کتابخانه مهندسی کامپیوتر و پایتون
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ادمین : @maryam3771
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‼️ دنبال فرصت کارآموزی هستید و پیدا نمیکنید؟ می‌خواهید دانشتون در علم داده رو توی پروژه های واقعی پیاده کنید و با اعتماد به نفس بیشتری در مصاحبه شرکت کنید؟

🔻می تونید از فضاهای کارآموزی مجازی استفاده کنید در این سایت ها می تونید بعنوان دانشمند داده بصورت رایگان کارآموزی انجام بدید 👇

https://www.theforage.com/simulations/bcg/data-science-ccdz

https://www.theforage.com/simulations/tata/data-visualisation-p5xo

https://www.theforage.com/simulations/pwc-ch/power-bi-cqxg

https://www.theforage.com/simulations/accenture-nam/data-analytics-mmlb

#علم_داده #DataScience

دانشکده مهندسی کامپیوتر 👇👇

🆔 @programmers_street
👍3
Short roadmap to learn #Tableau 👇

1. Getting Started:
   - Download and install Tableau Public (free) or Tableau Desktop (trial version).
   - Explore the Tableau interface to get familiar with its components.

2. Data Connection:
   - Learn to connect Tableau to your data sources like Excel, CSV, databases, or cloud services.

3. Data Preparation:
   - Understand how to clean and shape data in Tableau using the Data Source tab.

4. Basic Visualization:
   - Create simple visualizations like bar charts, line charts, and scatter plots.

5. Calculations:
   - Learn about calculated fields and basic functions for more complex data transformations.

6. Dashboards and Stories:
   - Explore creating interactive dashboards and stories to present your insights effectively.

7. Advanced Visualizations:
   - Dive into more advanced charts and graphs, such as heat maps, treemaps, and dual-axis charts.

8. Advanced Calculations:
   - Master advanced calculations, such as level of detail (LOD) expressions and table calculations.

9. Mapping:
   - Learn how to create maps and geospatial visualizations using Tableau's mapping features.

10. Data Blending:
    - Understand how to blend data from multiple sources for comprehensive analysis.

11. Performance Optimization:
    - Optimize the performance of your Tableau workbooks for larger datasets.

12. Tableau Server (Optional):
    - If needed, explore Tableau Server for collaboration and sharing.

13. Online Resources:
    - Utilize online tutorials, documentation, and forums to expand your knowledge.

14. Practice:
    - Work on real-world projects to apply what you've learned. Remember to practice and apply your knowledge as you progress through each stage.

15. Certification (Optional):
    - Consider pursuing Tableau certification for formal recognition of your skills.


#علم_داده #DataScience
دانشکده مهندسی کامپیوتر 👇👇

🆔 @programmers_street
👍3
نویسنده کتاب مشهور The Algorithm Design Manual ویدئوهای درس الگوریتمش رو در یوتیوب گذاشته:
https://www.youtube.com/playlist?list=PLOtl7M3yp-DXbHTFe_w9zFPXeau28CDao

Course Website: https://www3.cs.stonybrook.edu/~skiena/373/

Lecture notes, videos, and example sheets: https://www.cl.cam.ac.uk/teaching/2021/Algorithms/materials.html



#علم_داده #DataScience
دانشکده مهندسی کامپیوتر 👇👇

🆔 @programmers_street
3
منابع رایگان از موسسات معتبر بری یادگیری علم داده در سال 2025:

- Harvard
- Stanford
- MIT
- Microsoft
- Google
- IBM

10 Top Courses w/ Certificates* :

1. Python

    - From Harvard

https://cs50.harvard.edu/python/


2. SQL

     - From Stanford Online
https://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

3. Mathematics

     - From MIT OCW
https://ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

4. Excel

    - From Microsoft Learn
https://learn.microsoft.com/training/paths/modern-analytics/


5. PowerBI

    - From Microsoft Learn
https://learn.microsoft.com/collections/m14nt4rdwnwp04


6. Tableau

https://tableau.com/learn/training

7. Data Visualization

     - From Harvard
https://pll.harvard.edu/course/data-science-visualization

8. Data Analysis

     - From IBM
https://skillsbuild.org/adult-learners/explore-learning/data-analyst

9. Data Science using Python
https://learn.saylor.org/course/view.php?id=504

10. Machine Learning

      - From Google
https://developers.google.com/machine-learning/crash-course

#علم_داده #DataScience

🆔 @programmers_street
👍3
Data pipelines let you collect, process, and use huge amounts of data efficiently.

But building and maintaining these pipelines can be tricky with API rate limits, changing data schemas, etc.

In this in-depth course, you'll learn about data ingestion & normalization, data loading with an open source Python library, tuning performance, and much more.

https://www.freecodecamp.org/news/data-loading-with-python-and-ai/



#علم_داده #DataScience #پایتون

🆔 @programmers_street
برای تبدیل شدن به یه مهندس داده حرفه ای باید پروژه های واقعی انجام بدید

اگه می خواهید مهارت هاتون رو ارتقا بدید و با رزومه ای قوی وارد بازار کار بشید پیشنهاد میکنم از پروژه های رایگان این وبسایت استفاده کنید و علم داده را از حرفه ای ها یاد بگیرید

https://www.wqu.edu/adsl-apply

https://www.wqu.edu/ai-lab-computer-vision-apply



#علم_داده #DataScience

🆔 @programmers_street
👍1