Advanced level

Machine Learning course (with Python)

• Live classes during evening hours
• 2 months, 2 times per week
• Up to 15 students per class
• Course materials and classes are in English
Apply now
Seize the modern day with our practical Machine Learning course that emphasizes supervised learning and neural networks.

This course is perfect for math and code lovers — or anyone passionate about cutting edge technology. By the end of it, you will be able to understand the fundamentals of machine learning, implement its algorithms from scratch using Python libraries, and build and train neural networks to solve real-world problems. Your final project is exactly that — a deployed machine learning model for a system or idea of your choice.

Admission requirements

Some programming experience, ideally in Python
but solid knowledge of the fundamentals in any programming language is enough. So if you’ve coded before, you’ve got this one down. Feeling unsure? Check out our Python development course and consider it first.
Being comfortable with high-school mathematics
as this course will contain derivatives, matrix and vector operations, etc. You don’t need to be a calculus expert, but to get the most out of this course, you should be able to follow along with the foundations. Revise some math materials online or dust off your high-school workbook — and you’ll be ready in no time.
Intermediate English and above.

The place of Machine Learning

Being the “brain” behind artificial intelligence (AI), machine learning enables computers to learn from data and make smart decisions without explicit instructions. Its adoption by businesses across all industries is ever increasing — and so is the need for Machine learning engineers.

According to the World Economic Forum, the demand for AI and Machine learning specialists is expected to grow by 40% from 2023 to 2027. On LinkedIn, there are currently over 100,000 Machine learning engineer vacancies worldwide, with the average salary for Juniors sitting at 68,000 EUR a year. 

Intrigued? Let’s take a look at your skill set after studying Machine Learning at Beetroot Academy.
Apply now

What will your CV look like?

Trainee / Junior Machine learning engineer
Professional skills:
• strong understanding of foundations of machine learning approaches and algorithms
• ability to work machine learning tools (NumPy, Pandas, SciKit Learn)
• understanding of machine learning techniques like Linear Regression, Decision Trees, SVM, kNN, Random Forest
• understanding of neural networks
• awareness of machine learning trends
• proficiency and deep understanding of algorithms in ML/DL
• practical experience of using deep learning frameworks in real projects (preferably TensorFlow (+Keras), PyTorch)
• knowledge of basic data structures and algorithms
• experience with image recognition (OpenCV, OCR or alternative) 
• experience with Natural Language processing (NumPy, Spacy)
• knowledge of Big Data frameworks (Spark, Hadoop, Kafka, ElasticSearch, etc) 


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Machine Learning Fundamentals
12 hours
6 topics
Classical Methods and Neural Networks
8 hours
4 topics
Deep Neural Networks
16 hours
8 topics
Bonus Module. Generative AI, Advanced Methods, and AI Ethics
6 hours
3 topics
Course author
Tomas Bengtsson
7+ years in IT
Software Developer у Skira
Worked for Volvo Group Trucks Technology in the department for vehicle automation
Experience in the field of self-driving vehicles, about the sensors that are responsible for detecting  pedestrians, vehicles of different types, and other objects of interest

Ph.D. in Chalmers University of Technology, Sweden
Course consultant
Igor Vustianiuk
6+ years in IT
Data Scientist/Python Developer at Beetroot

Our teachers

All teachers pass multiple interviews to ensure aligning values, as well as impeccable soft and technical skills. The final step is a demo class where they teach a topic to other teachers.

Our team of methodologists supports and trains them continuously. This is the place where industry experts become great teachers.

The learning process

We use the flipped classroom, which means you study theory on your own and practice it in class with the teacher’s guidance and classmates’ support.
30 hours+
Before every live class, you will get access to an expertly crafted set of theoretical resources (videos, external links, and terminology). In class, your teacher will explain anything you may have found difficult during preparation.
Live classes
36 hours
In live classes, you will have homework discussions with your teacher, complete practical assignments, and work on group and individual projects.
30 hours+
Our home assignments give you a way to apply your new skills. Your teacher will check it and provide you with feedback about its accuracy and room for improvement.
But there’s more!
Aside from providing industry-leading education, we ensure that you receive meaningful support from student success managers and peers.
Like-minded students
We strive to ensure alignment in our students’ determination and values. We find this to an absolutely essential for an optimal learning experience.
Student success managers
Every group has a dedicated manager who will make sure that your course goes as planned. Think of them as your new best friend who can answer any questions you may have.
Community access
After graduating, you’ll join our extended family and become part of the alumni network. You'll have access to news, events, job opportunities, and many other perks.

Career support

We'll assist you with writing your first CV, make sure you nail your interviews, and help you navigate the job market. Our goal is to get you started in the tech industry, not just pass a course.

Beetroot Academy in a nutshell

We provide far more than just industry-leading education. Beetroot Academy’s approach makes career switches smooth and seamless. Here’s how:

Flipped classroom

Study theory at home and focus on practice in live classes, where you’ll be guided by one of our expert teachers.

Live classes

Join our Zoom classes led by industry expert — up to 15 students per class, during evening hours.


Get the help you need to break into your new career. We provide our students with meaningful support and career guidance.

Soft skills

Go beyond the technical stuff. Our approach emulates a real tech working environment, where our students work in groups, guided by a team lead.


Landing a job in tech can be tough — but we’ll provide you with the tools and knowledge necessary to nail your first interview.

Global community

Get access to the Beetroot Ecosystem that comprises thousands of alumni, a big development company, and a wide network of partners.

Admission process

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Step 1
Leave your application
If the course sparks your interest, please leave us your contact details in the form below. We’ll get back to you soon.
Step 2
Test and online meeting
Complete the test assignment and help us assess your level of readiness to join our course. Then meet one of our educational advisors to ask your questions about the course and see if we’re a good fit.
Step 3
Only after you have your questions answered make the payment to secure your seat in the next group. You can pay for the full course to get a discount or pay in installments.
Apply now


Course fee

We are here to provide you the flexibility to help you start a new career. Pay in one transfer to get a discount or in four monthly instalments.
Monthly payment
4 monthly payments
for full payment
36 hours
Classes with the teacher
60+ hours
theoretical and homework
Electronic certificate with confirmation
Portfolio of work after the course


What exactly is machine learning?
Why is everybody buzzing about AI?
How does machine learning differ from traditional programming?
What are some career opportunities in machine learning?
What if I don’t know how to code or do advanced math operations?
What kind of project work is included in this course?
Do you guarantee employment after the courses?

Your tech career starts here

You’re clicks away from embarking on an exciting and life-changing path.
Apply now