Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2025]
- Descrição
- Currículo
- FAQ
- Revisões
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
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
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
-
11
Intro (what you will learn in this section) -
12
Installing Tableau Desktop and Tableau Public (FREE)
-
13
Challenge description + view data in file
-
14
Connecting Tableau to a Data file - CSV file
-
15
Navigating Tableau - Measures and Dimensions
-
16
Creating a calculated field
-
17
Adding colours
-
18
Adding labels and formatting
-
19
Exporting your worksheet
-
20
Section Recap
-
21
Tableau Basics
-
22
Intro (what you will learn in this section)
-
23
Get the Dataset + Project Overview
-
24
Connecting Tableau to an Excel File
-
25
How to visualise an AB test in Tableau?
Learn how to do an AB test in Tableau with accessible and comprehensive visualization
-
26
Working with Aliases
-
27
Adding a Reference Line
-
28
Looking for anomalies
-
29
Handy trick to validate your approach / data
-
30
Section Recap
-
31
Intro (what you will learn in this section)
-
32
Creating bins & Visualizing distributions
-
33
Creating a classification test for a numeric variable
-
34
Combining two charts and working with them in Tableau
-
35
Validating Tableau Data Mining with a Chi-Squared test
-
36
Chi-Squared test when there is more than 2 categories
-
37
Quick Note -
38
Visualising Balance and Estimated Salary distribution
-
39
Extra: Chi-Squared Test (Stats Tutorial)
-
40
Extra: Chi-Squared Test Part 2 (Stats Tutorial)
-
41
Section Recap
-
42
Part Completed
-
56
Intro (what you will learn in this section)
-
57
Get the dataset
-
58
Assumptions of Linear Regression
-
59
Dummy Variables
-
60
Dummy Variable Trap
-
61
Understanding the P-Value
-
62
Ways to build a model: BACKWARD, FORWARD, STEPWISE
-
63
Backward Elimination - Practice time
-
64
Using Adjusted R-squared to create Robust models
-
65
Interpreting coefficients of MLR
-
66
Section Recap
-
75
Intro (what you will learn in this section)
-
76
Get the dataset
-
77
What is geo-demographic segmenation?
-
78
Let's build the model - first iteration
-
79
Let's build the model - backward elimination: STEP-BY-STEP
-
80
Transforming independent variables
-
81
Creating derived variables
-
82
Checking for multicollinearity using VIF
-
83
Correlation Matrix and Multicollinearity Intuition
-
84
Model is Ready and Section Recap
