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Start Your Free Trial Today >>Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!
Extremely Hands-On... Incredibly Practical... Unbelievably Real!
This is not one of those fluffy classes where everything works out just the way it should and your training is smooth sailing. This course throws you into the deep end.
In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities - you name it!
This course will give you a full overview of the Data Science journey. Upon completing this course you will know:
How to clean and prepare your data for analysis
How to perform basic visualisation of your data
How to model your data
How to curve-fit your data
And finally, how to present your findings and wow the audience
The course is structured the four main parts:
Part 1: Visualisation
Introduction to Tableau
How to use Tableau for Data Mining
Advanced Data Mining With Tableau
Part 2: Modelling
Stats Refresher
Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Building a robust geodemographic segmentation model
Assessing your model
Drawing insights from your model
Model maintenance
Part 3: Data Preparation
Business Intelligence (BI) Tools
ETL Phase 1: Data Wrangling before the Load
ETL Phase 2: Step-by-step guide to uploading data using SSIS
Handling errors during ETL (Phases 1 & 2)
SQL Programming for Data Science
ETL Phase 3: Data Wrangling after the load
Handling errors during ETL (Phase 3)
Part 4: Communication
Working with people
Presenting for Data Scientists
This course will give you so much practical exercises that real world will seem like a piece of cake when you graduate this class. This course has homework exercises that are so thought provoking and challenging that you will want to cry... But you won't give up! You will crush it. In this course you will develop a good understanding of the following tools:
SQL
SSIS
Tableau
Gretl
Why Choose This Course?
Expert Knowledge: Learn from industry leaders with extensive experience in Data Science.
Hands-On Learning: Engage with practical exercises and real-world case studies to apply your knowledge.
Flexibility: Whether you are starting from scratch or looking to update your skills, this course is structured to cater to your learning pace and style.
Community and Support: Join a community of like-minded learners and professionals, with access to expert support throughout your learning journey.
This course has pre-planned pathways. Using these pathways you can navigate the course and combine sections into YOUR OWN journey that will get you the skills that YOU need.
Or you can do the whole course and set yourself up for an incredible career in Data Science.
The choice is yours. Join the class and start learning today!
See you inside!
Sincerely,
Kirill Eremenko
$35
/ MonthAccelerate your Career and boost your Earning Potential with our Expert Instructors & Community! What Youāll Unlock: - š 40+ Courses (over 200 hours!) - š 17 Specialized Career Paths - š Quizzes and Practice Activities - š Certificates for Courses & Career Paths - š Prizes for Learning - š§Ŗ Weekly Live Labs (plus recordings!) - šÆ Monthly Missions to practice even more - š¼ Monthly Career Booster Events - š¬ Full access to the SDS Community - ā” Monthly Speed Networking - š„ Monthly Resume Clinics - š„ Group Mentorship Program "In just a few months of learning at SDS, I landed a Data Analyst job!" ā Sanaz Afshar, California
$157
/ MonthAccelerate your Career and boost your Earning Potential with our Expert Instructors & Community! What Youāll Unlock: - š 40+ Courses (over 200 hours!) - š 17 Specialized Career Paths - š Quizzes and Practice Activities - š Certificates for Courses & Career Paths - š Prizes for Learning - š§Ŗ Weekly Live Labs (plus recordings!) - šÆ Monthly Missions to practice even more - š¼ Monthly Career Booster Events - š¬ Full access to the SDS Community - ā” Monthly Speed Networking - š„ Monthly Resume Clinics - š„ Group Mentorship Program Plus, Pro Plan perks just for you: - š A Personalized Career Path built around your goals - š§āš« 1-on-1 Mentoring Sessions every month - āļø Personalized Resume Reviews "In just a few months of learning at SDS, I landed a Data Analyst job!" ā Sanaz Afshar, California
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