Machine Learning 

 

Armenian-Indian Center for Excellence in ICT (AITC) and Enterprise Incubator Foundation (EIF) are happy to announce the start of a new training. 


The training will be delivered by Yevgeni Mamasakhlisov, associate professor of the Yerevan State University, who has about 5 years Java and C++ experience in mobile gaming and Web development and more than 25 years teaching and science experience in different areas, including complex systems modeling, programming etc.

 


Level 1


DESCRIPTION

This course is for programmers, who are interested in ML algoritms and their implementation using Java and Python programming languages,

including: supervised, unsupervised and reinforced learning concepts, neural networks implementation, deep learning, etc. The course is mainly focused on the neural network based algorithms.

 

 

KNOWLEDGE TO BE GAINED

 

Training key topics include:

 

  •    Brief intro to Java and Python syntax
  •      Introduction into the artificial and biological neural networks
  •      Perceptron learning algorithms
  •      Adaptive linear neurons and the convergence of learning
  •      Classification problem addressed with perceptron, logistic regression and singular value machines
  •      Dimensionality reduction with principal components and linear discriminant analysis
  •      Clustering problem addressed with k-means, hierarchical cluster analysis and self-organizing maps
  •      Deep learning algorithms, including deep Boltzmann machines and convolutional neural networks
  •      Preprocessing data
  •      Data visualization
  •      Machine learning frameworks, including Weka and scikit-learn

 

TRAINING DETAILS 

 

Duration: 48 hours 

Fee: AMD 96 000 (for the entire level) 


PRE-REQUISITES

Knowledge of Java or Python at the basic level.

 


Level 2

DESCRIPTION 

This course is for Java and Python programmers, who are interested in a deep understanding of the ML algoritms and their practical implementation for the real life problems. The course is mainly focused on the practical work with ML frameworks and libraries and on some theoretical basics of the Machine Learning.

 

 

KNOWLEDGE TO BE GAINED 

Training key topics include:

 

  •      Theoretical aspects of the Deep Learning
  •      Autoencoders
  •      Structured Probabilistic Models for Deep Learning
  •      Tensorflow
  •      Spark ML

TRAINING DETAILS 

 

Duration: 24 hours 

Fee: AMD 60 000 (for the entire level) 


PRE-REQUISITES

Knowledge of the main ML algorithms and techniques.

 

HOW TO APPLY?

As the number of participants is limited the selection will be made on "first come - first served" basis. The selected students will be notified additionally. For more information please call us at 010 /93 /99 55 68 10.