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Coding Courses

Coding Courses

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📈 Analytical overview of Telegram channel Coding Courses

Channel Coding Courses (@coding_learning1) in the English language segment is an active participant. Currently, the community unites 17 923 subscribers, ranking 11 216 in the Education category and 23 737 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 923 subscribers.

According to the latest data from 01 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -143 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 12.26%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 0 views. Within the first day, a publication typically gains 0 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as javascript, array, html, learning, recognition.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
🔴Declaimer🔴 We do not hold this content or stored in our drive, we just redirect telegram or website link where this content is already shared

Thanks to the high frequency of updates (latest data received on 02 July, 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 Education category.

17 923
Subscribers
-724 hours
-537 days
-14330 days

Data loading in progress...

Attracting Subscribers
July '26
July '260
in 0 channels
June '26
+12
in 0 channels
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May '26
+3
in 0 channels
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April '26
+9
in 0 channels
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March '26
+75
in 0 channels
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February '26
+122
in 0 channels
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January '26
+176
in 0 channels
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December '25
+256
in 1 channels
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November '25
+389
in 0 channels
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October '25
+408
in 1 channels
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September '25
+258
in 0 channels
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August '25
+44
in 0 channels
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July '25
+5
in 0 channels
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June '25
+12
in 0 channels
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May '25
+26
in 0 channels
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April '25
+21
in 0 channels
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March '25
+24
in 1 channels
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February '25
+15
in 2 channels
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January '25
+313
in 1 channels
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December '24
+253
in 1 channels
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November '24
+1 010
in 0 channels
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October '24
+927
in 0 channels
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September '24
+1 604
in 0 channels
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August '24
+4 129
in 1 channels
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July '24
+1 723
in 0 channels
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June '24
+1 786
in 0 channels
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May '24
+1 758
in 0 channels
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April '24
+1 800
in 2 channels
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March '24
+2 085
in 0 channels
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February '24
+2 075
in 1 channels
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January '24
+746
in 0 channels
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December '23
+854
in 0 channels
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November '23
+33
in 0 channels
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October '23
+101
in 1 channels
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September '23
+172
in 0 channels
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August '230
in 0 channels
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July '230
in 0 channels
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June '230
in 0 channels
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May '230
in 0 channels
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April '230
in 0 channels
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March '230
in 0 channels
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February '230
in 0 channels
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January '230
in 0 channels
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December '220
in 0 channels
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November '220
in 0 channels
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October '220
in 0 channels
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September '220
in 0 channels
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August '22
+17
in 0 channels
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July '22
+16
in 0 channels
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June '22
+26
in 0 channels
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May '22
+14
in 0 channels
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April '22
+12
in 0 channels
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March '22
+11
in 0 channels
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February '22
+64
in 0 channels
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January '22
+179
in 0 channels
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December '21
+479
in 0 channels
Date
Subscriber Growth
Mentions
Channels
01 July0
Channel Posts
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*🚀 Complete Roadmap to learn AI Fundamentals* AI isn't just about using basic tools. To build real-world AI applications, you need to understand the fundamentals first and then learn the right tools. Here's a complete roadmap: *🎯 Phase 1: AI Fundamentals* ✅ What is Artificial Intelligence? ✅ Types of AI ANI, AGI, ASI ✅ Machine Learning vs Deep Learning vs Generative AI ✅ Supervised, Unsupervised & Reinforcement Learning ✅ Neural Networks Basics ✅ Large Language Models LLMs ✅ Tokens & Context Windows ✅ Embeddings ✅ Vector Databases ✅ Prompt Engineering ✅ RAG Retrieval-Augmented Generation ✅ AI Agents ✅ Fine-Tuning ✅ AI Safety & Responsible AI *🎯 Phase 2: Essential Programming Skills* ✅ Python ✅ SQL ✅ Git & GitHub ✅ REST APIs ✅ JSON ✅ FastAPI *🎯 Phase 3: Core AI Libraries* ✅ NumPy ✅ Pandas ✅ Scikit-learn ✅ PyTorch ✅ Transformers *🎯 Phase 4: Generative AI Tools* ✅ OpenAI API ✅ Hugging Face ✅ Ollama ✅ LangChain ✅ LangGraph ✅ LlamaIndex ✅ CrewAI ✅ AutoGen *🎯 Phase 5: Vector Databases* ✅ ChromaDB ✅ Pinecone ✅ Weaviate ✅ FAISS *🎯 Phase 6: AI App Development* ✅ Streamlit ✅ Gradio ✅ FastAPI ✅ Docker ✅ Redis ✅ PostgreSQL *🎯 Phase 7: AI Automation Tools* ✅ n8n ✅ Flowise ✅ Dify ✅ Make ✅ Zapier *🎯 Phase 8: Deployment & MLOps* ✅ Docker ✅ GitHub Actions ✅ MLflow ✅ Weights & Biases ✅ AWS / Azure / Google Cloud *🎯 Phase 9: Build Real Projects* ✅ AI Chatbot ✅ PDF Chat with RAG ✅ AI Coding Assistant ✅ Customer Support Bot ✅ Resume Analyzer ✅ Research Assistant ✅ Multi-Agent AI System ✅ Enterprise Knowledge Assistant
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