Data Science & Machine Learning with Python enroll
Learn the foundations of data science and machine learning using Python. Learn how to think like a data scientist. Understand what it means to learn from data using ML tools and algorithms. In this course you'll use Jupyter Lab, Numpy, Matplotlib, Seaborn, Pandas, Scikit Learn, and much more to dive into ever more advanced analysis and predictive modeling using data and code.
21 Sections · 203 Pages · By Gilad Gressel
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Level
Intermediate to advanced. This course assumes you are already comfortable with Python.
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Duration
250 Hours. Or, ~4 months of dedicated learning @ 15-20 hours per week
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What's included
79 lessons. 77 videos. 15 Jupyter Notebooks. 19 Practical Labs. 25 quizzes. 1 Capstone Project. And much more!
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Certificate
250-Hour Data Science & Machine Learning Certificate
This course is part of the following career track:
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2) Let's Get Started
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Video: DS/ML Course Introduction4 min
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Video: What Will You Do in This Course?3 min
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Video: Prerequisites for Data Science and Machine Learning1 min
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Video: Tools and Tips for Success6 min
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What is a Data Scientist5 min
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About Writing Code6 min
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Lab: Mini Research Project3 min
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Assignments
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What You Will Learn5 min
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Why Are You Here?
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3) The Essence of Machine Learning
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5) Learning Numpy, Pandas, and Matplotlib
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Video: Love the Product Not the Tools5 min
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DS/ML Course Learning Strategy4 min
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Link: O'REILLY Python Data Science Handbook
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Video: What is Numpy14 min
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Additional Numpy Resources4 min
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Video: What is Matplotlib7 min
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Additional Matplotlib Resources3 min
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Video: Python Pandas13 min
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Additional Pandas Resources3 min
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Video: What is Scikit Learn2 min
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Assignments
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Lab: Tech Stack Practice3 min
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Feedback
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Feedback: Learning Numpy, Pandas, and Matplotlib
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6.5) Exploratory Data Analysis
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Video: What is EDA12 min
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Video: Exploratory Data Analysis30 min
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Introduction to EDA with Python Pandas8 min
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Video: Boxplots (Box and Whisker)12 min
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Create Boxplots with Seaborn & Matplotlib5 min
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Video: How to Find Outliers11 min
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How to Find Outliers10 min
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Video: What is a Histogram14 min
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Create Histograms with Pandas, Seaborn & Matplotlib12 min
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Video: What is a Plot Diagram18 min
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Plot Diagrams with Matplotlib & Seaborn10 min
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Video: Bar Chart and Pie Chart with Matplotlib3 min
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How to Make a Bar Chart with Matplotlib4 min
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Video: Correlation Matrix and Homoscedasticity13 min
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Correlation Matrix and Homoscedasticity6 min
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Video: Auto Exploratory Data Analysis18 min
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Auto Exploratory Data Analysis3 min
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Quiz: Exploratory Data Analysis
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Assignment
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Lab: Exploratory Data Analysis5 min
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Feedback
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Feedback: Exploratory Data Analysis
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7) Linear Regression I
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8) Linear Regression II
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Video: What is Gradient Descent10 min
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Video: The Loss Function aka Cost Function Formula7 min
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Video: Using the Gradient Descent13 min
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What is Gradient Descent14 min
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Quiz: Gradient Descent
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Video: What is Regularization11 min
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Regularization in Machine Learning3 min
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Quiz: Regularization
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Video: Feature Scaling15 min
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Quiz: Feature Scaling
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Feature Scaling in Scikit Learn3 min
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Assignment and Solutions
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Lab: Gradient Descent and Regularization3 min
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Video Solution: Gradient Descent and Regularization11 min
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Lab: Linear Regression3 min
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Video Solution: California Housing Lab28 min
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Feedback
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Feedback: Linear Regression II
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9) Model Evaluation I
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How to Improve Predictive Modeling5 min
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Video: Improve Predictive Modeling with Test Set17 min
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How to Use Train Test Split9 min
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Video: What is a Baseline Model4 min
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Quiz: Baseline Models
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Scikit Learn Baseline Model3 min
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What is a Random State Generator5 min
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Quiz: Random Seed
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Assignment and Solution
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Lab: California Housing Extended3 min
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Video Solution: California Housing Extended Lab13 min
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Feedback
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Feedback: Model Evaluation I
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10) Model Evaluation II
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Video: Classification vs. Regression6 min
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Quiz: Classification Intro
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Video: KPI Metrics8 min
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Video: Model Accuracy and Confusion Matrix10 min
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Video: F1 Score, Precision and Recall11 min
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Metrics Don't Affect Performance!10 min
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Quiz: Metrics
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What is a Confusion Matrix7 min
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F1 Score, Precision and Recall5 min
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Assignment
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Lab: Detect Breast Cancer Metrics3 min
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Video Lab Solution: Detect Breast Cancer Metrics13 min
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Feedback
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Feedback: Model Evaluation II
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11) Classification with Decision Trees
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Video: Decision Trees in Machine Learning14 min
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Decision Tree Analysis6 min
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Quiz: Tree Parameters
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Video: How to Split Data and Gini Coefficient11 min
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Decision Tree Information Gain and Entropy10 min
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Quiz: Splitting
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Assignment
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Lab: Classify Spam with Decision Tree3 min
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Video Solution: Lab Classify Spam with Decision Tree13 min
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Feedback
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Feedback: Classification with Decision Trees
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12) Model Validation
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How to Use the Test Set5 min
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Video: Cross Validation & Validation Sets13 min
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Quiz: Validation Schemes
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Video: Learning Curve - Overfitting and Underfitting17 min
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Video: Validation Curve and Gridsearch13 min
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Validation and Learning Curve with Overfitting and Underfitting6 min
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Quiz: Validation and Learning Curves
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Data Validation and Sklearn Cross Validation10 min
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Assignment
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Lab: Classify Spam3 min
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Video Solution: Classify Spam Histogram Lab8 min
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Video Solution: Classify Spam Gridsearch Lab9 min
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Video Solution: Classify Spam Learning Curve Lab2 min
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Video Solution: Classify Spam Validation Curve Lab8 min
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Video Solution: Feature Selection and Ranking2 min
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Feedback
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Feedback: Model Validation
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13) Ensemble Methods
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Introduction: Ensemble Methods - Bagging & Boosting3 min
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Video: Bagging8 min
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Video: Random Forest Classifier6 min
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Quiz: Bagging
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Video: Boosting9 min
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Quiz: Boosting
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Stacking & Gradient Boosting5 min
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Assignment
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Lab: Classify Handwritten Digits3 min
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Video Solution: Classify Handwritten Digits Lab8 min
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Feedback
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Feedback: Ensemble Methods
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14) Dealing with Data
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Structured vs Unstructured Data4 min
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Video: Dealing with Data9 min
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Structured Data
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Video: Working with Tabular Data9 min
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Quiz: Tabular and Missing Data
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Encoding Categorical Data and Data Imputing4 min
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Unstructured Data
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Video: Computer Vision and Sound Models13 min
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Quiz: Computer Vision and Sound Data
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Quick Look Ahead: Deep Learning3 min
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Video: Introduction to NLP11 min
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Video: Introduction to Sklearn Pipelines8 min
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Quiz: NLP and Pipelines
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Python NLP and Sklearn Resources7 min
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Link: Data Cleaning - Tidy Data Paper
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Assignments
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Lab: Clean Dataset3 min
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Video Solution: Clean Dataset Lab17 min
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Lab: Basic NLP3 min
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Video Solution: Basic NLP Lab21 min
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Feedback
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Feedback: Dealing with Data
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15) Unsupervised Learning Intro
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16) Clustering
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Video: Introduction to Clustering4 min
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Video: K-Means Clustering8 min
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Link: Visualize K-Means Clustering
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Video: DBScan7 min
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Link: Visualize DBScan Clustering
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Quiz: Clustering
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Parameters for K-Means and DBScan Clustering5 min
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Video: Define Cluster Distance and Metrics11 min
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Define Cluster Distance Mathematically5 min
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What is L2-Norm?6 min
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Assignment
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Lab: Cluster Customer Data3 min
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Video Solution: Cluster Customer Data (K-Means) Lab7 min
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Video Solution: Cluster Customer Data (DBScan) Lab7 min
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Feedback
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Feedback: Clustering
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17) Dimensionality Reduction
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Video: The Curse of Dimensionality13 min
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The Curse of Dimensionality3 min
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Quiz: What Dimension?
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Video: Principal Component Analysis13 min
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Quiz: Reduce What?
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Sklearn PCA Parameters & Attributes3 min
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Sklearn Dimensionality Reduction4 min
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Assignment
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Lab: PCA Customer Clustering3 min
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Video Solution: PCA Customer Clustering Lab8 min
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Lab Link: PCA with Python Data Science Handbook
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Lab Link: K-Means with Python Data Science Handbook
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Feedback
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Feedback: Dimensionality Reduction
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18) Putting It All Together - Capstone Project
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Video: Data Science and ML Capstone Project9 min
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Elements of the Capstone Project3 min
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DS/ML Capstone Project Ideas7 min
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DS/ML Dataset Resources3 min
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Assignment
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DS/ML Capstone Proposal Instructions6 min
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Lab: DS/ML Capstone Proposal Form6 min
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Semi-Formal Research Paper Format6 min
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Video: Capstone Project Format5 min
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DS/ML Capstone Report Template3 min
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19) Next Steps
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Video: DS/ML Course Review8 min
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What to Study Next4 min
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Additional ML Resources: Books, Videos, Courses3 min
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Additional Resources: Deep Learning3 min
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Additional Resources: DevOps and Cloud3 min
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Get Connected!
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Data Science Online Communities3 min
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Data Science Blogs3 min
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About Work and Jobs
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Data Science and ML Job Preparation9 min
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Feedback: DS/ML Course
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Completion Certificate