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Readme.md

DS 204 - Class Guide

2/4/2019 - 4/15/2019

Mondays & Wednesdays, 8 p.m. - 11 p.m. EST

Materials:

Contact Info:

Schedule

Class Date Recording Repository Events
Unit 1: Your Development Environment Get familiar with Python, Jupyter, Git, the command line, and fundamental data science concepts.
1 - Welcome to Data Science 2/4 Link Link
2 - Your Development Environment 2/6 Link Link
3 - Python Foundations 2/11 Link Link Share Project 1
Unit 2: Statistics in Python Get introduced to fundamental concepts in statistics, and learn to perform basic data data analysis operations in Python.
4 - Exploratory Data Analysis in Pandas 2/13 Link Link
5 - Statistics in Python 2/20 Link Link Unit 1 Project: Python Share Project 2
6 - Experiments & Hypothesis Testing 2/25 Link Link
7 - Data Visualization in Python 2/27 Link Link
8 - Linear Regression 3/4 Link Link
Unit 3: Predictive Modeling Learn to build models that can predict a target variable from a given set of features in tabular data.
9 - Train-Test Split & Bias-Variance 3/6 Link Link Unit 2 Project: EDA Share Project 3** Final Project Pt 1:** Proposal
10 - KNN / Classification 3/11 Link Link
11 - Logistic Regression 3/13 Link Link
12 - Decision Trees 3/18 Link Link
13 - Ensembling and Random Forests 3/20 Link Link
14 - Natural Language Processing 3/25 Link Link
15 - Working With APIs 3/27 Link Link Unit 3 Project: Modeling Share Final Project** Final Project Pt 2:** EDA
Unit 4:** Special Topics**Get introduced to more specialized application areas in data science.
16 - Time Series 4/01 Link Link
17 - FLEX (Catch up, add bonus material, practice) 4/03 Link Link
18 - FLEX (Catch up, add bonus material, practice) 4/08 Link Link
19 - FLEX (Catch up, add bonus material, practice) 4/10 Link Link
20 - Present final projects 4/15 Link Link Final Project Pt 4: Presentation