"Integration of AI solutions in production" course
40 recorded sessions / certificate
starts June 22 / price - 39.900 rubles


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By clicking the button, I consent to the processing of personal data and agree to the privacy policy and the offer agreement.
"Integration of AI solutions in production" course
40 recorded sessions / certificate
starts June 22 / price - 39.900 rubles


Apply for course
By clicking the button, I consent to the processing of personal data and agree to the privacy policy and the offer agreement.
Course Objectives
Learn to integrate solutions based on neural networks and machine learning into production systems of any complexity
  • 1
    Master modern methods and frameworks for working with pre-trained neural networks.
    If you already use frameworks and modern components to work with neural networks, the course will help to expand your horizons in this area.
  • 2
    Gain skills in Full Stack ML development.
    If you have not previously worked with specialized neural network frameworks, you can quickly and deeply explore this area and start using them in the middle of your course.
  • 3
    Examine the main components of data processing and preparation (Data Engendering).
    The methods of data processing and Data Engendering will be useful not only for neural networks, but also will help to transfer data between different systems efficiently and reliably, to set up and manage data loading and processing.
  • 4
    Learn to quickly integrate a trained neural network into a wide range of industrial systems.
    The knowledge gained can be used not only for the integration of neural networks and various industrial systems, but also for the integration of the two systems with each other or for the integration of industrial systems and Python-programs.
  • 5
    Learn to set tasks for the development team (including those who are not familiar with neutron networks) to transfer the trained models to production.
    You will learn to speak the language of the developers
  • 6
    Learn to "pack" the trained neural network in a format convenient for the end user (Web-services, mobile applications, IoT devices, etc.).
    In today's world, startups consisting of 2-3 programmers are able to present a commercially ready product; upon completion of the course you will be able to perform tasks of a small team of developers.
The aim of the course is to give participants skills in Full Stack ML development. Upon completion of the course, participants will be able to create complex Pipeline data processing, independently deploy Data engeneering components, set tasks for the development team (to transfer the model to production), independently prepare the model for output to production (deploy all necessary components and package the model in a format suitable for transfer).
The course is designed for participants who are familiar with the basic concepts of neural networks, but have difficulties with the practical application of a neural network in real systems/tasks, and aims to give practical knowledge, as the already trained neural network can be applied in real tasks from A to Z (excluding the nuances related directly to the training of the neural network).Курс рассчитан на участников, знакомых с базовыми понятиями нейронных сетей, но имеющих трудности с практическим применением нейронной сети в реальных системах/задачах, и нацелен на то, чтобы дать практические знания, как уже обученную нейронную сеть можно применить в реальных задачах от А до Я (исключая нюансы, связанные непосредственно с обучением нейронной сети).
The course covers all steps: how and where to take data for an already trained neural network, how to properly feed it into the network, how to extract the results of predictions, how to give these results to different systems, how to make the neural network available online (in the cloud) and much more.
Training Format
  • 40 recorded sessions
    You will have 40 webinar records available for viewing at any time
  • 40 practical tasks
    After each lesson you will get a practical task
  • 9 months of curator support
    During the week, you will be able to ask any questions about how to perform tasks to your tutor in the common chat
What are you going to learn from the course
Web-crawling
(parsing and uploading data from sites, analyzing APIs)
Methods of data storage and presentation in relational and non-relational databases (DBs)
Relational data storage units
Postgres / Redshift / Oracle
MPP storages
(Teradata, SAP HANA)
Storages of unstructured data
(Hadoop, AWS S3)
Key-Value data warehouses
(Hbase, MongoDB)
In-Memory systems
Apache Solr, GPU-based databases
Real-Time data delivery systems
Apache Kafka, Spark Streaming
The most powerful tool for handling large amounts of data
Apache Spark
One of the most advanced frameworks for working with trained models
TensorFLow - Tensor Flow Extended
Containerization of applications in Docker/Kubernetis
Powerful AWS (Amazon Web Services) based development toolbox
API Gateway/AWS Lambda/AWS Fargate
Course teacher and methodologist
Gerard Kostin
31 y.o., Innsbruck, Austria
Extensive experience in solving problems using ML methods in the following areas: telecommunications, banking sector, Internet providers, industrial enterprises, e-commerce.
Practical experience of work with big data (clusters from 5 Pb). During his career in the field of Data Science he launched these areas from scratch in companies such as MTS and Rostelecom, worked together with companies from the U.S. silicon valley and EU companies.
Training program
Part #1. Theory
19 1-hour lectures
Data, their types and source systems
(5 sessions)
Data model (5 sessions)
ETL/ELT (5 sessions)
Transferring the model between languages (4 sessions)
Part #2. Data sources
7 30-minute sessions
Part #3. Practice
14 sessions of 30 minutes - 2 hours
Integration into production (14 sessions).

Sessions in this part are 100% practical, we will install, customize and combine various components to bring models and machine learning solutions into production. In the lessons there will be a minimum of theory, we will solve real cases from practice, there will be a lot of work by hand, we will write code. During the process, the teacher will share with you the most valuable practical experience and advice.
Apply for course
"Basic" plan

39.900 rubles
  • 40 recorded sessions
  • 40 practical tasks
  • 9 months of curator support
  • Certificate
Pay 39.900 rubles.
Our manager will answer any questions about the course
  • Artem Voronov-Gashev
    Customer service manager
    Email: info@neural-university.ru
    Phone: +7 (499) 648-67-44
    Whatsapp/viber/telegram:
    +7(918) 916-41-84
"Integration of AI solutions in production" course
40 recorded sessions / certificate
starts June 22 / price - 39.900 rubles


Apply for course
By clicking the button, I consent to the processing of personal data and agree to the privacy policy and the offer agreement.
"Integration of AI solutions in production" course
40 recorded sessions / certificate
starts June 22 / price - 39.900 rubles

Apply for course
By clicking the button, I consent to the processing of personal data and agree to the privacy policy and the offer agreement.