Course Content
01. Course Introduction
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Lesson 01. Introduction to the Course
03:33
Lesson 02. Course Help and Welcome
00:36
02. Environment Set-Up
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Lesson 01. Python Environment Setup
11:14
03. Jupyter Overview
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Lesson 02. Jupyter Notebooks
13:48
Lesson 03. Optional Virtual Environments
09:51
04. Python Crash Course
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Lesson 01. Welcome to the Python Crash Course Section!
00:17
Lesson 02. Introduction to Python Crash Course
01:26
Lesson 03. Python Crash Course – Part 1
19:30
Lesson 04. Python Crash Course – Part 2
15:14
Lesson 05. Python Crash Course – Part 3
16:39
Lesson 06. Python Crash Course – Part 4
15:37
Lesson 07. Python Crash Course Exercises – Overview
03:35
Lesson 08. Python Crash Course Exercises – Solutions
11:56
05. Python for Data Analysis – NumPy
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Lesson 01. Welcome to the NumPy Section!
00:10
Lesson 02. Introduction to Numpy
02:13
Lesson 03. Numpy Arrays
16:50
Lesson 05. Numpy Array Indexing
18:23
Lesson 06. Numpy Operations
07:04
Lesson 07. Numpy Exercises Overview
02:46
Lesson 08. Numpy Exercises Solutions
15:32
06. Python for Data Analysis – Pandas
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Lesson 01. Welcome to the Pandas Section!
00:14
Lesson 02. Introduction to Pandas
01:44
Lesson 03. Series
10:39
Lesson 04. DataFrames – Part 1
15:31
Lesson 05. DataFrames – Part 2
17:10
Lesson 06. DataFrames – Part 3
09:12
Lesson 07. Missing Data
06:19
Lesson 08. Groupby
06:49
Lesson 09. Merging Joining and Concatenating
08:56
Lesson 10. Operations
12:04
Lesson 11. Data Input and Output
14:00
07. Python for Data Analysis – Pandas Exercises
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Lesson 02. SF Salaries Exercise Overview
01:55
Lesson 03. SF Salaries Solutions
15:26
Lesson 04. Ecommerce Purchases Exercise Overview
02:11
Lesson 05. Ecommerce Purchases Exercise Solutions
15:12
08. Python for Data Visualization – Matplotlib
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Lesson 01. Welcome to the Data Visualization Section!
00:22
Lesson 02. Introduction to Matplotlib
03:02
Lesson 03. Matplotlib Part 1
16:58
Lesson 04. Matplotlib Part 2
15:51
Lesson 05. Matplotlib Part 3
11:51
Lesson 06. Matplotlib Exercises Overview
01:47
Lesson 07. Matplotlib Exercises – Solutions
10:19
09. Python for Data Visualization – Seaborn
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Lesson 01. Introduction to Seaborn
02:58
Lesson 02. Distribution Plots
18:20
Lesson 03. Categorical Plots
17:18
Lesson 04. Matrix Plots
10:14
Lesson 05. Grids
08:30
Lesson 06. Regression Plots
07:14
Lesson 07. Style and Color
08:21
Lesson 08. Seaborn Exercise Overview
01:53
Lesson 09. Seaborn Exercise Solutions
07:08
10. Python for Data Visualization – Pandas Built-in Data Visualization
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Lesson 01. Pandas Built-in Data Visualization
13:27
Lesson 02. Pandas Data Visualization Exercise
01:23
Lesson 03. Pandas Data Visualization Exercise- Solutions
08:55
11. Python for Data Visualization – Plotly and Cufflinks
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Lesson 01. Introduction to Plotly and Cufflinks
03:22
Lesson 03. Plotly and Cufflinks
18:38
12. Python for Data Visualization – Geographical Plotting
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Lesson 01. Introduction to Geographical Plotting
00:58
Lesson 02. Choropleth Maps – Part 1 – USA
19:26
Lesson 03. Choropleth Maps – Part 2 – World
06:53
Lesson 04. Choropleth Exercises
03:12
Lesson 05. Choropleth Exercises – Solutions
10:01
13. Data Capstone Project
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Lesson 01. Welcome to the Data Capstone Projects!
00:17
Lesson 02. 911 Calls Project Overview
02:07
Lesson 03. 911 Calls Solutions – Part 1
14:29
Lesson 04. 911 Calls Solutions – Part 2
17:37
Lesson 06. Finance Data Project Overview
03:06
Lesson 07. Finance Project – Solutions Part 1
16:13
Lesson 08. Finance Project – Solutions Part 2
18:11
Lesson 09. Finance Project – Solutions Part 3
06:24
14. Introduction to Machine Learning
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Lesson 02. Welcome to the Machine Learning Section!
00:31
Lesson 03. Supervised Learning Overview
08:21
Lesson 04. Evaluating Performance – Classification Error Metrics
16:37
Lesson 05. Evaluating Performance – Regression Error Metrics
05:36
Lesson 06. Machine Learning with Python
09:27
15. Linear Regression
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Lesson 01. Linear Regression Theory
04:33
Lesson 03. Linear Regression with Python – Part 1
18:16
Lesson 04. Linear Regression with Python – Part 2
07:05
Lesson 05. Linear Regression Project Overview
02:31
Lesson 06. Linear Regression Project Solution
18:43
16. Cross Validation and Bias-Variance Trade-Off
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Lesson 01. Bias Variance Trade-Off
06:25
17. Logistic Regression
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Lesson 01. Logistic Regression Theory
11:53
Lesson 02. Logistic Regression with Python – Part 1
17:43
Lesson 03. Logistic Regression with Python – Part 2
16:57
Lesson 04. Logistic Regression with Python – Part 3
08:15
Lesson 05. Logistic Regression Project Overview
01:36
Lesson 06. Logistic Regression Project Solutions
11:05
18. K Nearest Neighbors
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Lesson 01. KNN Theory
05:38
Lesson 02. KNN with Python
19:39
Lesson 03. KNN Project Overview
01:12
Lesson 04. KNN Project Solutions
14:14
19. Decision Trees and Random Forests
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Lesson 01. Introduction to Tree Methods
06:53
Lesson 02. Decision Trees and Random Forest with Python
13:57
Lesson 03. Decision Trees and Random Forest Project Overview
03:10
Lesson 05. Decision Trees and Random Forest Solutions Part 2
08:46
20. Support Vector Machines
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Lesson 01. SVM Theory
04:36
Lesson 02. Support Vector Machines with Python
17:52
Lesson 03. SVM Project Overview
02:21
Lesson 04. SVM Project Solutions
10:09
21. K Means Clustering
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Lesson 01. K Means Algorithm Theory
05:15
Lesson 02. K Means with Python
12:35
Lesson 03. K Means Project Overview
02:53
Lesson 04. K Means Project Solutions
16:38
22. Principal Component Analysis
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Lesson 01. Principal Component Analysis
03:26
Lesson 02. PCA with Python
16:59
23. Recommender Systems
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Lesson 01. Recommender Systems
04:13
Lesson 02. Recommender Systems with Python – Part 1
13:36
Lesson 03. Recommender Systems with Python – Part 2
13:21
24. Natural Language Processing
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Lesson 01. Natural Language Processing Theory
05:07
Lesson 02. NLP with Python – Part 1
16:02
Lesson 03. NLP with Python – Part 2
18:47
Lesson 04. NLP with Python – Part 3
17:30
Lesson 05. NLP Project Overview
02:04
Lesson 06. NLP Project Solutions
19:26
25. Neural Nets and Deep Learning
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Lesson 02. Welcome to the Deep Learning Section!
00:21
Lesson 03. Introduction to Artificial Neural Networks (ANN)
02:15
Lesson 05. Perceptron Model
10:39
Lesson 06. Neural Networks
07:19
Lesson 07. Activation Functions
10:39
Lesson 08. Multi-Class Classification Considerations
10:34
Lesson 09. Cost Functions and Gradient Descent
18:13
Lesson 10. Backpropagation
14:47
Lesson 11. TensorFlow vs Keras
02:13
Lesson 12. TF Syntax Basics – Part One – Preparing the Data
10:49
Lesson 13. TF Syntax Basics – Part Two – Creating and Training the Model
13:59
Lesson 14. TF Syntax Basics – Part Three – Model Evaluation
12:56
Lesson 15. TF Regression Code Along – Exploratory Data Analysis
18:51
Lesson 16. TF Regression Code Along – Exploratory Data Analysis – Continued
13:16
Lesson 17. TF Regression Code Along – Data Preprocessing and Creating a Model
08:43
Lesson 18. TF Regression Code Along – Model Evaluation and Predictions
11:23
Lesson 19. TF Classification Code Along – EDA and Preprocessing
08:05
Lesson 20. TF Classification – Dealing with Overfitting and Evaluation
16:50
Lesson 21. TensorFlow 2.0 Project Options Overview
01:40
Lesson 22. TensorFlow 2.0 Project Notebook Overview
07:41
Lesson 23. Keras Project Solutions – Dealing with Missing Data
20:35
Lesson 24. Keras Project Solutions – Dealing with Missing Data – Part Two
14:46
Lesson 25. Keras Project Solutions – Categorical Data
12:02
Lesson 26. Keras Project Solutions – Data PreProcessing
17:23
Lesson 27. Keras Project Solutions – Data PreProcessing
03:45
Lesson 28. Keras Project Solutions – Creating and Training a Model
03:57
Lesson 29. Keras Project Solutions – Model Evaluation
09:42
Lesson 30. Tensorboard
18:22
26. Big Data and Spark with Python
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Lesson 01. Welcome to the Big Data Section!
00:23
Lesson 02. Big Data Overview
05:31
Lesson 03. Spark Overview
09:00
Lesson 05. AWS Account Set-Up
04:13
Lesson 07. EC2 Instance Set-Up
16:18
Lesson 08. SSH with Mac or Linux
04:49
Lesson 09. PySpark Setup
23:48
Lesson 10. Lambda Expressions Review
05:26
Lesson 11. Introduction to Spark and Python
08:17
Lesson 12. RDD Transformations and Actions
23:09
27. BONUS SECTION THANK YOU!
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Python for Data Science and Machine Learning Bootcamp

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