Data Science Cohort 4

Tools

VSCode
Terminal
Git
(Ana)Conda

Operating System

Linux (Ubuntu)
MacOS
Windows 10

Schedule

Week 1 : Python

In Person
Computer Setup
Python Fundamentals
Git
Github
Python OOP
Testing with Pytest
Monte Carlo Techniques
Overview of Probability and Linear Algebra
Modeling with KNN
Assessment 1

Repositories

Week 2 : EDA

Remote
Numpy
Pandas
Matplotlib
Loading CSV Data
Cleaning Data
Analyzing Data
Plotting Data

Recordings

Repositories

Week 3 : Probabilty and Statistics

Remote
Statistics Overview
Moments
Counting
Set Theory
Probability Theory
Probability Distributions
Bayes Law
Central Limit Theorm
Law of Large Numbers
Sampling

Recordings

Repositories

Week 4 : Hypothesis Testing, Linear Algebra, Linear Regression

In Person
Hypothesis Testing (1 and 2-sample, proportions)
Linear Algebra
Simple and Multiple Linear Regression
Metrics
Week 4 Exam

Repositories

Week 5 : Cross Validation, Regularization, KNN

Remote
Cross Validation
Bias vs Variance
Regularization
Ridge Regression
Lasso
KNN

Recordings

Repositories

Week 6 : Logistic Regression, ROC, Decision Trees

Remote
Logistic Regression
ROC
AUC
Accuracy
Precison
Recall
Confusion Matrix
Information Theory
Decision Trees

Recordings

Repositories

Week 7 : Assessment, Gradient Descent, Optimization Theory, Random Forest

In Person
Assessment
Gradient Descent
Integrals
Partial Derivatives
Bagging
Random Forest
Boosting
AdaBoost
GradientBoost

Week 8 : Recommender Systems, PCA, NMF

Remote
Unsupervised Learning
Clustering
KMeans
Hierarchical Clustering
Recommender Systems
Principal Compontent Analysis
Matrix Factorization
Dimensionality Reduction

Week 9 : Neural Networks Part I

In Person
Thery of Neural Networks
Feed forward
Back propagation
Fully Connected Networks
Convolutional Neural Networks

Week 10 : Neural Networks Part II

Remote
Tensorflow
Keras
CPUs vs GPUs

Week 11 : Capstone

Remote
Work on Capstone

Week 12: Capstone

Remote
Work on Capstone

Week 13: Capstone

In person
Capstone Week
Presentations