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Data Bootcamp

Introduction to Python

Python Fundamentals 1
Python Fundamentals 2
Functions and Classes
Intro to numpy
Intro to pandas
Reading Files and Split Apply Combine
Reading Files and Split Apply Combine
datetime, and matplotlib intro
More plotting with matplotlib and seaborn
Accessing Data with API’s
Extracting Data From HTML
Probability Distributions: Discrete and Continuous
Inference and Hypothesis Testing
Inference and Hypothesis Testing

Introduction to Predictive Modeling

Introduction to Linear Regression
Regression Part II
Model Complexity and Evaluation
Cross Validation and K-Nearest Neighbors
Classification I: Logistic Regression
Evaluating Classification Models
Introduction to Decision Trees
Random Forests

Time Series Models

Time Series and Forecasting Intro
Forecasting with sktime

Intro to Artificial Neural Networks

Intro ANN
Text Classification and Recurrent Neural Networks

Deploying Models

Streamlit

Unsupervised Learning

Clustering

Homework

Assignment 1
Homework 2: Introduction to numpy and pandas
Homework 3: Advanced Pandas and Introductory Plotting
API’s and Data Visualization
A Regression Model for Wages
Grid Searching and Time Series Forecasting

Extra Problems

Climb the Ladder!
Climb the Ladder!
Climb the Ladder!
Plotting with bokeh
BONUS: plotly
Using interactive widgets with the notebook

Repository
Open issue

Index

By Lenny

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