Data Science Projects with Python

Data Science Projects with Python

Beginner

98 Lessons

24h

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

7 Projects
52 Playgrounds
7 Quizzes

This course includes

7 Projects
52 Playgrounds
7 Quizzes

Course Overview

As businesses gather vast amounts of data, machine learning is becoming an increasingly valuable tool for utilizing data to deliver cutting-edge predictive models that support informed decision-making. In this course, you will work on a data science project with a realistic dataset to create actionable insights for a business. You’ll begin by exploring the dataset and cleaning it using pandas. Next, you will learn to build and evaluate logistic regression classification models using scikit-learn. You will...Show More

What You'll Learn

Hands-on experience in data exploration, data processing, data modeling and data visualization using pandas, scikit-learn, and Matplotlib

The ability to evaluate model performance and interpret model predictions

A working knowledge of how predictive models can support business decision-making

An understanding of the mathematical foundations of machine learning models

What You'll Learn

Hands-on experience in data exploration, data processing, data modeling and data visualization using pandas, scikit-learn, and Matplotlib

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Course Content

1.

Introduction

2.

Data Exploration and Cleaning

(Challenge) Exploring Remaining Financial Features in Dataset

Project

3.

Introduction to scikit-learn and Model Evaluation

(Challenge) Logistic Regression and Precision-Recall Curve

Project

4.

Details of Logistic Regression and Feature Extraction

(Challenge) Logistic Regression Model and Coefficients

Project

5.

The Bias-Variance Trade-Off

(Challenge) Cross-Validation and Feature Engineering

Project

6.

Decision Trees and Random Forests

13 Lessons

(Challenge) Cross-Validation Grid Search with Random Forest

Project

7.

Gradient Boosting, XGBoost, and SHAP Values

12 Lessons

(Challenge) XGBoost and SHAP Explanation for Case Study Data

Project

8.

Test Set Analysis, Financial Insights, and Delivery to the Client

10 Lessons

(Challenge) Deriving Financial Insights

Project

9.

Appendix

1 Lesson

Course Author

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Anthony Walker

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Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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