Machine Learning

C1 Exploratory Data Analysis for ML 12 lessons

M1 EDA Fundamentals 3

1Introduction to EDA▸ 2Data Understanding▸ 3T Final Module Assessment▸

M2 Data Cleaning 3

1Handling Missing Values▸ 2Outliers and Data Types▸ 3T Final Module Assessment▸

M3 Feature Engineering 3

1Encoding and Scaling▸ 2Feature Creation and Selection▸ 3T Final Module Assessment▸

M4 Stats and Visualization 3

1Statistical Testing▸ 2Advanced Visualization▸ 3T Final Module Assessment▸

C2 Supervised ML Regression 12 lessons

M1 Intro to Regression 3

1Supervised Learning Overview▸ 2Regression Basics▸ 3T Final Module Assessment▸

M2 Linear Regression 3

1Simple Linear Regression▸ 2Multiple Linear Regression▸ 3T Final Module Assessment▸

M3 Polynomial Regularized 3

1Polynomial Regression▸ 2Regularization▸ 3T Final Module Assessment▸

M4 Evaluation and Project 3

1Evaluation Metrics▸ 2Regression Project▸ 3T Final Module Assessment▸

C3 Supervised ML Classification 12 lessons

M1 Intro to Classification 3

1Classification Concepts▸ 2Classification Metrics▸ 3T Final Module Assessment▸

M2 Logistic Regression KNN 3

1Logistic Regression▸ 2KNearest Neighbors▸ 3T Final Module Assessment▸

M3 Trees Forests SVM 3

1Decision Trees▸ 2Random Forests and SVM▸ 3T Final Module Assessment▸

M4 Ensemble and Evaluation 3

1Ensemble Methods▸ 2Model Selection and Evaluation▸ 3T Final Module Assessment▸

C4 Unsupervised ML 12 lessons

M1 Intro to Unsupervised 3

1Unsupervised Learning Overview▸ 2Distance and Similarity▸ 3T Final Module Assessment▸

M2 Clustering Algorithms 3

1KMeans Clustering▸ 2Hierarchical and DBSCAN▸ 3T Final Module Assessment▸

M3 Dimensionality Reduction 3

1PCA Principal Component Analysis▸ 2tSNE and UMAP▸ 3T Final Module Assessment▸

M4 Anomaly Detection 3

1Anomaly Detection Methods▸ 2RealWorld Applications Project▸ 3T Final Module Assessment▸

C5 Deep Learning and Reinforcement Learning 13 lessons

M1 Neural Networks 3

1Neural Network Basics▸ 2Training Neural Networks▸ 3T Final Module Assessment▸

M2 CNNs 3

1CNN Architecture▸ 2Transfer Learning and Applications▸ 3T Final Module Assessment▸

M3 RNNs 3

1RNN Architecture▸ 2Sequence Applications▸ 3T Final Module Assessment▸

M4 Reinforcement Learning 3

1RL Fundamentals▸ 2Deep Reinforcement Learning▸ 3T Final Module Assessment▸

M5 Final Project 1

1Deep Learning Project▸

C6 Machine Learning Capstone 12 lessons

M1 Project and Data 3

1Problem Definition▸ 2Data Preparation▸ 3T Final Module Assessment▸

M2 Model Development 3

1Model Training▸ 2Hyperparameter Tuning▸ 3T Final Module Assessment▸

M3 Evaluation and Optimization 3

1Comprehensive Evaluation▸ 2Optimization and Interpretation▸ 3T Final Module Assessment▸

M4 Deployment and Submission 3

1Model Deployment▸ 2Final Submission▸ 3T Final Module Assessment▸