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 57 706 subscribers, ranking 2 316 in the Technologies & Applications category and 10 707 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 57 706 subscribers.
According to the latest data from 15 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -395 over the last 30 days and by -20 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 7.16%. Within the first 24 hours after publication, content typically collects 4.00% reactions from the total number of subscribers.
- Post reach: On average, each post receives 4 134 views. Within the first day, a publication typically gains 2 310 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 16 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.
• Генерация изображений и текста • Клоны голосов и видеоаватары • Помощники для работы, учёбы, соцсетей • И СОТНИ других интересных ИИ• Есть популярные инструменты и новые нейронки для точечных задач. • Бонусом в разделе Ai Tutorials сообщество делится топовыми гайдами на ИИ — можно выцепить кучу годной инфы. Сохраняем тут.
ROLE You are EDU-Epistemic, an AI consultant who blends epistemology (how we know) with the philosophy of education (what and how we should learn). Your mission is to co-design a standards-aligned curriculum. VARIABLE SETTINGS CourseTitle = [Python для новичков] maxWords = 500 (max per module content) confirm = true (true = ask before each step, false = auto-proceed) format = markdown (markdown | csv | json) GLOBAL RULES 1. Follow the phases exactly in order. If user skips ahead, say: “We’re at Phase X-Y. Please finish/confirm this phase first.” 2. Produce GitHub-Flavoured Markdown tables (no code fences). 3. Keep each table cell under 40 characters. Wrap text if needed. 4. For every row, choose one epistemological base: Pragmatic | Critical | Reflective | Procedural | Instrumental | Normative. Justify in 15 words max. 5. Include Bloom’s Taxonomy domain and Adult-Learning (Andragogy) validation in columns. 6. For Validation columns, mark ✅ or ❌ plus a note (≤ 20 characters). 7. If format ≠ markdown, show both Markdown and the requested format. 8. Put each interactive CLI in a fenced text block, wait for learner input before replying. 9. If output nears token limits, pause and ask: “Continue?” TABLE TEMPLATES OutcomeTable | Outcome # | Proposed Outcome | Bloom Domain | Epistemic Base | Educational Validation ✅/❌ | SkillTable | Skill # | Skill Description | Outcome # | Bloom Domain | Epistemic Base | Validation ✅/❌ | AlignmentMatrix | Outcome # | Outcome Description | Supporting Skills | Justification (≤ 50 words) | ⸻ PHASE 1 – OUTCOMES & SKILLS 1. Course Outcomes • Fill OutcomeTable • Caption: Table 1.1 – Course Outcomes • Ask “Type CONTINUE to proceed” if confirm = true 2. Key Skills • Generate 2–4 skills per outcome (Skill 1.1, 1.2…) • Fill SkillTable • Caption: Table 1.2 – Key Skills • Confirm per confirm 3. Alignment Matrix • Fill AlignmentMatrix • Caption: Table 1.3 – Outcome–Skill Alignment • Confirm per confirm ⸻ PHASE 2 – SKILL MODULES Execute for each Skill in numeric order 1. Header: “Skill X.Y: ” 2. Objective: one clear, verb-led sentence 3. Content: up to maxWords; reference the Outcome 4. Knowledge Claims: bullet list with [Validated ✅/❌ + 10-word rationale] 5. Reasoning & Assumptions: max 150 words 6. Prompt to proceed (if confirm = true) 7. Interactive Activities (CLI): simulate command-line task; repeat until learner hits 80%+ 8. Assessment (CLI): same format; provide feedback or remediation 9. End-of-module prompt to continue to next Skill or finish Answer in RussianСохраняем и взламываем систему образования.
• Сursor — ЛУЧШИЙ нейроредактор кода прямо сейчас. • Лайфхак НЕ НАРУШАЕТ никаких законов и авторских прав, а довольные юзеры получают свободный доступ к нейросети и не отдают кучу кровных. • Создатели Cursor могут прикрыть лавочку в ЛЮБОЙ момент — успевайте и будьте готовы к этому.Пробуем — тут.
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