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Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

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Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data

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๐Ÿ“ˆ Telegram kanali Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books analitikasi

Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 56 111 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 375-o'rinni va Hindiston mintaqasida 6 527-o'rinni egallagan.

๐Ÿ“Š Auditoriya koโ€˜rsatkichlari va dinamika

ะฝะตะฒั–ะดะพะผะพ sanasidan buyon loyiha tez oโ€˜sib, 56 111 obunachiga ega boโ€˜ldi.

09 Iyun, 2026 dagi oxirgi maโ€™lumotlarga koโ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 105 ga, soโ€˜nggi 24 soatda esa 12 ga oโ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oโ€˜rtacha 2.63% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.84% ini tashkil etuvchi reaksiyalarni toโ€˜playdi.
  • Post qamrovi: Har bir post oโ€˜rtacha 1 473 marta koโ€˜riladi; birinchi sutkada odatda 470 ta koโ€˜rish yigโ€˜iladi.
  • Reaksiyalar va oโ€˜zaro taโ€™sir: Auditoriya faol: har bir postga oโ€˜rtacha 3 ta reaksiya keladi.
  • Tematik yoโ€˜nalishlar: Kontent algorithm, structure, stack, javascript, programming kabi asosiy mavzularga jamlangan.

๐Ÿ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโ€™riflaydi:
โ€œEverything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_dataโ€

Yuqori yangilanish chastotasi (oxirgi maโ€™lumot 10 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโ€™sir nuqtasiga aylantirishini koโ€˜rsatadi.

56 111
Obunachilar
+1224 soatlar
+527 kunlar
+10530 kunlar
Postlar arxiv
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To join Microsoft as a Data Engineer or Software Development Engineer (SDE), here are the key skills you should focus on preparing: 1. Programming Languages - Python: Essential for data manipulation and ETL tasks. - SQL: Strong command over writing queries for data retrieval, manipulation, and performance tuning. - Java/Scala: Important for working with big data frameworks and building scalable systems. 2. Big Data Technologies - Apache Hadoop: Understanding of distributed data storage and processing. - Apache Spark: Experience with batch and real-time data processing. - Kafka: Knowledge of data streaming technologies. 3. Cloud Platforms - Microsoft Azure: Especially services like Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Blob Storage. - AWS or Google Cloud: Familiarity with cloud infrastructure is valuable, but Azure expertise will be a plus. 4. ETL Tools and Data Pipelines - Understanding how to build and manage ETL (Extract, Transform, Load) pipelines. - Knowledge of tools like Airflow, Talend, Azure Data Factory, or similar platforms. 5. Databases and Data Warehousing - Relational Databases: MySQL, PostgreSQL, SQL Server. - NoSQL Databases: MongoDB, Cassandra, DynamoDB. - Data Warehousing: Familiarity with tools like Snowflake, Redshift, or Azure Synapse. 6. Version Control and CI/CD - Git: Proficient in version control systems. - Continuous Integration/Continuous Deployment (CI/CD): Familiarity with Jenkins, GitHub Actions, or Azure DevOps. 7. Data Modeling and Architecture - Experience in designing scalable data models and database architectures. - Understanding Data Lakes and Data Warehouses concepts. 8. System Design & Algorithms - Knowledge of data structures and algorithms for solving system design problems. - Ability to design large-scale distributed systems, an important part of the interview process. 9. Analytics Tools - Power BI or Tableau: Useful for data visualization. - Pandas, NumPy for data manipulation in Python. 10. Problem-Solving and Coding Focus on practicing on platforms like LeetCode, HackerRank, or Codeforces to improve problem-solving skills, which are critical for technical interviews. 11. Soft Skills - Collaboration and Communication: Working in teams and effectively communicating technical concepts. - Adaptability: Ability to work in a fast-paced and evolving technical environment. By preparing in these areas, you'll be in a strong position to apply for roles at Microsoft, especially in data engineering or SDE roles. Keep Learning!! Join @pythonjoyy and share it with friends.

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- Learn JavaScript before React. - Learn Git before CI/CD pipelines. - Learn Docker before Kubernetes. - Learn Vanilla DOM before jQuery - Learn REST APIs before GraphQL. - Learn Linux Basics before Docker. - Learn Algorithms before LeetCode - Learn HTML/CSS before JavaScript. - Learn TCP/IP Basics before WebSocket - Learn Data Structures before Algorithms. - Learn Monolithic before Microservices Architecture. - Learn SQL before ORMs (Object-Relational Mapping). - Learn Manual Testing before Test-Driven Development - Learn MVC Pattern before MVVM (Model-View-ViewModel) or SPA (Single-Page Application) frameworks. It all starts with the basics & fundamentals. Have the patience to master them and then move to languages & fundamentals. Good core knowledge allows you to adapt & learn any technologies you need to do your job. I have curated Best Web Development Resources: https://topmate.io/coding/930165 ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

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Common Programming Interview Questions     How do you reverse a string?     How do you determine if a string is a palindrome?     How do you calculate the number of numerical digits in a string?     How do you find the count for the occurrence of a particular character in a string?     How do you find the non-matching characters in a string?     How do you find out if the two given strings are anagrams?     How do you calculate the number of vowels and consonants in a string?     How do you total all of the matching integer elements in an array?     How do you reverse an array?     How do you find the maximum element in an array?     How do you sort an array of integers in ascending order?     How do you print a Fibonacci sequence using recursion?     How do you calculate the sum of two integers?     How do you find the average of numbers in a list?     How do you check if an integer is even or odd?     How do you find the middle element of a linked list?     How do you remove a loop in a linked list?     How do you merge two sorted linked lists?     How do you implement binary search to find an element in a sorted array?     How do you print a binary tree in vertical order? Conceptual Coding Interview Questions     What is a data structure?     What is an array?     What is a linked list?     What is the difference between an array and a linked list?     What is LIFO?     What is FIFO?     What is a stack?     What are binary trees?     What are binary search trees?     What is object-oriented programming?     What is the purpose of a loop in programming?     What is a conditional statement?     What is debugging?     What is recursion?     What are the differences between linear and non-linear data structures? General Coding Interview Questions     What programming languages do you have experience working with?     Describe a time you faced a challenge in a project you were working on and how you overcame it.     Walk me through a project youโ€™re currently or have recently worked on.     Give an example of a project you worked on where you had to learn a new programming language or technology. How did you go about learning it?     How do you ensure your code is readable by other developers?     What are your interests outside of programming?     How do you keep your skills sharp and up to date?     How do you collaborate on projects with non-technical team members?     Tell me about a time when you had to explain a complex technical concept to a non-technical team member.     How do you get started on a new coding project? Best Programming Resources: https://topmate.io/coding/886839 Join for more: https://t.me/programming_guide ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

Repost from Data Analyst Jobs
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๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฆ๐—ค๐—Ÿ ๐—ฌ๐—ผ๐˜‚๐—ง๐˜‚๐—ฏ๐—ฒ ๐—ฃ๐—น๐—ฎ๐˜†๐—น๐—ถ๐˜€๐˜๐˜€ ๐—ง๐—ต๐—ฎ๐˜ ๐—ช๐—ถ๐—น๐—น ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚ ๐—ฎ ๐—ค๐˜‚๐—ฒ๐—ฟ๐˜† ๐—ฃ๐—ฟ๐—ผ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜ S
๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฆ๐—ค๐—Ÿ ๐—ฌ๐—ผ๐˜‚๐—ง๐˜‚๐—ฏ๐—ฒ ๐—ฃ๐—น๐—ฎ๐˜†๐—น๐—ถ๐˜€๐˜๐˜€ ๐—ง๐—ต๐—ฎ๐˜ ๐—ช๐—ถ๐—น๐—น ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚ ๐—ฎ ๐—ค๐˜‚๐—ฒ๐—ฟ๐˜† ๐—ฃ๐—ฟ๐—ผ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜ Still stuck Googling โ€œWhat is SQL?โ€ every time you start a new project?๐Ÿ’ต Youโ€™re not alone. Many beginners bounce between tutorials without ever feeling confident writing SQL queries on their own.๐Ÿ‘จโ€๐Ÿ’ปโœจ๏ธ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/4f1F6LU Letโ€™s dive into the ones that are actually worth your timeโœ…๏ธ

๐Ÿš€ Complete Roadmap to Become a Data Scientist in 5 Months ๐Ÿ“… Week 1-2: Fundamentals โœ… Day 1-3: Introduction to Data Science, its applications, and roles. โœ… Day 4-7: Brush up on Python programming ๐Ÿ. โœ… Day 8-10: Learn basic statistics ๐Ÿ“Š and probability ๐ŸŽฒ. ๐Ÿ” Week 3-4: Data Manipulation & Visualization ๐Ÿ“ Day 11-15: Master Pandas for data manipulation. ๐Ÿ“ˆ Day 16-20: Learn Matplotlib & Seaborn for data visualization. ๐Ÿค– Week 5-6: Machine Learning Foundations ๐Ÿ”ฌ Day 21-25: Introduction to scikit-learn. ๐Ÿ“Š Day 26-30: Learn Linear & Logistic Regression. ๐Ÿ— Week 7-8: Advanced Machine Learning ๐ŸŒณ Day 31-35: Explore Decision Trees & Random Forests. ๐Ÿ“Œ Day 36-40: Learn Clustering (K-Means, DBSCAN) & Dimensionality Reduction. ๐Ÿง  Week 9-10: Deep Learning ๐Ÿค– Day 41-45: Basics of Neural Networks with TensorFlow/Keras. ๐Ÿ“ธ Day 46-50: Learn CNNs & RNNs for image & text data. ๐Ÿ› Week 11-12: Data Engineering ๐Ÿ—„ Day 51-55: Learn SQL & Databases. ๐Ÿงน Day 56-60: Data Preprocessing & Cleaning. ๐Ÿ“Š Week 13-14: Model Evaluation & Optimization ๐Ÿ“ Day 61-65: Learn Cross-validation & Hyperparameter Tuning. ๐Ÿ“‰ Day 66-70: Understand Evaluation Metrics (Accuracy, Precision, Recall, F1-score). ๐Ÿ— Week 15-16: Big Data & Tools ๐Ÿ˜ Day 71-75: Introduction to Big Data Technologies (Hadoop, Spark). โ˜๏ธ Day 76-80: Learn Cloud Computing (AWS, GCP, Azure). ๐Ÿš€ Week 17-18: Deployment & Production ๐Ÿ›  Day 81-85: Deploy models using Flask or FastAPI. ๐Ÿ“ฆ Day 86-90: Learn Docker & Cloud Deployment (AWS, Heroku). ๐ŸŽฏ Week 19-20: Specialization ๐Ÿ“ Day 91-95: Choose NLP or Computer Vision, based on your interest. ๐Ÿ† Week 21-22: Projects & Portfolio ๐Ÿ“‚ Day 96-100: Work on Personal Data Science Projects. ๐Ÿ’ฌ Week 23-24: Soft Skills & Networking ๐ŸŽค Day 101-105: Improve Communication & Presentation Skills. ๐ŸŒ Day 106-110: Attend Online Meetups & Forums. ๐ŸŽฏ Week 25-26: Interview Preparation ๐Ÿ’ป Day 111-115: Practice Coding Interviews (LeetCode, HackerRank). ๐Ÿ“‚ Day 116-120: Review your projects & prepare for discussions. ๐Ÿ‘จโ€๐Ÿ’ป Week 27-28: Apply for Jobs ๐Ÿ“ฉ Day 121-125: Start applying for Entry-Level Data Scientist positions. ๐ŸŽค Week 29-30: Interviews ๐Ÿ“ Day 126-130: Attend Interviews & Practice Whiteboard Problems. ๐Ÿ”„ Week 31-32: Continuous Learning ๐Ÿ“ฐ Day 131-135: Stay updated with the Latest Data Science Trends. ๐Ÿ† Week 33-34: Accepting Offers ๐Ÿ“ Day 136-140: Evaluate job offers & Negotiate Your Salary. ๐Ÿข Week 35-36: Settling In ๐ŸŽฏ Day 141-150: Start your New Data Science Job, adapt & keep learning! ๐ŸŽ‰ Enjoy Learning & Build Your Dream Career in Data Science! ๐Ÿš€๐Ÿ”ฅ

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Git Commands ๐Ÿ›  git init โ€“ Initialize a new Git repository ๐Ÿ“ฅ git clone โ€“ Clone a repository ๐Ÿ“Š git status โ€“ Check the status of your repository โž• git add โ€“ Add a file to the staging area ๐Ÿ“ git commit -m "message" โ€“ Commit changes with a message ๐Ÿš€ git push โ€“ Push changes to a remote repository โฌ‡๏ธ git pull โ€“ Fetch and merge changes from a remote repository Branching ๐Ÿ“Œ git branch โ€“ List all branches ๐ŸŒฑ git branch โ€“ Create a new branch ๐Ÿ”„ git checkout โ€“ Switch to a branch ๐Ÿ”— git merge โ€“ Merge a branch into the current branch โšก๏ธ git rebase โ€“ Apply commits on top of another branch Undo & Fix Mistakes โช git reset --soft HEAD~1 โ€“ Undo the last commit but keep changes โŒ git reset --hard HEAD~1 โ€“ Undo the last commit and discard changes ๐Ÿ”„ git revert โ€“ Create a new commit that undoes a specific commit Logs & History ๐Ÿ“– git log โ€“ Show commit history ๐ŸŒ git log --oneline --graph --all โ€“ View commit history in a simple graph Stashing ๐Ÿ“ฅ git stash โ€“ Save changes without committing ๐ŸŽญ git stash pop โ€“ Apply stashed changes and remove them from stash Remote & Collaboration ๐ŸŒ git remote -v โ€“ View remote repositories ๐Ÿ“ก git fetch โ€“ Fetch changes without merging ๐Ÿ•ต๏ธ git diff โ€“ Compare changes Donโ€™t forget to react โค๏ธ if youโ€™d like to see more content like this!

๐Ÿฑ ๐—ฅ๐—ฒ๐—ฎ๐—น-๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€ ๐˜๐—ผ ๐—•๐˜‚๐—ถ๐—น๐—ฑ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ โ€“ ๐—ช๐—ถ๐˜๐—ต ๐—™๐˜‚๐—น๐—น ๐—ง๐˜‚๐˜๐—ผ๐—ฟ๐—ถ๐—ฎ๐—น๐˜€
๐Ÿฑ ๐—ฅ๐—ฒ๐—ฎ๐—น-๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€ ๐˜๐—ผ ๐—•๐˜‚๐—ถ๐—น๐—ฑ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ โ€“ ๐—ช๐—ถ๐˜๐—ต ๐—™๐˜‚๐—น๐—น ๐—ง๐˜‚๐˜๐—ผ๐—ฟ๐—ถ๐—ฎ๐—น๐˜€!๐Ÿ˜ Are you ready to build real-world tech projects that donโ€™t just look good on your resume, but actually teach you practical, job-ready skills?๐Ÿง‘โ€๐Ÿ’ป๐Ÿ“Œ Hereโ€™s a curated list of 5 high-value development tutorials โ€” covering everything from full-stack development and real-time chat apps to AI form builders and reinforcement learningโœจ๏ธ๐Ÿ’ป ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/3UtCSLO Theyโ€™re real, portfolio-worthy projects you can start todayโœ…๏ธ

Working under a bad tech lead can slow you down in your career, even if you are the most talented Hereโ€™s what you should do if you're stuck with a bad tech lead: Ineffective Tech Lead: - downplays the contributions of their team - creates deadlines without talking to the team - views team members as a tool to build and code - doesnโ€™t trust their team members to do their jobs - gives no space or opportunities for personal / skill development Effective Tech lead: - sets a clear vision and direction - communicates with the team & sets realistic goals - empowers you to make decisions and take ownership - inspires and helps you achieve your career milestones - always looks to add value by sharing their knowledge and coaching I've always grown the most when I've worked with the latter. But I also have experience working with the former. If you are in a team with a bad tech lead, itโ€™s tough, I understand. Hereโ€™s what you can do: โžฅdonโ€™t waste your energy worrying about them โžฅfocus on your growth and what you can do in the environment โžฅfocus and try to fill the gap your lead has created by their behaviors โžฅtalk to your manager and share how you're feeling rather than complain about the lead โžฅtry and understand why they are behaving the way they behave, whatโ€™s important for them And the most important: Donโ€™t get sucked into this behavior and become like one! You will face both types of people in your career: Some will teach you how to do things, and others will teach you how not to do things! Coding Projects:๐Ÿ‘‡ https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502 ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

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