Yeriko Vargas
Computer Science Tutor — Python, Machine Learning, SQL, Real-World Projects & Assignment Help
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Yeriko Vargas
Masters degree
/ 55 min
About your coding tutor - Yeriko
Hey — I’m Yeriko Vargas. If you’ve ever sat there like “why does none of this make sense?” — that’s exactly where I come in. I teach Python, stats, and machine learning in a way that actually clicks. No robotic lectures, no memorizing random formulas — we break things down, step by step, until you get it. I’ve built real models at Ford Motor Company and Chrysler, but more importantly, I know how to explain things in a way students understand. My whole focus is helping you go from lost → confident as fast as possible. We learn by building real stuff — not fake textbook problems. One of my recent projects is a music recommendation system that thinks like a DJ. It breaks songs into energy, texture, and dynamics using signal processing, then uses PCA + clustering to organize them into “states.” From there, it picks the next track based on similarity, BPM, key, and flow. So instead of guessing, you’re actually understanding how intelligent systems make decisions. I can help you with: * Python (Pandas, NumPy, Jupyter — all the real tools) SQL + working with real datasets * Statistics & probability (finally making sense of it) Machine learning (without the confusion) * Assignments, projects, exam prep Whether you’re stuck on homework, building a project, or just trying to understand what’s going on — I’ve got you. We’re not just learning… we’re making this stuff make sense. 🚀
Meet Yeriko
Yeriko graduated from Oakland University
Coding tutor specialities
Paired coding
Homework help
Upskilling
Debugging
Code Review
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 types for coding classes
ADHD
Coding for adults
Coding for intermediate
Coding for beginners
Coding for advanced
Yeriko - Coding tutor also teaches
Coding for kids
Matlab
R Programming
Coding concepts taught by Yeriko
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
The Tutor and Student explored predictive modeling concepts, starting with Y and Y-hat, and applying them to flight simulation scenarios. They discussed data generation, model fitting, and error evaluation, and concluded by demonstrating how to place a trade order using Python and the Interactive Brokers API.
Predictive Modeling with Y-hat
Linear Regression: The Foundation
Data Simulation and Generation
Model Evaluation: Finding the Best Fit
The student and tutor explored financial data analysis with Python, focusing on API integration and data processing. They worked on connecting to the IBKR API, troubleshooting connection errors, and implementing data fetching and analysis techniques, including statistical modeling for financial predictions. The session also involved debugging Python environments and package installations.
API Keys and Authentication
Connecting to Brokerage APIs (IBKR Example)
DataFrames and Data Manipulation in Pandas
Statistical Concepts: Z-scores and Confidence Intervals
Predictive Modeling: ARMA and Linear Regression
The tutor reviewed fundamental concepts of trigonometry, including the relationship between circles, right triangles, and trigonometric functions (sine, cosine, tangent, and their reciprocals). The student practiced identifying angles on the Cartesian plane based on coordinates and understood how these relate to trigonometric values, with plans to reinforce these concepts through practice problems in future sessions.
Trigonometric Ratios: SOH CAH TOA
Unit Circle and Coordinates
Functions and the Vertical Line Test
Relationship between Coordinates
Angles
and Trigonometric Values
The student and tutor worked on Python programming, focusing on data storage and retrieval using custom functions within Jupyter Notebooks. They practiced creating functions to save and import data frames, organizing code into modular Python files, and establishing templates for efficient project setup. The next steps involve the student practicing these concepts independently.
Python Functions and Modules
Data Storage and Retrieval (PKL Files)
Organizing Code with Templates and Folders
APIs and Inter-System Communication
The Tutor and Student explored data science techniques for financial analysis, focusing on Principal Component Analysis (PCA) and data processing for machine learning models. They practiced fetching financial data, normalizing it, and transitioning code from notebooks to terminal scripts for efficiency. The next session will involve reviewing the Student's setup and data acquisition process.
Batch Processing and Memory Management
Terminal vs. Notebooks
Data Normalization and Scaling
Principal Component Analysis (PCA)
Data Wrangling and Feature Engineering
Approach & tools used by coding tutor
Visual Studio Code
Google Colab
PyCharm
Git & GitHub
Jupyter Notebook
Hands-on coding classes
Record lessons
Open Q&A
Parent feedback
Note taking
Pets are welcomed
Programming tutors on Wiingy are vetted for quality
Every tutor is interviewed and selected for subject expertise and teaching skill.