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Become a Professional Data Analyst - Earn $60k Per Year
Section 1 Welcome
Lecture 1 Welcome (3:39)
Lecture 2 Anaconda (7:42)
Lecture 3 Intro to Jupyter Notebook (9:52)
Lecture 4 Using the Jupyter Notebook (11:51)
Section 2 Vectorizing Operations with NumPy
Lecture 5 NumPy Python’s Vectorization Solution (7:48)
Lecture 6 NumPy Arrays Creation, Methods and Attributes (23:21)
Lecture 7 Using NumPy for Simulations (11:54)
Section 3 Pandas
Lecture 8 The Pandas Library (14:09)
Lecture 9 Main Properties, Operations and Manipulations (13:35)
Lecture 10 Answering Simple Questions about a Dataset – Part 1 (11:36)
Lecture 11 Answering Simple Questions about a Dataset – Part 2 (15:54)
Section 4 Visualization and Exploratory Data Analysis
Lecture 12 Basics of Matplotlib (6:59)
Lecture 13 Pyplot (10:20)
Lecture 14 The Object-Oriented Interface (9:05)
Lecture 15 Common Customizations (11:46)
Lecture 16 EDA with Seaborn and Pandas (9:10)
Lecture 17 Analysing Variables Individually (17:21)
Lecture 18 Relationships between Variables (15:20)
Section 5 Statistical Computing with Python
Lecture 19 SciPy and the Statistics Sub-Package (4:00)
Lecture 20 Alcohol Consumption (10:36)
Lecture 21 Hypothesis Testing - Part 1 (8:07)
Lecture 22 Hypothesis Testing - Part 2 (5:20)
Section 6 Predictive Analytics Models
Lecture 23 Introduction to Predictive Analytics Models (6:13)
Lecture 24 The Scikit-Learn Library – Building a Simple Predictive Model (6:43)
Lecture 25 Classification – Predicting the Drinking Habits of Teenagers (8:17)
Lecture 26 Regression – Predicting House Prices (7:56)
Lecture 25 Classification – Predicting the Drinking Habits of Teenagers
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