Why Take This Course?
In our Introduction to Machine Learning training, mathematical operations with matrices are discussed after the introduction of Big Data, Supervised and Unsupervised Learning using the Python programming language throughout the course. Later, Probability, Data Preparation, Linear Regression, Logistic Regression, Regularization, Decision Tree, and Unsupervised Learning are discussed in detail. We’ve also created great material to support your learning process using the world’s leading resources.
Finally, we support your development process by giving you homework so that you can not only force yourself to practice but also leave the described topics in theory. In this way, you can expand yourself and your portfolio like GitHub by gathering experience in both theory and practice.
This course is for everyone who wants to take the first step to the Artificial Intelligence and Data Science world by learning the fundamentals of Machine Learning.
You are invited to join our Machine Learning forum and use this space to discuss topics related to the course, share interesting and relevant material and links, ask questions and engage with peers.
All Our Programs Include
- A joint certificate issued by Global AI Hub for each successful learner
- Good knowledge about Python Experience with Pandas, NumPy, Matplotlib libraries
- Basic knowledge about Probability & Statistic
- Basic knowledge about Data Visualization
Normally the price of this course is 240 EUR per learner. However, this course is currently part of the “10million.AI” project and its various national education campaigns aiming at educating more than 10 million learners for free on AI and other digital technologies.
Thanks to the Swiss-based AI Business School and many other global and national supporters of this non-profit initiative, for you this course is free of any charges.
Part of the following learning paths
- Day 1:
- Probability Review
- Linear Algebra Review
- Day 2:
- Data Preparation
- Linear Regression
- Day 3:
- Logistic Regression
- Day 4:
- Decision Trees
- Day 5:
- Unsupervised Learning
The course includes a series of lessons that lead you through the content in small, bite-sized learning blocks. Each lesson includes exciting video sessions followed by thought-provoking assessment questions.
- Video sessions have to be marked as complete and can be accessed freely after the completion of each lesson.
- Assessment questions are graded for the calculation of certification progress.
- Each day has a “Materials” section to help you revise the topics that are seen that day.
Are you ready to dive into the fascinating world of AI by taking the first step with Python? Click on the first lesson and dive right in!