Yeriko Vargas

Python, ML, R-Studio & SQL Mentor | Turn Your Ideas into Fully Functional Data Projects

4.2(31)

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Yeriko Vargas

Masters degree

/ 55 min

About your coding tutor - Yeriko

Hello! My name is Yeriko Vargas. I hold a Master's degree in Statistics and have several years of experience working with Python, data science, and machine learning. I enjoy helping students understand difficult topics by breaking them into clear logical steps. My focus is on teaching intuition and problem-solving skills rather than simply giving answers. I can help with: Python Pandas NumPy Machine Learning Statistical Modeling Data Analysis Regression Hypothesis Testing Probability Data Visualization Jupyter Notebooks Python programming Statistics and probability Data science projects Machine learning basics Data analysis using Pandas and NumPy University homework and assignments Whether you are learning Python for the first time or working on a data science project, I can help guide you through the problem-solving process. I am a data scientist and statistician with strong experience in Python, R , SQL, machine learning, and statistical modeling. My teaching style focuses on helping students understand concepts intuitively rather than memorizing formulas. Subjects I tutor include Python programming, statistics, data analysis, and machine learning fundamentals.

Yeriko graduated from Oakland University

Yeriko graduated from Oakland University
Yeriko graduated from Oakland University

Coding tutor specialities

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Debugging

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Paired coding

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Code Review

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Homework help

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Upskilling

Learner types for coding classes

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Coding for adults

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Coding for intermediate

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ADHD

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Coding for advanced

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Coding for beginners

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15 days Refund

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Coding concepts taught by Yeriko

Student learned 2 days ago

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.

Principal Component Analysis (PCA)

Clustering Analysis

Exploratory Data Analysis (EDA)

Data Preprocessing: Scaling and Normalization

Supervised vs. Unsupervised Learning

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Student learned 4 days ago

The Tutor and Student explored the concept of APIs and their application in financial data analysis, specifically using Yahoo Finance. They discussed anomaly detection techniques in machine learning, including cluster analysis and random forests, and touched upon fundamental statistical concepts like normality and data labeling (supervised vs. unsupervised learning). Future sessions were planned to delve deeper into PCA and its combination with clustering.

APIs and Data Fetching

DataFrames and Data Manipulation

Anomaly Detection

Cluster Analysis

Supervised vs. Unsupervised Learning

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Approach & tools used by coding tutor

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PyCharm

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Jupyter Notebook

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Git & GitHub

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Visual Studio Code

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Google Colab

Hands-on coding classes

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Note taking

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Open Q&A

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Record lessons

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Pets are welcomed

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Parent feedback

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