Mô tả

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by a Data Scientist and a Machine Learning expert so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

Over 900,000 students world-wide trust this course.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course can be completed by either doing either the Python tutorials, or R tutorials, or both - Python & R. Pick the programming language that you need for your career.

This course is fun and exciting, and at the same time, we dive deep into Machine Learning. It is structured the following way:

  • Part 1 - Data Preprocessing

  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression

  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

  • Part 4 - Clustering: K-Means, Hierarchical Clustering

  • Part 5 - Association Rule Learning: Apriori, Eclat

  • Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

  • Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP

  • Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks

  • Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA

  • Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Each section inside each part is independent. So you can either take the whole course from start to finish or you can jump right into any specific section and learn what you need for your career right now.

Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

Bạn sẽ học được gì

Master Machine Learning on Python & R

Have a great intuition of many Machine Learning models

Make accurate predictions

Make powerful analysis

Make robust Machine Learning models

Create strong added value to your business

Use Machine Learning for personal purpose

Handle specific topics like Reinforcement Learning, NLP and Deep Learning

Handle advanced techniques like Dimensionality Reduction

Know which Machine Learning model to choose for each type of problem

Build an army of powerful Machine Learning models and know how to combine them to solve any problem

Yêu cầu

  • Just some high school mathematics level.

Nội dung khoá học

46 sections

Welcome to the course! Here we will help you get started in the best conditions.

6 lectures
Welcome Challenge!
02:43
Machine Learning Demo - Get Excited!
04:45
Get all the Datasets, Codes and Slides here
00:09
How to use the ML A-Z folder & Google Colab
05:44
Installing R and R Studio (Mac, Linux & Windows)
05:21
EXTRA: Use ChatGPT to Boost your ML Skills
00:23

-------------------- Part 1: Data Preprocessing --------------------

4 lectures
Welcome to Part 1 - Data Preprocessing
00:22
The Machine Learning process
01:31
Splitting the data into a Training and Test set
02:02
Feature Scaling
06:27

Data Preprocessing in Python

24 lectures
Getting Started - Step 1
05:21
Getting Started - Step 2
05:21
Importing the Libraries
03:34
Importing the Dataset - Step 1
05:13
Importing the Dataset - Step 2
04:42
Importing the Dataset - Step 3
05:46
For Python learners, summary of Object-oriented programming: classes & objects
01:03
Coding Exercise 1: Importing and Preprocessing a Dataset for Machine Learning
1 question
Taking care of Missing Data - Step 1
05:56
Taking care of Missing Data - Step 2
05:58
Coding Exercise 2: Handling Missing Data in a Dataset for Machine Learning
1 question
Encoding Categorical Data - Step 1
04:24
Encoding Categorical Data - Step 2
05:54
Encoding Categorical Data - Step 3
04:39
Coding Exercise 3: Encoding Categorical Data for Machine Learning
1 question
Splitting the dataset into the Training set and Test set - Step 1
03:55
Splitting the dataset into the Training set and Test set - Step 2
05:59
Splitting the dataset into the Training set and Test set - Step 3
03:52
Coding Exercise 4: Dataset Splitting and Feature Scaling
1 question
Feature Scaling - Step 1
05:56
Feature Scaling - Step 2
04:45
Feature Scaling - Step 3
03:48
Feature Scaling - Step 4
05:59
Coding exercise 5: Feature scaling for Machine Learning
1 question

Data Preprocessing in R

11 lectures
Getting Started
01:35
Dataset Description
01:57
Importing the Dataset
02:44
Taking care of Missing Data
05:55
Encoding Categorical Data
05:56
Splitting the dataset into the Training set and Test set - Step 1
04:38
Splitting the dataset into the Training set and Test set - Step 2
04:54
Feature Scaling - Step 1
04:25
Feature Scaling - Step 2
04:49
Data Preprocessing Template
05:15
Data Preprocessing Quiz
5 questions

-------------------- Part 2: Regression --------------------

1 lectures
Welcome to Part 2 - Regression
00:21

Simple Linear Regression

17 lectures
Simple Linear Regression Intuition
02:22
Ordinary Least Squares
03:17
Simple Linear Regression in Python - Step 1a
05:49
Simple Linear Regression in Python - Step 1b
05:58
Simple Linear Regression in Python - Step 2a
03:53
Simple Linear Regression in Python - Step 2b
03:58
Simple Linear Regression in Python - Step 3
04:35
Simple Linear Regression in Python - Step 4a
05:49
Simple Linear Regression in Python - Step 4b
05:57
Simple Linear Regression in Python - Additional Lecture
00:30
Simple Linear Regression in R - Step 1
04:40
Simple Linear Regression in R - Step 2
05:58
Simple Linear Regression in R - Step 3
03:38
Simple Linear Regression in R - Step 4a
05:44
Simple Linear Regression in R - Step 4b
05:33
Simple Linear Regression in R - Step 4c
04:37
Simple Linear Regression Quiz
5 questions

Multiple Linear Regression

26 lectures
Dataset + Business Problem Description
03:44
Multiple Linear Regression Intuition
02:26
Assumptions of Linear Regression
04:23
Multiple Linear Regression Intuition - Step 3
07:21
Multiple Linear Regression Intuition - Step 4
02:10
Understanding the P-Value
11:44
Multiple Linear Regression Intuition - Step 5
15:41
Multiple Linear Regression in Python - Step 1a
05:54
Multiple Linear Regression in Python - Step 1b
02:35
Multiple Linear Regression in Python - Step 2a
04:28
Multiple Linear Regression in Python - Step 2b
04:43
Multiple Linear Regression in Python - Step 3a
05:52
Multiple Linear Regression in Python - Step 3b
04:32
Multiple Linear Regression in Python - Step 4a
05:38
Multiple Linear Regression in Python - Step 4b
05:34
Multiple Linear Regression in Python - Backward Elimination
01:35
Multiple Linear Regression in Python - EXTRA CONTENT
00:31
Multiple Linear Regression in R - Step 1a
03:53
Multiple Linear Regression in R - Step 1b
03:57
Multiple Linear Regression in R - Step 2a
05:22
Multiple Linear Regression in R - Step 2b
04:20
Multiple Linear Regression in R - Step 3
04:26
Multiple Linear Regression in R - Backward Elimination - HOMEWORK !
17:51
Multiple Linear Regression in R - Backward Elimination - Homework Solution
07:33
Multiple Linear Regression in R - Automatic Backward Elimination
00:15
Multiple Linear Regression Quiz
5 questions

Polynomial Regression

21 lectures
Polynomial Regression Intuition
05:08
Polynomial Regression in Python - Step 1a
04:36
Polynomial Regression in Python - Step 1b
05:55
Polynomial Regression in Python - Step 2a
05:55
Polynomial Regression in Python - Step 2b
05:43
Polynomial Regression in Python - Step 3a
05:57
Polynomial Regression in Python - Step 3b
05:38
Polynomial Regression in Python - Step 4a
03:59
Polynomial Regression in Python - Step 4b
03:59
Polynomial Regression in R - Step 1a
03:45
Polynomial Regression in R - Step 1b
03:39
Polynomial Regression in R - Step 2a
04:40
Polynomial Regression in R - Step 2b
04:55
Polynomial Regression in R - Step 3a
04:59
Polynomial Regression in R - Step 3b
05:31
Polynomial Regression in R - Step 3c
05:42
Polynomial Regression in R - Step 4a
03:58
Polynomial Regression in R - Step 4b
03:47
R Regression Template - Step 1
05:57
R Regression Template - Step 2
05:25
Polynomial Regression Quiz
5 questions

Support Vector Regression (SVR)

14 lectures
SVR Intuition (Updated!)
08:09
Heads-up on non-linear SVR
03:57
SVR in Python - Step 1a
05:46
SVR in Python - Step 1b
03:29
SVR in Python - Step 2a
05:34
SVR in Python - Step 2b
04:56
SVR in Python - Step 2c
03:31
SVR in Python - Step 3
05:57
SVR in Python - Step 4
03:46
SVR in Python - Step 5a
03:42
SVR in Python - Step 5b
03:40
SVR in R - Step 1
05:58
SVR in R - Step 2
04:58
SVR Quiz
5 questions

Decision Tree Regression

11 lectures
Decision Tree Regression Intuition
11:06
Decision Tree Regression in Python - Step 1a
04:40
Decision Tree Regression in Python - Step 1b
03:58
Decision Tree Regression in Python - Step 2
04:59
Decision Tree Regression in Python - Step 3
03:16
Decision Tree Regression in Python - Step 4
04:59
Decision Tree Regression in R - Step 1
04:55
Decision Tree Regression in R - Step 2
05:49
Decision Tree Regression in R - Step 3
04:55
Decision Tree Regression in R - Step 4
03:50
Decision Tree Regression Quiz
5 questions

Random Forest Regression

7 lectures
Random Forest Regression Intuition
06:44
Random Forest Regression in Python - Step 1
05:53
Random Forest Regression in Python - Step 2
05:55
Random Forest Regression in R - Step 1
05:51
Random Forest Regression in R - Step 2
05:58
Random Forest Regression in R - Step 3
05:26
Random Forest Regression Quiz
5 questions

Evaluating Regression Models Performance

3 lectures
R-Squared Intuition
04:35
Adjusted R-Squared Intuition
05:30
Evaluating Regression Models Performance Quiz
5 questions

Regression Model Selection in Python

8 lectures
Make sure you have this Model Selection folder ready
00:31
Preparation of the Regression Code Templates - Step 1
04:45
Preparation of the Regression Code Templates - Step 2
05:59
Preparation of the Regression Code Templates - Step 3
03:59
Preparation of the Regression Code Templates - Step 4
03:58
THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 1
04:47
THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 2
04:15
Conclusion of Part 2 - Regression
01:03

Regression Model Selection in R

3 lectures
Evaluating Regression Models Performance - Homework's Final Part
08:54
Interpreting Linear Regression Coefficients
09:16
Conclusion of Part 2 - Regression
01:03

-------------------- Part 3: Classification --------------------

2 lectures
Welcome to Part 3 - Classification
00:21
What is Classification?
02:30

Logistic Regression

30 lectures
Logistic Regression Intuition
04:55
Maximum Likelihood
03:50
Logistic Regression in Python - Step 1a
05:43
Logistic Regression in Python - Step 1b
03:59
Logistic Regression in Python - Step 2a
05:51
Logistic Regression in Python - Step 2b
05:57
Logistic Regression in Python - Step 3a
03:58
Logistic Regression in Python - Step 3b
03:30
Logistic Regression in Python - Step 4a
05:59
Logistic Regression in Python - Step 4b
01:49
Logistic Regression in Python - Step 5
05:59
Logistic Regression in Python - Step 6a
05:52
Logistic Regression in Python - Step 6b
03:33
Logistic Regression in Python - Step 7a
05:54
Logistic Regression in Python - Step 7b
03:44
Logistic Regression in Python - Step 7c
03:19
Logistic Regression in Python - Step 7 (Colour-blind friendly image)
00:12
Logistic Regression in R - Step 1
05:58
Logistic Regression in R - Step 2
02:58
Logistic Regression in R - Step 3
05:23
Logistic Regression in R - Step 4
02:48
Warning - Update
00:38
Logistic Regression in R - Step 5a
05:48
Logistic Regression in R - Step 5b
05:59
Logistic Regression in R - Step 5c
04:59
Logistic Regression in R - Step 5 (Colour-blind friendly image)
00:12
R Classification Template
05:22
Machine Learning Regression and Classification EXTRA
00:17
Logistic Regression Quiz
5 questions
EXTRA CONTENT: Logistic Regression Practical Case Study
00:16

K-Nearest Neighbors (K-NN)

8 lectures
K-Nearest Neighbor Intuition
04:52
K-NN in Python - Step 1
05:58
K-NN in Python - Step 2
05:51
K-NN in Python - Step 3
05:58
K-NN in R - Step 1
05:54
K-NN in R - Step 2
04:33
K-NN in R - Step 3
04:44
K-Nearest Neighbor Quiz
5 questions

Support Vector Machine (SVM)

7 lectures
SVM Intuition
09:49
SVM in Python - Step 1
05:58
SVM in Python - Step 2
05:53
SVM in Python - Step 3
02:39
SVM in R - Step 1
05:47
SVM in R - Step 2
05:27
SVM Quiz
5 questions

Kernel SVM

11 lectures
Kernel SVM Intuition
03:17
Mapping to a higher dimension
07:50
The Kernel Trick
12:20
Types of Kernel Functions
02:24
Non-Linear Kernel SVR (Advanced)
10:55
Kernel SVM in Python - Step 1
05:59
Kernel SVM in Python - Step 2
05:59
Kernel SVM in R - Step 1
05:42
Kernel SVM in R - Step 2
05:41
Kernel SVM in R - Step 3
04:58
Kernel SVM Quiz
5 questions

Naive Bayes

11 lectures
Bayes Theorem
20:25
Naive Bayes Intuition
14:03
Naive Bayes Intuition (Challenge Reveal)
06:04
Naive Bayes Intuition (Extras)
09:41
Naive Bayes in Python - Step 1
05:56
Naive Bayes in Python - Step 2
05:48
Naive Bayes in Python - Step 3
01:35
Naive Bayes in R - Step 1
04:53
Naive Bayes in R - Step 2
04:41
Naive Bayes in R - Step 3
03:29
Naive Bayes Quiz
5 questions

Decision Tree Classification

7 lectures
Decision Tree Classification Intuition
08:08
Decision Tree Classification in Python - Step 1
05:59
Decision Tree Classification in Python - Step 2
05:56
Decision Tree Classification in R - Step 1
05:55
Decision Tree Classification in R - Step 2
05:51
Decision Tree Classification in R - Step 3
05:42
Decision Tree Classification Quiz
5 questions

Random Forest Classification

7 lectures
Random Forest Classification Intuition
04:28
Random Forest Classification in Python - Step 1
05:56
Random Forest Classification in Python - Step 2
05:56
Random Forest Classification in R - Step 1
05:56
Random Forest Classification in R - Step 2
05:58
Random Forest Classification in R - Step 3
05:26
Random Forest Classification Quiz
5 questions

Classification Model Selection in Python

6 lectures
Make sure you have this Model Selection folder ready
00:33
Confusion Matrix & Accuracy Ratios
04:52
ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 1
05:51
ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 2
05:59
ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 3
05:52
ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 4
02:38

Evaluating Classification Models Performance

6 lectures
False Positives & False Negatives
07:57
Accuracy Paradox
02:12
CAP Curve
11:16
CAP Curve Analysis
06:19
Conclusion of Part 3 - Classification
02:09
Evaluating Classiification Model Performance Quiz
5 questions

-------------------- Part 4: Clustering --------------------

1 lectures
Welcome to Part 4 - Clustering
00:21

K-Means Clustering

18 lectures
What is Clustering? (Supervised vs Unsupervised Learning)
03:19
K-Means Clustering Intuition
02:37
The Elbow Method
03:59
K-Means++
04:48
K-Means Clustering in Python - Step 1a
04:59
K-Means Clustering in Python - Step 1b
02:58
K-Means Clustering in Python - Step 2a
04:55
K-Means Clustering in Python - Step 2b
05:25
K-Means Clustering in Python - Step 3a
05:59
K-Means Clustering in Python - Step 3b
05:57
K-Means Clustering in Python - Step 3c
03:58
K-Means Clustering in Python - Step 4
05:58
K-Means Clustering in Python - Step 5a
05:59
K-Means Clustering in Python - Step 5b
04:57
K-Means Clustering in Python - Step 5c
06:59
K-Means Clustering in R - Step 1
05:59
K-Means Clustering in R - Step 2
05:39
K-Means Clustering Quiz
5 questions

Hierarchical Clustering

16 lectures
Hierarchical Clustering Intuition
08:47
Hierarchical Clustering How Dendrograms Work
08:47
Hierarchical Clustering Using Dendrograms
11:21
Hierarchical Clustering in Python - Step 1
05:58
Hierarchical Clustering in Python - Step 2a
04:52
Hierarchical Clustering in Python - Step 2b
05:58
Hierarchical Clustering in Python - Step 2c
05:59
Hierarchical Clustering in Python - Step 3a
05:45
Hierarchical Clustering in Python - Step 3b
05:42
Hierarchical Clustering in R - Step 1
03:45
Hierarchical Clustering in R - Step 2
05:23
Hierarchical Clustering in R - Step 3
03:18
Hierarchical Clustering in R - Step 4
02:45
Hierarchical Clustering in R - Step 5
02:33
Hierarchical Clustering Quiz
5 questions
Conclusion of Part 4 - Clustering
00:12

-------------------- Part 5: Association Rule Learning --------------------

1 lectures
Welcome to Part 5 - Association Rule Learning
00:11

Apriori

9 lectures
Apriori Intuition
18:13
Apriori in Python - Step 1
08:46
Apriori in Python - Step 2
17:07
Apriori in Python - Step 3
12:48
Apriori in Python - Step 4
19:41
Apriori in R - Step 1
19:53
Apriori in R - Step 2
14:24
Apriori in R - Step 3
19:17
Apriori Quiz
5 questions

Eclat

4 lectures
Eclat Intuition
06:05
Eclat in Python
12:00
Eclat in R
10:09
Eclat Quiz
5 questions

-------------------- Part 6: Reinforcement Learning --------------------

1 lectures
Welcome to Part 6 - Reinforcement Learning
00:41

Upper Confidence Bound (UCB)

14 lectures
The Multi-Armed Bandit Problem
15:36
Upper Confidence Bound (UCB) Intuition
14:53
Upper Confidence Bound in Python - Step 1
12:42
Upper Confidence Bound in Python - Step 2
03:51
Upper Confidence Bound in Python - Step 3
07:16
Upper Confidence Bound in Python - Step 4
15:45
Upper Confidence Bound in Python - Step 5
06:12
Upper Confidence Bound in Python - Step 6
07:28
Upper Confidence Bound in Python - Step 7
08:09
Upper Confidence Bound in R - Step 1
13:39
Upper Confidence Bound in R - Step 2
15:58
Upper Confidence Bound in R - Step 3
17:37
Upper Confidence Bound in R - Step 4
03:18
Upper Confidence Bound Quiz
5 questions

Thompson Sampling

10 lectures
Thompson Sampling Intuition
19:12
Algorithm Comparison: UCB vs Thompson Sampling
08:12
Thompson Sampling in Python - Step 1
05:47
Thompson Sampling in Python - Step 2
12:19
Thompson Sampling in Python - Step 3
14:03
Thompson Sampling in Python - Step 4
07:45
Additional Resource for this Section
00:28
Thompson Sampling in R - Step 1
19:01
Thompson Sampling in R - Step 2
03:27
Thompson Sampling Quiz
5 questions

-------------------- Part 7: Natural Language Processing --------------------

26 lectures
Welcome to Part 7 - Natural Language Processing
01:05
NLP Intuition
03:02
Types of Natural Language Processing
04:11
Classical vs Deep Learning Models
11:22
Bag-Of-Words Model
17:05
Natural Language Processing in Python - Step 1
07:13
Natural Language Processing in Python - Step 2
06:45
Natural Language Processing in Python - Step 3
12:54
Natural Language Processing in Python - Step 4
11:00
Natural Language Processing in Python - Step 5
17:24
Natural Language Processing in Python - Step 6
09:52
Natural Language Processing in Python - EXTRA
00:23
Homework Challenge
00:43
Natural Language Processing in R - Step 1
16:35
Warning - Update
00:22
Natural Language Processing in R - Step 2
08:39
Natural Language Processing in R - Step 3
06:27
Natural Language Processing in R - Step 4
02:57
Natural Language Processing in R - Step 5
02:05
Natural Language Processing in R - Step 6
05:49
Natural Language Processing in R - Step 7
03:26
Natural Language Processing in R - Step 8
05:20
Natural Language Processing in R - Step 9
12:50
Natural Language Processing in R - Step 10
17:31
Homework Challenge
00:47
Natural Language Processing Quiz
5 questions

-------------------- Part 8: Deep Learning --------------------

3 lectures
Welcome to Part 8 - Deep Learning
00:23
What is Deep Learning?
12:34
Deep Learning Quiz
5 questions

Artificial Neural Networks

21 lectures
Plan of attack
02:51
The Neuron
16:24
The Activation Function
08:29
How do Neural Networks work?
12:47
How do Neural Networks learn?
12:58
Gradient Descent
10:12
Stochastic Gradient Descent
08:44
Backpropagation
05:21
Business Problem Description
04:59
ANN in Python - Step 1
10:21
ANN in Python - Step 2
18:36
ANN in Python - Step 3
14:28
ANN in Python - Step 4
11:58
ANN in Python - Step 5
16:25
ANN in R - Step 1
17:17
ANN in R - Step 2
06:30
ANN in R - Step 3
12:29
ANN in R - Step 4 (Last step)
14:07
Deep Learning Additional Content
00:24
EXTRA CONTENT: ANN Case Study
00:14
ANN QUIZ
5 questions

Convolutional Neural Networks

17 lectures
Plan of attack
03:31
What are convolutional neural networks?
15:49
Step 1 - Convolution Operation
16:38
Step 1(b) - ReLU Layer
06:41
Step 2 - Pooling
14:13
Step 3 - Flattening
01:52
Step 4 - Full Connection
19:24
Summary
04:19
Softmax & Cross-Entropy
18:20
CNN in Python - Step 1
11:35
CNN in Python - Step 2
17:46
CNN in Python - Step 3
17:56
CNN in Python - Step 4
07:21
CNN in Python - Step 5
14:55
CNN in Python - FINAL DEMO!
23:38
Deep Learning Additional Content #2
00:21
CNN Quiz
5 questions

-------------------- Part 9: Dimensionality Reduction --------------------

1 lectures
Welcome to Part 9 - Dimensionality Reduction
00:33

Principal Component Analysis (PCA)

7 lectures
Principal Component Analysis (PCA) Intuition
03:49
PCA in Python - Step 1
16:52
PCA in Python - Step 2
05:30
PCA in R - Step 1
12:08
PCA in R - Step 2
11:22
PCA in R - Step 3
13:42
PCA Quiz
5 questions

Linear Discriminant Analysis (LDA)

4 lectures
Linear Discriminant Analysis (LDA) Intuition
03:50
LDA in Python
14:52
LDA in R
19:59
LDA Quiz
5 questions

Kernel PCA

2 lectures
Kernel PCA in Python
11:03
Kernel PCA in R
20:30

-------------------- Part 10: Model Selection & Boosting --------------------

1 lectures
Welcome to Part 10 - Model Selection & Boosting
00:29

Model Selection

6 lectures
k-Fold Cross-Validation Intuition
08:57
Bias-Variance Tradeoff
04:47
k-Fold Cross Validation in Python
13:45
Grid Search in Python
21:56
k-Fold Cross Validation in R
19:29
Grid Search in R
13:59

XGBoost

3 lectures
XGBoost in Python
14:48
Model Selection and Boosting Additional Content
00:32
XGBoost in R
18:14

Annex: Logistic Regression (Long Explanation)

1 lectures
Logistic Regression Intuition
17:06

Congratulations!! Don't forget your Prize :)

2 lectures
Huge Congrats for completing the challenge!
01:31
Bonus: How To UNLOCK Top Salaries (Live Training)
00:44

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