Yeriko Vargas
Computer Science Tutor — Stop Feeling Lost in Python & ML, Start Building Real Projects (Music, Video, AI)
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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
Debugging
Assignment help
Homework help
Job readiness
Code Review
Paired coding
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
High School students
College students
ADHD
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 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.
Linear Regression Basics
Correlation: Measuring Relationships
Distributions: The Shape of Data
Null Hypothesis and p-values
The Tutor and Student collaborated on designing a system for tracking dealer training attendance and knowledge retention for M&A Supply. They discussed data structure, ID management, and the use of AI-generated content and potential dashboards to improve training effectiveness. The next steps involve the Student creating a system template based on the discussed data and concepts.
Data Tracking and Management
Training Curriculum and Delivery
Leveraging AI and Automation in Training
Data Identification and Interconnectivity
The student and tutor worked on developing and organizing AI skills within platforms like Claude and Cursor. They practiced troubleshooting, creating custom skills for website structure and data backup, and establishing a file organization system for multiple projects. The session concluded with a plan to build a marketing funnel by integrating existing email templates and skills.
Folder Organization and Project Management
Command Line Interface (CLI) and Terminal Operations
AI Model Capabilities and Limitations
Funnel Building and Automation Strategies
AI Skill Development and Training
The tutor and student worked on setting up the Cursor IDE, organizing project folders, and integrating AI coding assistants. They practiced using the terminal, explored AI model selection, and began developing a lead generation website by generating HTML and discussing deployment strategies, with a plan to focus on project implementation in future sessions.
Understanding Code Hosting and Deployment
Project Deployment and Workflow Management
AI Agent Interaction with Cloud Code
Cursor IDE Setup and Configuration
The Tutor provided an overview of AI development environments and project organization, explaining the benefits of tools like Cursor for integrating AI into coding. The Student expressed interest in applying these concepts to their own projects, and they planned to schedule follow-up sessions to set up the Student's computer and begin working on their specific applications.
Environments in Python
GitHub for Code Management
AI Model Selection and Usage
Development Environments and Tools
The Student and Tutor reviewed concepts related to linear regression, matrix operations, and Principal Component Analysis (PCA). They discussed how multiple features predict an outcome and how PCA reduces dimensionality by identifying principal components that capture data variance. The next steps involve applying these concepts to predict sales using a linear regression model.
Y-hat (ŷ) as Prediction
Principal Component Analysis (PCA)
Linear Regression and Model Building
Matrices in Data Representation
Teaching tools used by tutor
Google Colab
Xcode
Visual Studio Code
PyCharm
Jupyter Notebook
Dynamic programming classes
Open Q&A
Pets are welcomed
Note taking
Parent feedback
Record lessons
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