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
Upskilling
Job readiness
Debugging
Homework help
Paired coding
Code Review
Exam prep
Learner for programming class
College students
ADHD
High School 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
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15 days Refund
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Free Tutor Swap
Computer Science concepts taught by Yeriko
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.
Relationship between Coordinates
Angles
and Trigonometric Values
Functions and the Vertical Line Test
Unit Circle and Coordinates
Trigonometric Ratios: SOH CAH TOA
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 Wrangling and Feature Engineering
Data Normalization and Scaling
Principal Component Analysis (PCA)
The Student and Tutor explored Principal Component Analysis (PCA) and clustering techniques, applying them to a music dataset to understand song energy based on texture and dynamics. They discussed data preprocessing, including normalization and scaling, and explored methods for determining the optimal number of clusters. The session concluded with a plan to apply similar techniques to a finance project in future sessions.
Clustering Analysis
Exploratory Data Analysis (EDA)
Data Preprocessing: Scaling and Normalization
Supervised vs. Unsupervised Learning
Principal Component Analysis (PCA)
Teaching tools used by tutor
PyCharm
Jupyter Notebook
Visual Studio Code
Google Colab
Git & GitHub
Dynamic programming classes
Record lessons
Open Q&A
Note taking
Parent feedback
Pets are welcomed
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