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Data Bootcamp

Introduction to Python

Installations and Introduction to your Terminal
Python Fundamentals 1
Data Structures and Introduction to Pandas
Intro to pandas
Introduction to pandas
Missing Values and Split Apply Combine
datetime, and matplotlib intro
More plotting with matplotlib and seaborn
More EDA, Time Series, and Geospatial Data
Accessing Data with API’s
Extracting Data From HTML

Modeling with Python

Inference and Hypothesis Testing
Introduction to Linear Regression and Linear Programming
Model Complexity and Evaluation
Regression Part II
Introduction to Classification and K-Nearest Neighbors
Classification II: Logistic Regression
Evaluating Classification Models
Introduction to Decision Trees
Random Forests
Boosted Ensembles
PCA: A Brief Introduction
Unsupervised Learning

Artificial Neural Networks

Introduction to Artificial Neural Networks
Convolutional Nets in PyTorch
Text Classification with Neural Networks
Using a pretrained model and dataset from huggingface
Fine tuning a model with torchvision

Bonus

Using a pretrained model and dataset from huggingface
Huggingface and gradio
Pretrained Models in an app

Library and WRDS

0. Setup WRDS Python API
Data Workflow Steps

Projects

Midterm Project

Homework

Assignment 1
Homework 3: Advanced Pandas and Introductory Plotting
A Regression Model for Wages
Problem 1: Difference in Groups

Class Notebook Solutions

Python Fundamentals 1
Data Structures and Introduction to Pandas
Introduction to pandas
Missing Values and Split Apply Combine
datetime, and matplotlib intro
More plotting with matplotlib and seaborn
Accessing Data with API’s
Extracting Data From HTML
Introduction to Linear Regression and Linear Programming
Regression Part II

Extras

Climb the Ladder!
Plotting with bokeh

Repository
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By Lenny

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