-
1
Welcome (00:00)
-
Phase 1 Overview
-
Reward of EE Journal
-
-
2
Week 1 (00:00)
-
Day 1 AM - Machine Learning Landscape
-
Day 1 PM - Machine Learning Problem Framing
-
P1W1D1 Non Graded Challenge - ML Problem Framing
-
Day 2 AM - Math for Machine Learning: Vector & Matrix
-
Day 2 PM - Math for Machine Learning: Multivariate Calculus (Derivative)
-
P1W1D2 Non Graded Challenge - EDA
-
Day 3 AM - Feature Engineering: Part 1
-
Day 3 PM - Feature Engineering: Part 2
-
P1W1D3 Non Graded Challenge - Feature Engineering
-
Day 4 AM - Linear Regression
-
Day 4 PM - Polynomial & Logistic Regression
-
P1W1D4 Non Graded Challenge - Model Training and Evaluation (Linear Regression)
-
Day 5 AM - Technical Test 1 - Business Use Case & Data Analysis
-
Day 5 PM - Graded Challenge 4
-
-
3
Week 2 (00:00)
-
Day 1 AM - Classification Model Evaluation
-
Day 1 PM - K-Nearest Neighbors (KNN) & Naive Bayes
-
P1W2D1 Non Graded Challenge - ML Problem Framing on Classification
-
Day 2 AM - Support Vector Machine (SVM)
-
Day 2 PM - Decision Tree & Ensemble Learning
-
P1W2D2 Non Graded Challenge - EDA
-
Day 3 AM - Hyperparameter Tuning
-
Day 3 PM - Algorithm Chains & Pipelines
-
P1W2D3 Non Graded Challenge - Feature Engineering
-
Day 4 AM - Milestone 1 Phase 0 Presentation
-
Day 4 PM - Data Balancing
-
P1W2D4 Non Graded Challenge - Classification Model
-
Day 4 PM - Career Assignments
-
Day 5 AM - Technical Test 2 - Python & SQL
-
Day 5 PM - Graded Challenge 5 - Classification
-
-
4
Week 3 (10:58)
-
Day 1 AM - Recommender System
-
Day 1 PM - Dimensionality Reduction
-
Day 1 - Career Class // Interview 101 - Self Learning
-
Day 2 AM - Clustering: Part 1
-
Day 2 PM - Clustering: Part 2
-
Day 3 AM - Time Series: Part 1
-
Day 3 PM - Time Series: Part 2
-
P1W3D3 Non Graded Challenge - Time Series
-
Day 4 AM - Communication Practice
-
Day 4 PM - Communication Practice
-
Day 5 AM - Technical Test 3 - ML - Data Preparation
-
Day 5 PM - Graded Challenge 6 - Unsupervised Learning
-
-
5
Week 4 (00:00)
-
Day 1 AM - Live Code 4 - Time Series
-
Day 1 PM - Anomaly Detection
-
Day 2 AM - Model Deployment
-
Day 2 PM - MLOps
-
Day 3 AM - Milestone Mentoring Session
-
Day 3 PM - Milestone Mentoring Session
-
Day 4 AM - Free Time
-
Day 4 PM - Free Time
-
Day 5 AM - Free Time
-
Day 5 PM - Free Time
-
