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Course content
Intro (What You Will Learn in This Section)
00:28
Installing Tableau Desktop and Tableau Public (FREE) [updated]
04:07
Challenge Description + View Data in File
02:32
Connecting Tableau to a Data File - CSV File
05:17
Navigating Tableau - Measures and Dimensions
08:42
Creating a Calculated Field
06:15
Adding Colours
07:38
Adding Labels and Formatting
11:00
Exporting Your Worksheet
06:23
Section Recap
03:34
Quiz: Tableau Basics
Intro (What You Will Learn in This Section)
00:44
Get the Dataset + Project Overview
07:13
Connecting Tableau to an Excel File
03:57
How To Visualise an AB Test in Tableau?
06:29
Working With Aliases
04:06
Adding a Reference Line
04:53
Looking For Anomalies
08:36
Handy Trick to Validate Your Approach / Data
09:14
Section Recap
05:04
Intro (What You Will Learn in This Section)
00:44
Creating Bins & Visualizing Distributions
09:55
Creating a Classification Test For a Numeric Variable
04:25
Combining Two Charts and Working With Them in Tableau
07:06
Validating Tableau Data Mining With a Chi-Squared Test
10:29
Chi-Squared Test When There Is More Than 2 Categories
08:16
Quick Note
Visualising Balance and Estimated Salary Distribution
11:04
Extra: Chi-Squared Test (Stats Tutorial)
19:12
Extra: Chi-Squared Test Part 2 (Stats Tutorial)
09:11
Section Recap
05:44
Part Completed
01:31
Intro (What You Will Learn in This Section)
01:15
Get the Dataset
04:12
Assumptions of Linear Regression
04:27
Dummy Variables
08:05
Dummy Variable Trap
02:11
Understanding the P-Value
11:45
Ways to Build a Model: BACKWARD, FORWARD, STEPWISE
15:42
Backward Elimination - Practice Time
16:08
Using Adjusted R-squared to Create Robust Models
10:17
Interpreting Coefficients of MLR
12:47
Section Recap
03:09
Intro (What You Will Learn in This Section)
01:35
Get the Dataset
04:20
Binary Outcome: Yes/No-Type Business Problems
09:09
Logistic Regression Intuition
17:03
Your First Logistic Regression
07:49
False Positives and False Negatives
08:01
Confusion Matrix
04:57
Interpreting Coefficients of a Logistic Regression
10:04
Intro (What You Will Learn in This Section)
01:02
Get the Dataset
07:25
What is Geo-demographic Segmentation?
05:06
Let's Build the Model - First Iteration
08:27
Let's Build the Model - Backward Elimination: STEP-BY-STEP
11:11
Transforming Independent Variables
10:09
Creating Derived Variables
06:08
Checking for Multicollinearity Using VIF
08:06
Correlation Matrix and Multicollinearity Intuition
08:21
Model is Ready and Section Recap
06:28
Intro (What You Will Learn in This Section)
00:38
Accuracy Paradox
02:12
Cumulative Accuracy Profile (CAP)
11:16
How to Build a CAP Curve in Excel
14:27
Assessing Your Model Using the CAP Curve
07:12
Get My CAP Curve Template
06:20
How To Use Test Data To Prevent Overfitting Your Model
03:35
Applying the Model To Test Data
07:59
Comparing Training Performance and Test Performance
11:34
Section Recap
03:33
Intro (What You Will Learn in This Section)
00:34
Power Insights From Your CAP
13:53
Coefficients of a Logistic Regression - Plan of Attack (Advanced Topic)
03:47
Odds Ratio (Advanced Topic)
08:30
Odds Ratio vs Coefficients in a Logistic Regression (Advanced Topic)
07:08
Deriving Insights From Your Coefficients (Advanced Topic)
13:14
Section Recap
03:26
Intro (What You Will Learn in This Section)
00:24
Working With Data
01:16
What Is a Data Warehouse? What Is a Database?
03:28
Setting up Microsoft SQL Server 2019 for Practice
07:22
Important: Practice Database
09:36
ETL for Data Science - What is Extract Transform Load (ETL)?
02:01
Microsoft BI Tools: What is SSDT-BI and What Are SSIS/SSAS/SSRS ?
04:05
Installing SSDT With MSVS Shell
04:25
Intro (What You Will Learn in This Section)
00:51
Starting and Navigating an SSIS Project
01:47
Creating a Flat File Source Task and OLE DB Destination
01:53
Setting Up Your Flat File Source Connection
06:08
Setting Up Your Database Connection and Creating a RAW Rable
06:58
Run the Upload & Disable
02:40
Due Dilligence: Upload Quality Assurance
02:01
Intro (What You Will Learn in This Section)
00:50
Download the Dataset For This Section
00:47
How Excel Can Mess Up Your Data
03:46
Bulletproof Blueprint for Data Wrangling Before the Load
07:31
SSIS Error: Text Qualifier Not Specified
07:16
What Do You Do When Your Source File Is Corrupt? (Part 1)
18:02
What Do You Do When Your Source File Is Corrupt? (Part 2)
06:10
SSIS Error: Data Truncation
15:56
Handy Trick For Finding Anomalies in SQL
03:46
Automating Error Handling in SSIS: Conditional Split
08:20
Automating Error Handling in SSIS: Conditional Split (Level 2)
09:03
How To Analyze the Error Files
16:41
Due Diligence: the One Thing You HAVE To Do Every Time
04:57
Types of Errors in SSIS
04:01
Summary
19:07
Homework
03:39
Intro (What You Will Learn in This Section)
00:32
Download the Dataset For This Section
00:38
Getting To Know MS SQL Management Studio
02:14
Shortcut to Upload the Data
04:20
SELECT * Statement
05:52
Using the WHERE Clause To Filter Data
05:50
How To Use Wildcards / Regular Expressions in SQL (% and _)
04:37
Comments in SQL
02:11
Order By
05:49
Data Types in SQL
07:54
Implicit Data Conversion in SQL
03:35
Using Cast() vs Convert()
03:51
Working with NULLs
05:04
Understanding How LEFT, RIGHT, INNER, and OUTER Joins Work
06:18
Joins With Duplicate Values
02:33
Joining On Multiple Fields
05:21
Practicing Joins
04:57
Intro (What You Will Learn in This Section)
00:57
RAW, WRK, DRV Tables
05:54
Download the Dataset For This Section
01:32
Create Your First Stored Procedure in SQL
03:31
Executing Stored Procedures
02:50
Modifying Stored Procedures
08:26
Create Table
09:08
Insert INTO
05:42
Check If Table Exists + Drop Table + Truncate
06:00
Intermediate Recap - Procedures
04:16
Create the Procedure For the Second File
11:27
Adding Leading Zeros
07:16
Converting Data On the Fly
10:22
How To Create a Procedure Template
07:52
Archiving Procedures
04:38
What You Can Do With These Tables Going Forward [drv files etc.]
13:50
Intro (What You Will Learn in This Section)
00:54
Download the Dataset For This Section
00:47
Upload the Data to RAW Table
10:50
Create Stored Procedure
05:07
How To Deal With Errors Using the isnumeric() Function
07:45
How To Deal With Errors Using the len() Function
07:37
How to Deal With Errors Using the isdate() Function
07:40
Additional Quality Assurance Check: Balance
03:52
Additional Quality Assurance Check: ZipCode
03:17
Additional Quality Assurance Check: Birthday
04:09
Part Completed
09:53
ETL Error Handling "Vehicle Service" Project
07:45
Intro (What You Will Learn in This Section)
01:42
Case Study
02:00
Analysing the Intro
03:33
Intro Dissection - Recap
09:27
REAL Data Science Presentation Walkthrough - Make Your Audience Say "WOW"
16:29
My Brainstorming Method
03:03
How To Present To Executives
05:27
The Truth Is Not Always Pretty
02:46
Passion and the Wow-factor
01:59
Extra: My Full Presentation | LIVE 2015
16:20
Extra: Links To Other Examples of Good Storytelling
Advanced Data Mining with Tableau: Visualising Credit Score & Tenure
05:44
Advanced Data Mining with Tableau: Chi-Squared Test for Country
04:18
ETL Error Handling (Phases 1 and 2)
19:52
ETL Error Handling "Vehicle Service" Project (Part 1 of 3)
19:09
ETL Error Handling "Vehicle Service" Project (Part 2 of 3)
10:42
ETL Error Handling "Vehicle Service" Project (Part 3 of 3)
14:35