Coding & Data Science Resources
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Red:📈 Análisis del canal de Telegram Coding & Data Science Resources
El canal Coding & Data Science Resources (@codingfreebooks) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 32 421 suscriptores, ocupando la posición 4 025 en la categoría Tecnologías y Aplicaciones y el puesto 12 523 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 32 421 suscriptores.
Según los últimos datos del 25 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 244, y en las últimas 24 horas de 4, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.77%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 899 visualizaciones. En el primer día suele acumular 0 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 7.
- Intereses temáticos: El contenido se centra en temas clave como insidead, chart, programming, mining, lecture.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Official Telegram Channel for Free Coding & Data Science Resources
Admin: @love_data”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
32 421
Suscriptores
+424 horas
-67 días
+24430 días
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Publicaciones del Canal
💻 How to Learn Programming in 1 Year – Step by Step 📝✨
✅ Tip 1: Start with a Single Language
Choose one language (Python, JavaScript, or Java) and stick to it. Mastering one deeply beats superficial knowledge of many—Python's great for beginners due to its readability.
✅ Tip 2: Learn the Basics First
Focus on fundamentals:
⦁ Variables & Data Types
⦁ Loops & Conditionals
⦁ Functions / Methods
⦁ Lists, Arrays, Dictionaries / Objects
✅ Tip 3: Practice Small Projects
Build weekly:
⦁ Calculator
⦁ To-do list app
⦁ Simple web scraper
⦁ Guess-the-number game
⦁ Weather API fetcher
✅ Tip 4: Understand Problem-Solving & Logic
Programming is problem-solving:
⦁ Break problems into steps
⦁ Write pseudocode
⦁ Debug carefully—use print statements or debuggers
✅ Tip 5: Learn Version Control
Use Git to track changes, collaborate, and avoid losing work. Commands like git commit, push, and branch are essentials.
✅ Tip 6: Read Others' Code
Explore open-source on GitHub to see pro structure and patterns—start with simple repos like a basic web app.
✅ Tip 7: Practice Coding Challenges
Hit LeetCode, HackerRank, or Codewars daily for logic, algorithms, and speed—aim for 5-10 problems/week.
✅ Tip 8: Understand Key Concepts Deeply
⦁ Object-Oriented Programming (OOP)
⦁ Recursion
⦁ Data Structures – Arrays, Lists, Stacks, Queues, Trees
⦁ Algorithms – Sorting, Searching
✅ Tip 9: Build Real Projects
⦁ Portfolio website
⦁ Chatbot
⦁ Data analysis with Python
⦁ Simple game
⦁ Full-stack app like a blog
✅ Tip 10: Be Consistent & Review
Code daily (30-60 mins), review old code to refine style. Track progress with a journal or GitHub streak.
💬 Tap ❤️ for more!
| 2 |  🔰 10 python one liners | 1 233 |
| 3 |  If you’re a student, graduate, or someone looking for a career switch, read this.
Most people spend months watching random YouTube videos and still don’t become job-ready.
Instead, learn in a structured offline classroom.
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| 4 | Data Analyst Interview Questions & Preparation Tips
Be prepared with a mix of technical, analytical, and business-oriented interview questions.
1. Technical Questions (Data Analysis & Reporting)
SQL Questions:
How do you write a query to fetch the top 5 highest revenue-generating customers?
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.
How would you optimize a slow-running query?
What are CTEs and when would you use them?
Data Visualization (Power BI / Tableau / Excel)
How would you create a dashboard to track key performance metrics?
Explain the difference between measures and calculated columns in Power BI.
How do you handle missing data in Tableau?
What are DAX functions, and can you give an example?
ETL & Data Processing (Alteryx, Power BI, Excel)
What is ETL, and how does it relate to BI?
Have you used Alteryx for data transformation? Explain a complex workflow you built.
How do you automate reporting using Power Query in Excel?
2. Business and Analytical Questions
How do you define KPIs for a business process?
Give an example of how you used data to drive a business decision.
How would you identify cost-saving opportunities in a reporting process?
Explain a time when your report uncovered a hidden business insight.
3. Scenario-Based & Behavioral Questions
Stakeholder Management:
How do you handle a situation where different business units have conflicting reporting requirements?
How do you explain complex data insights to non-technical stakeholders?
Problem-Solving & Debugging:
What would you do if your report is showing incorrect numbers?
How do you ensure the accuracy of a new KPI you introduced?
Project Management & Process Improvement:
Have you led a project to automate or improve a reporting process?
What steps do you take to ensure the timely delivery of reports?
4. Industry-Specific Questions (Credit Reporting & Financial Services)
What are some key credit risk metrics used in financial services?
How would you analyze trends in customer credit behavior?
How do you ensure compliance and data security in reporting?
5. General HR Questions
Why do you want to work at this company?
Tell me about a challenging project and how you handled it.
What are your strengths and weaknesses?
Where do you see yourself in five years?
How to Prepare?
Brush up on SQL, Power BI, and ETL tools (especially Alteryx).
Learn about key financial and credit reporting metrics.(varies company to company)
Practice explaining data-driven insights in a business-friendly manner.
Be ready to showcase problem-solving skills with real-world examples.
React with ❤️ if you want me to also post sample answer for the above questions
Share with credits: https://t.me/sqlspecialist
Hope it helps :) | 964 |
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| 6 | Python has a built-in topological dependency sorter!🚀
If you're working with tasks that have dependencies — for example, in build systems, CI/CD pipelines, or workflow orchestration — the order of execution often has to be determined manually.
Usually through graphs, DFS,, or custom execution order logic.
But Python's standard library already has graphlib.TopologicalSorter.
ts = TopologicalSorter()
ts.add("deploy", "test")
ts.add("test", "build")
After preparation, the sorter returns the correct execution order.
tuple(ts.static_order())
Result:
("build", "test", "deploy")
Especially useful for workflow management systems, dependency resolution, orchestration systems, and any tasks with a dependency graph.
🔥 TopologicalSorter allows you to solve dependency problems using Python's built-in tools without having to implement graph algorithms manually. | 1 023 |
| 7 | Python has a built-in topological dependency sorter!🚀
If you're working with tasks that have dependencies — for example, in build systems, CI/CD pipelines, or workflow orchestration — the order of execution often has to be determined manually.
Usually through graphs, DFS,, or custom execution order logic.
But Python's standard library already has graphlib.TopologicalSorter.
ts = TopologicalSorter()
ts.add("deploy", "test")
ts.add("test", "build")
After preparation, the sorter returns the correct execution order.
tuple(ts.static_order())
Result:
("build", "test", "deploy")
Especially useful for workflow management systems, dependency resolution, orchestration systems, and any tasks with a dependency graph.
🔥 TopologicalSorter allows you to solve dependency problems using Python's built-in tools without having to implement graph algorithms manually.
#Python #DependencyResolution #WorkflowOrchestration #CICD #BuildSystems #TopologicalSort
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