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
Predictive modeling
Machine learning
Data visualization
Assignment help
Business intelligence
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
Data Science for intermediate
Data Science for beginners
Data Science for adults
ADHD
Data Science for advanced
Your data science tutor also teaches
Data Analysis
Data Science
Tableau
Data Science concepts taught by Yeriko
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.
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.
AI Model Capabilities and Limitations
Funnel Building and Automation Strategies
Command Line Interface (CLI) and Terminal Operations
Folder Organization and Project Management
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
Cursor IDE Setup and Configuration
AI Agent Interaction with Cloud Code
Project Deployment and Workflow Management
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
Teaching tools used by data science tutor
Google Colab
Jupyter Notebook
RStudio
Interactive data science classes
Open Q&A
Parent feedback
Pets are welcomed
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.