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1:45:52

Data Cleaning with Microsoft Excel & Data Visualisation with Microsoft Power BI

0:33:36

Day 14 - XGBoost & Data Leakage (Intermediate ML Lessons 6 & 7)

0:22:46

Day 13 - Pipelines & Cross-Validation (Intermediate ML Lessons 4 & 5)

0:38:37

Day 12 - Introduction, Missing Values & Categorical Variables (Intermediate ML Lessons 1, 2 & 3)

0:13:21

Day 11 - Machine Learning Competitions (Intro to ML Lesson 7)

0:15:11

Day 10 - Underfitting and Overfitting & Random Forests (Intro to ML Lessons 5 & 6)

0:30:04

Day 9 - Your First Machine Learning Model & Model Validation (Intro to ML Lessons 3 & 4)

0:14:03

Day 8 - How Models Work & Basic Data Exploration (Intro to ML Lessons 1 & 2)

0:26:25

Day 7 - Working with External Libraries (Python Lesson 7)

0:27:19

Day 6 - Strings and Dictionaries (Python Lesson 6)

0:37:14

Day 5 - Lists & Loops and List Comprehensions (Python Lessons 4 & 5)

0:25:18

Day 4 - Booleans and Conditionals (Python Lesson 3)

0:29:11

Day 3 - Functions and Getting Help (Python Lesson 2)

0:31:54

Day 1 & Day 2 - Level up to Contributor & Hello, Python (Python Lesson 1)

0:18:38

Forage Data@ANZ Program Task 2 - Predictive Analytics

0:45:59

Forage Data@ANZ Program Task 1 - Exploratory Data Analysis

0:18:39

Kaggle Titanic Survival Prediction Competition Part 2/2 - Data Preprocessing & Modelling

0:26:23

Kaggle Titanic Survival Prediction Competition Part 1/2 - Exploratory Data Analysis

0:10:01

Python Pandas Tutorial - Combining Dataframes Using Pandas

0:11:48

Python Pandas Tutorial - Handling Missing Data Using Pandas

0:07:10

Python Pandas Tutorial - Grouping & Sorting Data Using Pandas

0:10:25

Python Pandas Tutorial - Applying Functions In Pandas

0:09:02

Python Pandas Tutorial - Selecting Data Using Pandas

0:10:30

Python Pandas Tutorial - Creating Your Own Dataframe Using Pandas