Գրանցվի՜ր դասընթացին
Թող տվյալներդ, և մեր մասնագետը շուտով կապ կհաստատի քեզ հետ
ADVANCED MACHINE LEARNING
The goal of the course is to provide in-depth knowledge of machine learning within 5 months.
ՈՒ՞Մ ՀԱՄԱՐ Է ԴԱՍԸՆԹԱՑԸ
Individuals aiming to specialize in the tech industry by learning one of the most popular professions.
Professionals aiming to transition into the tech industry and build a new career with in-demand skills.
Employees looking to learn new skills and boost their performance in their current roles for growth.
Machine learning is in high demand with significant growth prospects in the job market
With ML skills, you can work remotely, freelance, or in various other formats without restrictions
High Demand
Flexible Work Arrangements
Investment in the Future
Learning ML is an investment in your future, positioning you as a leading specialist in the field
Development of New Qualities
Learning ML helps develop research, problem-solving, analytical, and many other skills
Why Start learning machine learning?
5 months duration
Offline, online, hybrid
format
format
Where Do Our Students Work?
SLIDER FOR MOBILE VERSION
What Does the Course Package Include?
Individual Approach
Receive personalized consultations from your instructor during and after the course
Become part of the ML Community, gaining the opportunity to share ideas and questions with the community
Alumni Club
24/7 Coworking Space
ACA's doors are always open for you. You can work from here for free at any time
Final Project
With the help of the instructor, you'll develop a portfolio and present a comprehensive final project
Participate in workshops to develop soft skills, create a professional CV, and manage your LinkedIn profile effectively
Soft Skill-երի վորքշոփ
1-1 հանդիպումներ
Regular one-on-one meetings with the program manager to ensure the best outcomes
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Ինչպե՞ս ՄԱՍՆԱԿՑԵԼ դասընթացին
Register for the Course
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Participate in the Interview
Become an ACA Student
After filling in your details, you'll receive an email with information about the next steps and other course details.
You'll receive a test via email designed to assess your preliminary knowledge through logical tasks.
Complete the Test
After passing the test, an introductory interview is held with the instructor and coordinator.
After the interview phase, you'll officially become an ACA student and join the upcoming group.
OUR TUTORS
Hrachya Asatryan
ML Scientist at Intelinair
Hayk Aprikyan
ML Engineer at Magical Labs
Davit Khazaryan
Adjunct Lecturer at AUA
Vahan Huroyan
Machine Learning Researcher at YerevaNN
OUR TUTORS
Hrachya Asatryan
ML Scientist at Intelinair
Hayk Aprikyan
ML Engineer at Magical Labs
Davit Khazaryan
Adjunct Lecturer at AUA
Vahan Huroyan
Machine Learning Researcher at YerevaNN
WHAT YOU WILL LEARN
● Introduction to Machine Learning
● k-Nearest Neighbors (kNN), Cross Validation
● Linear Regression
● Polynomial Regression, Bias-Variance tradeoff, Linear Regression (statistical perspective)
● Regularization (Lasso, Ridge, Elastic Net)
● Classification: Linear Models for classification, Fisher’s linear discriminant
● Logistic Regression
● Linear Discriminant Analysis (LDA) Quadratic Discriminant Analysis, Naive Bayes
● Support Vector Machines (SVM) hard margin, soft margin
● Decision Trees: Classification and Regression
● Ensemble Methods: Bagging
● Random Forest
● Boosting
● Gradient Boosting
● Unsupervised Learning, clustering, k-means clustering, measuring clustering quality
● Spectral clustering
● Gaussian Mixture Models,
● Density Based Clustering (DBSCAN)
● Kernel Density Estimation (KDE)
● k-Nearest Neighbors (kNN), Cross Validation
● Linear Regression
● Polynomial Regression, Bias-Variance tradeoff, Linear Regression (statistical perspective)
● Regularization (Lasso, Ridge, Elastic Net)
● Classification: Linear Models for classification, Fisher’s linear discriminant
● Logistic Regression
● Linear Discriminant Analysis (LDA) Quadratic Discriminant Analysis, Naive Bayes
● Support Vector Machines (SVM) hard margin, soft margin
● Decision Trees: Classification and Regression
● Ensemble Methods: Bagging
● Random Forest
● Boosting
● Gradient Boosting
● Unsupervised Learning, clustering, k-means clustering, measuring clustering quality
● Spectral clustering
● Gaussian Mixture Models,
● Density Based Clustering (DBSCAN)
● Kernel Density Estimation (KDE)
● Dimensionality Reduction: PCA, LDA
● Multi-Dimensional Scaling (MDS)
● t-SNE (t-distributed stochastic neighbor embedding)
● Non-negative matrix factorization (NMF)
● Dense Networks, Activation Functions
● Feedforward and Backpropagation
● Optimizers - SGD, Rmsprop, Adam etc.
● Regularization in NN
● Batch and Layer Normalization
● Tensorflow/Keras
● Convolutional Neural Networks
● Popular CNNs
● Image Classification with CNN
● Object Detection with CNN
● Recurrent Neural Networks - LSTM, GRU
● Generative Adversarial Networks
● Language Modeling
● Attention mechanism, Transformers
● Metrics of recommendation systems
● Collaborative Filtering
● Matrix Factorization
● Sequence-aware recommender systems
● Factorization Machines
● Multi-Dimensional Scaling (MDS)
● t-SNE (t-distributed stochastic neighbor embedding)
● Non-negative matrix factorization (NMF)
● Dense Networks, Activation Functions
● Feedforward and Backpropagation
● Optimizers - SGD, Rmsprop, Adam etc.
● Regularization in NN
● Batch and Layer Normalization
● Tensorflow/Keras
● Convolutional Neural Networks
● Popular CNNs
● Image Classification with CNN
● Object Detection with CNN
● Recurrent Neural Networks - LSTM, GRU
● Generative Adversarial Networks
● Language Modeling
● Attention mechanism, Transformers
● Metrics of recommendation systems
● Collaborative Filtering
● Matrix Factorization
● Sequence-aware recommender systems
● Factorization Machines
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It's totally free
Frequently asked questions
If you have any other questions, we’ll be happy to answer them on any platform
Frequently asked questions
If you have any other questions, we’ll be happy to answer them on any platform
The course fee is 890.000 AMD
Yes, if you are unable to pay the full amount at once, you can choose an installment plan of up to 24 months.
Դասընթացը ամբողջությամբ հայերեն է, սակայն լիարժեք մասնակցության համար անհրաժեշտ է անգլերենի ընդհանուր իմացություն՝ ընթացիկ նյութերը, տերմինները և այլ հասկացություններ սովորելու համար։
The course fee is 890.000 AMD
Yes, if you are unable to pay the full amount at once, you can choose an installment plan of up to 24 months.
Դասընթացը ամբողջությամբ հայերեն է, սակայն լիարժեք մասնակցության համար անհրաժեշտ է անգլերենի ընդհանուր իմացություն՝ ընթացիկ նյութերը, տերմինները և այլ հասկացություններ սովորելու համար։
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