Нейро
Пишем про нейронки, полезные сервисы и IT-технологии. По рекламе: @oleginc Менеджер – @Spiral_Yuri РКН: clck.ru/3KHCuR
Show more📈 Analytical overview of Telegram channel Нейро
Channel Нейро (@neuro_code) in the Russian language segment is an active participant. Currently, the community unites 57 668 subscribers, ranking 2 315 in the Technologies & Applications category and 10 714 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 57 668 subscribers.
According to the latest data from 19 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -387 over the last 30 days and by -6 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 6.73%. Within the first 24 hours after publication, content typically collects 3.91% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 879 views. Within the first day, a publication typically gains 2 255 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 21.
- Thematic interests: Content is focused on key topics such as github, bluetooth, девайс, нейросеть, gemini.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Пишем про нейронки, полезные сервисы и IT-технологии.
По рекламе: @oleginc
Менеджер – @Spiral_Yuri
РКН: clck.ru/3KHCuR”
Thanks to the high frequency of updates (latest data received on 20 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
[SUBJECT]=Тема или навык для изучения [CURRENT_LEVEL]=Начальный уровень знаний (начальный/средний/продвинутый) [TIME_AVAILABLE]=Сколько часов в неделю готовы уделять обучению [LEARNING_STYLE]=Предпочтительный метод обучения (визуальный/слуховой/практический/чтение) [GOAL]=Конкретная цель обучения или целевой уровень навыкаСам промт:
[SUBJECT]=Topic or skill to learn [CURRENT_LEVEL]=Starting knowledge level (beginner/intermediate/advanced) [TIME_AVAILABLE]=Weekly hours available for learning [LEARNING_STYLE]=Preferred learning method (visual/auditory/hands-on/reading) [GOAL]=Specific learning objective or target skill level Step 1: Knowledge Assessment 1. Break down [SUBJECT] into core components 2. Evaluate complexity levels of each component 3. Map prerequisites and dependencies 4. Identify foundational concepts Output detailed skill tree and learning hierarchy ~ Step 2: Learning Path Design 1. Create progression milestones based on [CURRENT_LEVEL] 2. Structure topics in optimal learning sequence 3. Estimate time requirements per topic 4. Align with [TIME_AVAILABLE] constraints Output structured learning roadmap with timeframes ~ Step 3: Resource Curation 1. Identify learning materials matching [LEARNING_STYLE]: - Video courses - Books/articles - Interactive exercises - Practice projects 2. Rank resources by effectiveness 3. Create resource playlist Output comprehensive resource list with priority order ~ Step 4: Practice Framework 1. Design exercises for each topic 2. Create real-world application scenarios 3. Develop progress checkpoints 4. Structure review intervals Output practice plan with spaced repetition schedule ~ Step 5: Progress Tracking System 1. Define measurable progress indicators 2. Create assessment criteria 3. Design feedback loops 4. Establish milestone completion metrics Output progress tracking template and benchmarks ~ Step 6: Study Schedule Generation 1. Break down learning into daily/weekly tasks 2. Incorporate rest and review periods 3. Add checkpoint assessments 4. Balance theory and practice Output detailed study schedule aligned with [TIME_AVAILABLE] Отвечай на русском языке.
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