsiveness: H1 Headings & Centering
Amazon Affiliate Banner Integration
WordPress Theme Customization & Content Management
Website Performance & SEO Foundations
User Experience (UX) & Design Refinements
The Student and Tutor engaged in a wide-ranging discussion covering principles of aerodynamics, the application of AI and statistics in fields like rocketry and medical diagnostics, and personal data tracking for self-improvement. The Student also demonstrated and explained techniques for playing complex drum rhythms. They made plans to cover Python and app development in their next session.
Exponential Growth & Focused Skill Development
Rocket Nozzle Fluid Dynamics & Optimization
Data-Driven AI & Predictive Modeling
Statistics as a Framework for Experimentation & Proof
Outliers: Rethinking Deviations in Data & Society
Personal Data Analytics for Self-Optimization
The Student and Tutor engaged in a comprehensive discussion on core Data Science concepts, including data normalization, different types of statistical distributions, and the classification of variables. They explored the stages of Exploratory Data Analysis (EDA), covering data imputation methods and the significance of residuals in statistical modeling. The session also introduced the foundational principles of Artificial Intelligence, explaining its operational mechanics through the analogy of neurons and discussing its real-world applications. The Student expressed interest in learning about optical recognition and applying these concepts to personal data analysis for self-improvement, which was noted for future lessons.
Exploratory Data Analysis (EDA) & Imputing Missing Data
Data Normalization and Distributions
Introduction to Artificial Intelligence (AI) and Neural Networks
Residuals and Data Variance
Categorical vs. Numerical Variables & Predictive Models
The session covered setting up Python virtual environments to manage project dependencies and avoid conflicts with system-level installations. The student learned how to create, activate, and manage virtual environments, as well as how to export and import package lists for different machines. Homework includes practicing the virtual environment setup and exploring data analysis using the new environment.
Creating and Activating a Virtual Environment
Package Management with Pip
Exporting and Replicating Environments (requirements.txt)
Terminal Usage for Python Development
Importing Data and Calculating Portfolio Returns
Virtual Environments in Python
The Tutor and Student explored statistical concepts including linear regression, correlation, and probability distributions. They practiced analyzing data relationships using correlation matrices and discussed hypothesis testing with examples. The next session is planned to involve more complex datasets and examples.
Null Hypothesis and p-values
Correlation: Measuring Relationships
Linear Regression Basics
Distributions: The Shape of Data
Teaching tools used by tutor
PyCharm
Visual Studio Code
Jupyter Notebook
Google Colab
Git & GitHub
Dynamic programming classes
Record lessons
Pets are welcomed
Open Q&A
Parent feedback
Note taking
Find programming tutors in similar subjects
Coding tutors on Wiingy are vetted for quality
Every tutor is interviewed and selected for subject expertise and teaching skill.