Machine Learning & Data Science
21 Week Course

As part of the grant projects announced by the Ministry of High-Tech Industry of the Republic of Armenia, Armenian Code Academy is organizing the "Machine Learning" course. There are available full and partial scholarships from the Ministry of HTI and our partner companies. Fifteen full scholarships are given from the company krisp.

Various fields

This course covers most of modern machine learning technologies and applications.


Due to the amount of material we have to cover, we are going to have 4 classes per week, lasting 2-4 hours. This means that it would be expremely hard to combine this course with full time work.

Invited tutors

We’ll have various invited tutors who are well known professionals in their fields of interest.


During educational process you will not only learn the theory of machine learning but also advanced engineering with Python.


After each workshop you will implement a real-life project in a group.


Successful graduates of this course will be hired by our partner companies.

Course Syllabus

    Part 1: Intro to Python

  • Python for newbies
  • Developer tools (Git, Docker, etc)
  • Part 2: Regression

  • Introduction
  • Data visualisation tools
  • Linear Regression
  • Feature Scaling
  • Ridge Regression
  • Cross-Validation
  • Regression Models for count data
  • Part 3: Classification

  • Logistic Regression
  • SVM
  • Soft and Hard Margin SVM
  • Part 4: Trees

  • Trees
  • Random Forests
  • Ensemble methods
  • Part 5: Unsupervised Clustering

  • Clustering; K-Means
  • Cluster evaluation methods
  • Gaussian Mixture Models
  • EM for Gaussian Mixture Models

    Part 6: Unsupervised Learning

  • Density Estimation – Kernel Density Estimation
  • Binning and KD-Trees for KDE
  • Dimensionality Reduction: PCA, SVD
  • Part 7: Neural Networks

  • Convolutional neural networks
  • NN Regularization
  • Optimization
  • NN debugging
  • Adversarial learning
  • Recurrent neural networks
  • Attention and memory
  • Part 8: NLP

  • Background and Glossary
  • Deep learning for NLP
  • Natural language understanding
  • NLP libraries and technologies
  • Part 9: Reinforcement Learning

  • Markov Decision Processes, dynamic programming
  • Model-free RL: from Monte Carlo to temporal difference methods
  • Policy gradient methods
  • RL with function approximation
  • Deep RL
  • FINAL Part: Group Project

Our Tutors

Anna Harutyunyan

Research Scientist
Google DeepMind

Vahan Huroyan

Postdoctoral Research Associate in ML and Data Science
University of Arizona

Irina Higgins

Senior Research Scientist
Google DeepMind

Gagik Amirkhanyan

Senior Machine Learning Engineer

Vahe Tshitoyan

Machine Learning software engineer

Shahane Arushanyan

Data Scientist
Philip Morris International

Mikael Arakelian

Software Engineer

frequently asked questions

What preliminary experience is needed?

Analytical thinking, knowledge of English, computer and mathematical knowledge, communication skills and ability to learn in a non-formal environment

Who can participate?

The program is open to citizens of the Republic of Armenia and the Republic of Artsakh (over 18 y.o. Yerevan applicants and over 16 y.o. applicants from regions and Republic of Artsakh), who will successfully undergo the admission procedure and will meet the objectives of the program.

What's the application procedure?

  • 1. Fill in the registration form (Applicant confirms his/her readiness to compensate the organizer for damages resulting from the transmission of false, incorrect and/or incomplete information about personal data)
  • 2. Take an online test. You can also take a mock-exam to test your knowledge
  • Applicants who pass the entrance threshold will be invited for an individual online interview.
  • NOTE: you can find all the links by following the "Enroll" button below.
  • What’s the format of classes?

    The intermediate-level "Machine Learning" course will be conducted in the following format:

  • - Three theoretical lessons per week, two hours each
  • - One four hour practical lesson
  • Intermediate practical classes will be held for up to 20 people in groups.
  • What will I get at the end of the course?

    • - Certificate of Excellence (in case of a final grade of 85% and more points),
    • - Graduation Certificate (in case of 50% - 85% of the final grade),
    • - Certificate of Participation (in case of less than 50% points of the final grade).
    • - CVs and graduation projects of excellent students will be referred to ACA partner companies, with letters of recommendation for top 10 students.

    How much is the course fee?

    • The courses are co-financed. The state will finance part of the course cost, which will depend on the results of the admission competition.
    • Based on the exam results and the interview, the course fee that should be paid by the course participant will be determined.
    • The cost of the four-month course is 600,000 AMD.
    • Our partner companies will give full scholarships to the best students who will be chosen after the exam and the interview.
    • Fifteen full scholarships are given from the company Krisp.


    Still have questions?

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