Introduction to Machine Learning

About the Course

Introduction to Machine Learning Training will take place for 10 hours in total with 2-hour programs for 5 days!

We created the content of the education by using the sources of the world’s leading universities Stanford, Caltech, MIT and Harvard!

We will explore supervised and unsupervised learning in our 10-hour journey, where we will start with the topics of linear algebra and probability. As we learn how algorithms work, we will implement them using Python.

Our education is certified.

“Artificial intelligence is a bridge between art and science.”
Pamela McCorduck

If you also want to have a say in this vast world, sign up for our training at the link on our profile and take your first step to build the future!

What will you get?

All lectures at the Global AI Hub are given by expert instructors in the relevant field. Our educational materials have been prepared using the resources of the world’s leading universities. During the training, our mentors will be with you and answer your questions from the relevant Hub. Through our community, you can quickly find answers for your questions, meet people in your class and speed up your learning process.

With the quizzes to be held at the end of each lesson, you can reinforce what you have learned and become a Top Learner with your success. All participants test their learning with carefully prepared homework and quizzes, measure their success and prepare in advance for the problems they may encounter in the real world. After completing the course, participants take the opportunity to participate in projects and competitions through the AI Community. By demonstrating outstanding success in these activities, participants can take advantage of the many job opportunities we offer.


  • Good knowledge about Python
  • Experience with Pandas, NumPy, Matplotlib libraries
  • Basic knowledge about Probability & Statistic
  • Basic knowledge about Data Visualization


Introduction to ML
  • What is Big Data?
  • What is ML?
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
Linear Algebra Review
  • Matrices and Vectors
  • Addition and Scalar Multiplication
  • Matrix-Vector Multiplication
  • Matrix-Matrix Multiplication
  • Matrix Multiplication Properties
  • Inverse and Transpose
Probability Review
  • Random Variables
  • Probability Distributions
  • Marginal & Conditional Prob.
  • Independence
  • Expectation, Variance, Covariance
  • Bayes’ Rule
Data Preparation
  • Steps of Machine Learning Project
  • Data Gathering
  • Exploratory Data Analysis (EDA)
  • Pre-processing
  • Train / Validation / Test Split
Linear Regression
  • Linear Regression with a Single Feature
  • Linear Regression with Multiple Variables
  • Error Function
  • Gradient Descent
  • Cross validation
Logistic Regression
  • Hypothesis Representation
  • Decision Boundary
  • Sigmoid Function
  • Cost Function
  • Gradient Descent
  • Optimization
  • Multiclass Classification
  • Overfitting and Underfitting
  • Regularized Linear Regression
  • Regularized Logistic Regression
Decision Tree
  • Choosing an attribute
  • Using Information Theory
  • Information Gain
  • Gain-Ratio
  • Pruning
  • Regression Trees
  • Random Forest
Unsupervised Learning
  • Clustering
  • K-means
  • Dimensionality Reduction
  • Challenges with High-dimensional Data
  • Feature Reduction


Course Information

Course Type: Instructor-Led Training

  Skill Level: Introduction

  Students Enrolled: 1.690

  Languages: English

  Total Duration: 10 hours

  Certification: Yes


Yes, you have to upload your profile photo to join Hubs.

No, every training is a part of the Top Learner program. You can access the Top Learner program page here.

The attendance form will only be active during the actual training. Please fill in the attendance form within this period.

In order to get a certificate at the end of the training, it is compulsory to attend at least 3 days.

3 days after you have completed the training, you should receive your certificate. Be sure to check your mailbox and also your spam folder in case you don’t see it.

In order to be eligible for certification, you must attend the trainings for at least 3 days. If you have completed the attendance form for at least 3 days, check your mail box frequently, including spam.

Quizzes are held at the end of each class and they are only 15 minutes long. You must fill in the quiz before the expiry date.

No, there will be no make-up quizzes.

Since our training is certified, it is only possible to watch training recordings during the training.

You can download and install Anaconda on your computer using following link:  

It will be shared in a relevant Hub.

It will be shared in the Global AI Hub Github account and relevant hub at the end of the course.

Each participant needs to open a GitHub repository with their own account. At the end of the course, we will share a form to obtain your repository link which includes your works.

You should submit your homeworks and project  within 3 days after the course ends.

To get a certificate, you must attend the course at least 3 days and fill the attendance form. Homeworks, quizzes and final project are not required for certification.