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Langflow. Practical Course on Building AI Applications
An intensive hands-on course on Langflow — a low‑code platform for building AI applications.
Over 8 sessions, you will go from getting to know the interface to deploying a ready‑made AI solution into production.
Each session follows the “theory → demonstration → practice” principle, so you immediately apply your knowledge to real‑world tasks.
Over 8 sessions, you will go from getting to know the interface to deploying a ready‑made AI solution into production.
Each session follows the “theory → demonstration → practice” principle, so you immediately apply your knowledge to real‑world tasks.
8 online sessions of 1.5 hours each. Each class: theory block > demonstration in Langflow > practical assignment for participants.
8 classes
17,500 RUB*
Final project
Price for the full course with materials and access to the group chat.
17,500 RUB - for groups of 10 or more people
25,000 RUB - for groups of up to 10 people
17,500 RUB - for groups of 10 or more people
25,000 RUB - for groups of up to 10 people
The final meeting included a presentation of the project—a full-fledged AI solution built on the Langflow low-code platform.
online
Training takes place online on our own platform.
Who This Course Is For
Developers
Want to rapidly prototype AI solutions and focus on architecture rather than debugging boilerplate? Langflow will cut development time by 5‑10 times.
Data Analysts
You already work with SQL and Python but want to build AI pipelines visually to test hypotheses faster and put them into practice.
Product Managers and Technical Leads
You want to understand how modern RAG systems and AI agents work under the hood so you can set realistic tasks for your team and estimate timelines.
Anyone Already Working with LLMs
If you’ve tried the OpenAI API but want to speed up prototyping and move from “toy” examples to production‑grade solutions — this course is for you.
Prerequisites: Basic understanding of what LLMs, APIs, and Python are. Programming experience is not required.
What You Will Learn in the Course
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Get familiar with the Langflow interface and its key capabilities for visual pipeline construction. - Learn the architecture of Langflow — from data transfer between nodes to its internal execution logic.
- Explore real DUC use cases: processing B2B requests in logistics, building RAG for knowledge bases, and extracting data from documents.
- Understand the components that make up Langflow pipelines and how they interact.
- Understand what a RAG system is, its building blocks, and how to assemble one in Langflow without writing a single line of code.
How the Course Is Structured
8 online meetings of 1.5 hours each, every week.
Small groups — up to 20 people to give attention to each participant.
Small groups — up to 20 people to give attention to each participant.
Hands‑on practice during class and homework assignments to reinforce learning. Your mentor reviews everything.
A closed Telegram chat with instructors and participants — you can consult and ask questions 24/7.
Course Instructors
You learn from professionals who create industrial AI solutions every day and develop the DUC SmartSearch and DUC SmartBI platforms themselves.
- Alexander SuleykinFounder of DUC TechnologiesPhD, Associate Professor at NUST MISIS and HSE. 10+ years in Big Data and AI. Author of 32+ scientific papers
- Roman BabenkoHead of AI DevelopmentSystems Analyst and Data Analyst with 17+ years of experience. Has delivered projects with up to 95% response accuracy for major clients. Winner of GLOWBYTE AUTUMN HACK 2023 hackathon, author of scientific articles.
- Dmitry SirotinData EngineerPhD. 13+ years of experience. Expert in data warehouse construction, ETL processes, and query optimization in PostgreSQL and Greenplum. Author of several registered developments at ROSPATENT.
- Artemy KadikovPython DeveloperExpert and practitioner focused on creating AI agents and automation. Over two years of experience developing and creating AI agents.
- Valentina SorokinaPractical Lecturer in LLMLecturer with three years of experience at a leading university and IT specialist with three years of industry experience. Author of several scientific publications dedicated to AI research.
Александр активно популяризирует перспективы использования решений в области Big Data и цифровых экосистем для прогнозирования и принятия взвешенных управленческих решений.
Научные исследования
Публикации, индексируемые в WoS & Scopus, в т. ч. Q1:
Your Results After the Course
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Certificate of course completion -
A finished project for your portfolio— a working AI application you can show to employers or clients. -
Skills you can immediately apply at work— you’ll be able to implement RAG, agents, and monitoring starting tomorrow. -
Access to the DUC alumni community— communication with colleagues and experts, new contacts and opportunities.