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VSCode
Terminal
Git
(Ana)Conda
Linux (Ubuntu)
MacOS
Windows 10
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
Remote Numpy
Pandas
Matplotlib
Loading CSV Data
Cleaning Data
Analyzing Data
Plotting Data
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
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
Week 5 : Cross Validation, Regularization, KNN
Remote Cross Validation
Bias vs Variance
Regularization
Ridge Regression
Lasso
KNN
Week 6 : Logistic Regression, ROC, Decision Trees
Remote Logistic Regression
ROC
AUC
Accuracy
Precison
Recall
Confusion Matrix
Information Theory
Decision Trees
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
In person Capstone Week
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