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The Learning Cycle 🌱

The Learning Cycle 🌱

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At The Learning Cycle, we champion collective learning & growth, dedicating our community to sharing resources and opportunities that empower individuals on their learning journeys. Buy ads: https://telega.io/c/learningcycle

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📈 نظرة تحليلية على قناة تيليجرام The Learning Cycle 🌱

تُعد قناة The Learning Cycle 🌱 (@learningcycle) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 29 796 مشتركاً، محتلاً المرتبة 6 533 في فئة التعليم والمرتبة 1 367 في منطقة الولايات المتحدة.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 29 796 مشتركاً.

بحسب آخر البيانات بتاريخ 20 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 562، وفي آخر 24 ساعة بمقدار -26، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 10.55‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 3.17‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 3 143 مشاهدة. وخلال اليوم الأول يجمع عادةً 944 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 6.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل reader, edit, archive, ebook, anna.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
At The Learning Cycle, we champion collective learning & growth, dedicating our community to sharing resources and opportunities that empower individuals on their learning journeys. Buy ads: https://telega.io/c/learningcycle

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 21 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

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-257 أيام
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أرشيف المشاركات
🟨 Funded Ph.D. Research Assistant Positions 📚 #Construction_Engineering 📚 #Civil_Engineering 📚 #Computer_Science 🏫 University: Arizona State University 🌎 Country: USA 🇺🇸 🎓 Supervisor: Dr. Siyuan Song ✅ Candidates with a background in Construction Engineering, Civil Engineering, Computer Science, or other relevant fields are preferred. Self-motivated, independent, responsible, and enthusiastic individuals with strong English writing and speaking skills are encouraged to apply. Publication records or research experience are a plus. 📌 How to apply: Please email Dr. Siyuan Song (siyuan.song.1@asu.edu) with the following materials: CV/Resume Transcripts Names and contact information of 3-5 references TOEFL, GRE scores (if any) Sample work (if any), e.g., publications, thesis, etc. 📅 Application deadline: The review of applicants will begin immediately and continue until the positions are filled. Please feel free to contact Dr. Song for more information. _____ Copied

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Think_Straight.pdf10.12 KB

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1. Google Data Analytics: https://www.coursera.org/professional-certificates/google-data-analytics 2. Learn Python Basics for Data Analysis: https://www.coursera.org/learn/python-crash-course 3. Data Analysis with R Programming: https://www.coursera.org/learn/data-analysis-r 4. Foundations: Data, Data, Everywhere: https://www.coursera.org/learn/foundations-data 5. Ask Questions to Make Data-Driven Decisions: https://www.coursera.org/learn/ask-questions-make-decisions 6. Process Data from Dirty to Clean: https://www.coursera.org/learn/process-data 7. Share Data Through the Art of Visualization: https://www.coursera.org/learn/visualize-data 8. Analyze Data to Answer Questions: https://www.coursera.org/learn/analyze-data 9. Get Started with Python: https://www.coursera.org/learn/python 10. Go Beyond the Numbers: Translate Data into Insights: https://www.coursera.org/learn/go-beyond-the-numbers-translate-data-into-insight 11. The Power of Statistics: https://www.coursera.org/learn/the-power-of-statistics 12. Regression Analysis: https://www.coursera.org/learn/regression-analysis-simplify-complex-data-relationships 13. The Nuts and Bolts of Machine Learning: https://www.coursera.org/learn/the-nuts-and-bolts-of-machine-learning 14. Google Advanced Data Analytics Capstone: https://www.coursera.org/learn/google-advanced-data-analytics-capstone

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LeetCode: An Indispensable Resource for Preparing Improving your Coding Skills and Preparing for Technical Interviews LeetCode can be a valuable resource for improving coding skills and preparing for technical interviews. It offers a wide range of coding problems from various domains and difficulty levels, allowing users to practice problem-solving and algorithmic thinking. Many companies, especially in the tech industry, use similar coding challenges during their interview processes. Link: https://leetcode.com/discuss/general-discussion/460599/blind-75-leetcode-questionsBy regularly solving problems on LeetCode, you can enhance your problem-solving abilities, gain familiarity with common algorithms and data structures, and improve your coding efficiency. Additionally, LeetCode provides solutions and discussions for each problem, allowing you to learn from different approaches and gain insights from the community. However, it's important to note that LeetCode is just one of many resources available for improving coding skills. It's beneficial to supplement your learning with other resources like textbooks, online courses, and real-world projects to gain a well-rounded understanding of programming concepts. Ultimately, the worth of LeetCode depends on your specific goals and learning style. If you are preparing for technical interviews or seeking to enhance your coding skills, LeetCode can be a valuable tool in your learning journey. #chatgpt

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Python for Bioinformatics Projects and Drug Discovery: https://morioh.com/p/7fe85ed008f3?f=5c224490c513a556c9042463 Modern Genetics & Biotechnology: https://t.me/allomics BIOINFORMATICS open Access Online Resources carefully collected over Many years 1. https://pubmed.ncbi.nlm.nih.gov/?term=Bioinformatics&sort= 2. http://bio-protocol.org/Default.aspx 3. https://www.vlab.co.in/broad-area-biotechnology-and-biomedical-engineering 4. http://rosalind.info/glossary/ 5. http://ghr.nlm.nih.gov/glossary 6. http://rosalind.info/courses/ 7. http://nptel.ac.in/courses/117106113/ 8. https://www.vlab.co.in/broad-area-computer-science-and-engineering 9. https://www.codecademy.com/resources/cheatsheets/all 10. http://nptel.ac.in/courses/102101003/ 11. https://www.ncert.nic.in/textbook.php( "Class XI" and "Class XII" under the drop-down menus) 12. https://stepik.org/catalog/search?q=Bioinformatics 13. https://www.coursera.org/search?query=Bioinformatics & 15. https://www.edx.org/search?q=Bioinformatics 16. https://nptel.ac.in/courses/102/104/102104056/ 17. https://www.mygoblet.org/training-materials/#trainingmaterialstabs|0 18. https://www.biosb.nl/archive-courses/ 19. https://shodhganga.inflibnet.ac.in/simple-search?query=Bioinformatics 20. http://bioinformaticsinstitute.ru/en 21. https://www.ibiology.org/biology-topics/ 22. http://www.cdfd.org.in/empc/scm_classes.html 23. http://bpa-csiro-workshops.github.io/btp-workshop-ngs/ 24. https://www.biostarhandbook.com/ 25. http://www.startbioinfo.org/ 26. http://www.cdfd.org.in/empc/scm_classes.html 27. https://bio.tools/ 28) https://www.embnet.org/wp/quick-guides/ https://www.embnet.org/wp/critical-guides/ 29. https://www.wipo.int/tools/en/gsearch.html?q=Bioinformatics 30. http://countbio.com/ 31. https://www.ebi.ac.uk/training/on-demand 32. http://www.staff.hs-mittweida.de/~wuenschi/doku.php?id=rwbook2 33. https://biotech.co.in/en/binc-bioinformatics-national-certification 34. https://www.youtube.com/results?search_query=ncbi+now 35. https://scilifelab.github.io/courses/ 36. https://www.imsc.res.in/~kabru/parapp/bioinformatics_notes.pdf 37. https://tess.elixir-europe.org/materials 38. https://www.agmoocs.in/courses 39. AWK one liners- http://www.pement.org/awk/awk1line.txt 40. http://rsg-uk.iscbsc.org/resources/16-education-resources.html 41. https://rsgturkey.com/en/resources/ 42. https://iscb-mx.github.io/ 43. https://www.bioinformatics.recipes/ https://www.bioinformatics.recipes/project/list/ https://www.bioinformatics.recipes/latest/recipes/ 44. https://nptel.ac.in/courses/102/106/102106065/ 45. https://onlinecourses.swayam2.ac.in/cec21_bt04/preview 46. https://bioinformaticsdotca.github.io/ 47. https://edu.t-bio.info/collections/ 48. https://edu.t-bio.info/lp-courses/ 49. https://bioconductor.org/help/course-materials/ 50. https://www.iscb.org/education-and-training-resources #newliferesearchfoundationteam #ngunanaddingimentorshipprogram #upcimulticulturalrainministryandglobalmissions #christianyouthsummitmakurdi #themoscowgoodnewschurchandicf #adullamcalvarymission

Learn Python, R & SQL Programming, Bioinformatics, Genomics & Omics/Multiomics, Advanced Genetics, Biotechnology, Bash Scripting, Biostatistics, Statistics and Probability, Machine Learning, Artificial Intelligence, Large Language Models, LangChain, ChatGPT/ChatGPT Plus (4), etc @everyone, we carefully compiled these materials for those who willl be starting their studies soon, you can also find them useful for self-studying. (1) Python, R & SQL Programming, AI - ML/DL (a) From Blogs such as W3Schools, Machine Learning Mastery, Towards Data Science, Kaggle, Coursera, Analytics Vidhya, Leetcode, Khan Academy, Skikit learn, DataCamp, GeekforGeeks, Educative.io, GitHub repositories, Simplilearn, Edureka, mit.edu.courses, ETH Python Course, Symposium materials from GT, dev.to courses, developers.google, byjusfutureschools.edu, Real Python, c-sharpcorner.com, etc - https://docs.google.com/document/d/1--9XgjuOv9ZhDfuGDpUzE1e04JCTtrijSHgMnZ7MI9Y/edit (b) BioPython - For Projects http://biopython.org/DIST/docs/tutorial/Tutorial.html (c) Deep Learning https://dl.ebooksworld.ir/books/Deep.Learning.for.Coders.with.fastai.and.PyTorch.Howard.Gugger.OReilly.9781492045526.EBooksWorld.ir.pdf (d) Computational Genomics with R https://compgenomr.github.io/book/ (e) SQL https://www.sqlbot.co/ https://www.w3schools.com/sql/ https://www.kaggle.com/learn/intro-to-sql https://www.kaggle.com/learn/advanced-sql https://www.kaggle.com/code/dimarudov/data-analysis-using-sql (2) Maths of Machine Learning By deeplearning.ai https://www.deeplearning.ai/courses/mathematics-for-machine-learning-and-data-science-specialization/ (b) ChatGPT for Education and Research Chat GPT 4 - ChatGPT Free Download AI ChatBot: Smart Assistant and enjoy it on your iOS. Simplify your life with a smart assistant chatgpt. The only difference between the two chatbots is the number of parameters used in their architecture. ChatGPT uses the transformer model with 12 layers and 117 million parameters. However, ChatGPT Plus is powered by a 24-layer transformer model with 1.5 billion parameters. https://medium.com/@ind/chatgpt-vs-chatgpt-plus-a-comparison-e8b233165def https://www.producthunt.com/stories/is-chatgpt-plus-worth-it-chatgpt-paid-vs-free https://drasmajabeen.com/chatgpt-for-scientific-research-paper-writing/ (c) Researchers Discover a More Flexible Approach to Machine Learning: https://www.quantamagazine.org/researchers-discover-a-more-flexible-approach-to-machine-learning-20230207/ (d) LangChain AI in Python https://python.langchain.com/docs/use_cases/code_understanding https://pypi.org/project/langchain/ (e) Chain-of-thought (CoT) AI ThoughtSource: A central hub for large language model reasoning data - A Nature paper: https://www.nature.com/articles/s41597-023-02433-3 (3) Shomu's Biology - Any topic in Biology, e.g: (a) Advanced Genetics - Lecture Part 1-13 - https://m.youtube.com/watch?v=3eKZ3ffUA2Y&t=5s Quantitative Genetics Problems - part 1-13 (b) Biostatistics Part 1-14 - https://m.youtube.com/watch?v=Ip7NDs1oDOo (c) Population Genetics Part 1-20 - https://m.youtube.com/watch?v=L7rpgdOsq_s Population Genetics problems and maths problems in population genetics part 1 to Chapter 8 problems - https://m.youtube.com/watch?v=fNZ9wBb3Opw (d) Ecology Part 1-19 - https://m.youtube.com/watch?v=mQ16jszjyFo (e) Epidemiology https://m.youtube.com/watch?v=sB4EBtPPDdw (f) Bioinformatics and Practical Bioinformatics - 42 videos in total Part 1-17 with practical bioinformatics aspects 1-23 - https://m.youtube.com/watch?v=w-uk-_TOgR0&list=PLb0WW0k29aHrF8aZzK17ORTesZsd-lING&index=1&pp=iAQB (g) Data Analysis in Medicine and Health Using R https://lnkd.in/dRg6jFu5 Other Bioinformatics Resources BabrahamBioinf videos: https://www.youtube.com/watch?v=mQ2KbMOJOXU NCBI: https://www.youtube.com/watch?v=QIZ8QH6JcC8 EMBL: https://www.youtube.com/playlist?list=PL67E0627174F36FCF Bioinformatics WorkBook: https://bioinformaticsworkbook.org/list.html#gsc.tab=0