Yeriko Vargas
Data Science Help for College — Python, Stats, ML (Assignments + Projects) + Real Understanding
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Yeriko Vargas
Masters degree
/ 55 min
About your data science tutor
HeY! I’m Yeriko. I teach Python, statistics, and machine learning by building real, high-impact projects — not just theory. We work with sound, video, and real datasets so concepts actually stick and translate into real skills. I’ve built models at Ford Motor Company and Chrysler, and I bring that same production-level thinking into every session. This isn’t “tutorial-style” learning. This is how data science actually works in the real world. Here, you won’t just code, you’ll learn how to: Think like a data scientist Structure messy data into usable systems Build models that actually solve problems Communicate insights like a pro From predictive modeling to full ML pipelines, everything is broken down in a way that’s clear, practical, and immediately usable — no fluff, no confusion. One example: I’ve built a music recommendation system that treats audio as structured data. Instead of guessing songs, the system extracts features like energy, texture, and dynamics using signal processing, then uses PCA + clustering to organize tracks into “states.” From there, it selects the next track using similarity scoring + constraints like BPM, key, and energy flow — essentially modeling how a DJ thinks, but powered by machine learning. That’s the core idea: take something complex → break it into data → build an intelligent system around it. On top of that, I’m strong in SQL and tools like Tableau, so we go beyond modeling — we cover the full pipeline: data extraction → transformation → modeling → visualization → decision-making.
Meet Yeriko
Yeriko graduated from Oakland University
Data Science tutor skills
Deep Learning
Machine learning
Assignment help
Business intelligence
Case Studies
Predictive modeling
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 data science class
ADHD
Data Science for intermediate
Data Science for adults
Data Science for advanced
Data Science for beginners
Your data science tutor also teaches
Data Analysis
Data Science
Tableau
Data Science concepts taught by Yeriko
The session was a demo lesson focused on R Studio programming for an undergraduate Economics course (Econ 221). The Student sought help with a homework assignment involving data analysis concepts such as identifying missing values, understanding variables, constructing new variables, analyzing relationships, and calculating probabilities. The Tutor explained these concepts in detail, relating them to economics and discussing a plan to work through the homework questions and prepare for an upcoming midterm.
Grouping Data for Comparative Analysis
Introduction to Probability Concepts in Data
Analyzing Relationships Between Variables
Feature Engineering: Creating New Variables
Understanding Data Variables and Structures
Handling Missing Values (NA
NaN) in R
The student and tutor worked on establishing Python connectivity for trading applications, troubleshooting API errors, and understanding programming kernels. They then explored the differences between machine learning and deep learning, followed by a discussion on applying data science to music composition using MIDI notation. The session concluded with the creation of a dedicated Python environment for music-related packages.
MIDI for Music Representation
Python Environment Management (Conda)
Understanding Kernels in Computing
Machine Learning vs. Deep Learning
The student and tutor explored the distinctions between supervised and unsupervised machine learning, particularly in the context of computer vision and data representation. They discussed how images and music can be converted into numerical data for analysis and how this can be applied to various fields. Future sessions were planned to cover setting up development environments and further explore music generation projects.
Supervised vs. Unsupervised Learning
Computer Vision: Pixels to Vectors
Feature Extraction and Data Representation
Clustering and Pattern Recognition
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.
User Interface Elements: Pop-ups and Zoom Features
AI Chatbot Development Stages
Website Content Renaming and Hyperlinking
Responsive Design and Alignment
Website Image Optimization
Affiliate Disclosure Banners
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.
User Experience (UX) & Design Refinements
Website Performance & SEO Foundations
WordPress Theme Customization & Content Management
Amazon Affiliate Banner Integration
Mobile Responsiveness: H1 Headings & Centering
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
Teaching tools used by data science tutor
Looker
RStudio
Google Colab
Streamlit
Jupyter Notebook
Interactive data science classes
Parent feedback
Pets are welcomed
Open Q&A
Record lessons
Note taking
Data Science tutors on Wiingy are vetted for quality
Every tutor is interviewed and selected for subject expertise and teaching skill.
