Data Science Machine Learning Data Analysis
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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

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Free Certification Courses to Learn Data Analytics in 2025:

1. Python
🔗 https://imp.i384100.net/5gmXXo

2. SQL
🔗 https://edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql

3. Statistics and R
🔗 https://edx.org/learn/r-programming/harvard-university-statistics-and-r

4. Data Science: R Basics
🔗https://edx.org/learn/r-programming/harvard-university-data-science-r-basics

5. Excel and PowerBI
🔗 https://learn.microsoft.com/en-gb/training/paths/modern-analytics/

6. Data Science: Visualization
🔗https://edx.org/learn/data-visualization/harvard-university-data-science-visualization

7. Data Science: Machine Learning
🔗https://edx.org/learn/machine-learning/harvard-university-data-science-machine-learning

8. R
🔗https://imp.i384100.net/rQqomy

9. Tableau
🔗https://imp.i384100.net/MmW9b3

10. PowerBI
🔗 https://lnkd.in/dpmnthEA

11. Data Science: Productivity Tools
🔗 https://lnkd.in/dGhPYg6N

12. Data Science: Probability
🔗https://mygreatlearning.com/academy/learn-for-free/courses/probability-for-data-science

13. Mathematics
🔗http://matlabacademy.mathworks.com

14. Statistics
🔗 https://lnkd.in/df6qksMB

15. Data Visualization
🔗https://imp.i384100.net/k0X6vx

16. Machine Learning
🔗 https://imp.i384100.net/nLbkN9

17. Deep Learning
🔗 https://imp.i384100.net/R5aPOR

18. Data Science: Linear Regression
🔗https://pll.harvard.edu/course/data-science-linear-regression/2023-10

19. Data Science: Wrangling
🔗https://edx.org/learn/data-science/harvard-university-data-science-wrangling

20. Linear Algebra
🔗 https://pll.harvard.edu/course/data-analysis-life-sciences-2-introduction-linear-models-and-matrix-algebra

21. Probability
🔗 https://pll.harvard.edu/course/data-science-probability

22. Introduction to Linear Models and Matrix Algebra
🔗https://edx.org/learn/linear-algebra/harvard-university-introduction-to-linear-models-and-matrix-algebra

23. Data Science: Capstone
🔗 https://edx.org/learn/data-science/harvard-university-data-science-capstone

24. Data Analysis
🔗 https://pll.harvard.edu/course/data-analysis-life-sciences-4-high-dimensional-data-analysis

25. IBM Data Science Professional Certificate
https://imp.i384100.net/9gxbbY

26. Neural Networks and Deep Learning
https://imp.i384100.net/DKrLn2

27. Supervised Machine Learning: Regression and Classification
https://imp.i384100.net/g1KJEA

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #SupervisedLearning #IBMDataScience #FreeCourses #Certification #LearnDataScience
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🍃 Stem-Leaf Plot - An intelligent visualization!

It's a simple and effective way to visualize and compare datasets.

📊 Imagine we have two datasets: Set 1 (7, 12, 14, 17, 19, 23, 25) and Set 2 (3, 11, 16, 18, 20, 21, 24). We'll use a stem-leaf plot to compare them.

🌿 First, let's create the 'stem' which represents the tens place (0, 1, 2) and the 'leaf' represents the ones place (0-9).

🔍 By comparing the plots, we can see that Dataset 1 has higher values in the tens place, while Dataset 2 has a more uniform distribution.

🎯 Stem-leaf plots are great for small datasets and provide a clear picture of data distribution. The special thing about a stem-and-leaf diagram is that the original data can be read out of the graphical representation.


Give it a try next time you need to compare datasets!

✍🏽 Have you used stem-leaf plots before?

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #SupervisedLearning #IBMDataScience #FreeCourses #Certification #LearnDataScience

https://yangx.top/CodeProgrammer ✈️
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🗂 10 “Real Data Science Portfolio” Examples

📁 I've brought you 10 of the best portfolios from data science professionals, each of whom has followed a unique path! Check out these 10 and get inspired to build a strong portfolio of your own!👇
1️⃣ Ken Jee Portfolio | Data Scientist
▶️ Field: Sports data analysis
👤 Link: Portfolio

2️⃣ Yassine Alouini's Portfolio | Kegel Master
▶️ Domain: Machine Learning and Kegel Competitions
👤 Link: Portfolio

3️⃣ Tatman Portfolio | Data Scientist
▶️ Domain: Natural Language Processing (NLP)
👤 Link: Portfolio

4️⃣ Robinson Portfolio | Data Scientist
▶️ Field: Statistical analysis and R programming
👤 Link: Portfolio

5️⃣ Siraj Raval's Portfolio | AI Instructor
▶️ Field: Machine Learning and Artificial Intelligence
👤 Link: Portfolio

6️⃣ Julia Silge's Portfolio | Data Scientist
▶️ Domain: Organized data and data visualization
👤 Link: Portfolio

7️⃣ Mueller Portfolio | Developer Scikit-Learn
▶️ Field: Machine learning and open source projects
👤 Link: Portfolio

8️⃣ Wickham Portfolio | Data Scientist
▶️ Area: R programming and data visualization
👤 Link: Portfolio

9️⃣ Portfolio of François Puget | Kegel Master
▶️ Domain: Advanced Machine Learning Techniques
👤 Link: Portfolio

🔟 Emily's Portfolio | Data Analyst at Disney
▶️ Domain: Data visualization and storytelling
👤 Link: Portfolio

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #SupervisedLearning #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming

https://yangx.top/CodeProgrammer 🧠
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🔥 MIT has updated its famous course 6.S191: Introduction to Deep Learning.

The program covers topics of #NLP, #CV, #LLM and the use of technology in medicine, offering a full cycle of training - from theory to practical classes using current versions of libraries.

The course is designed even for beginners: if you know how to take derivatives and multiply matrices, everything else will be explained in the process.

The lectures are released for free on YouTube and the #MIT platform on Mondays, with the first one already available

.

All slides, #code and additional materials can be found at the link provided.

📌 Fresh lecture : https://youtu.be/alfdI7S6wCY?si=6682DD2LlFwmghew

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras

https://yangx.top/CodeProgrammer
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Numpy @CodeProgrammer.pdf
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🏳️‍🌈 "NumPy Library" Tutorial

👨🏻‍💻 For the past few days, I've been busy preparing this comprehensive tutorial on the NumPy library for data science, trying to cover all the tips and tricks of this library.

Why is this booklet different? Because it is not written based on just theoretical concepts, but is the result of my own experiences and learning. It has real and practical examples that will help you better understand #NumPy concepts and use them in your projects.💯

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras

https://yangx.top/CodeProgrammer
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