Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.

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πŸ“š 3D Deep Learning with Python (2022)

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πŸ“š Fundamentals and Methods of Machine and Deep Learning (2022)

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πŸ“š Deep Learning (2023)

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πŸ“š Deep Learning for EEG-based Brain-computer Interfaces (2022)

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πŸ“š Learning Deep Learning (2022)

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πŸ“š Fundamentals of Machine Learning and Deep Learning in Medicine (2023)

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πŸ“š Regularization in Deep Learning (2023)

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πŸ“š Deep Learning with JAX (2023)

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πŸ“š Interpretability in Deep Learning (2023)

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⚠️ O'Reilly Media, one of the most reputable publishers in the fields of programming, data mining, and AI, has made 10 data science books available to those interested in this field for free .

βœ”οΈ To use the online and PDF versions of these books, you can use the following links:πŸ‘‡

0⃣ Python Data Science Handbook
β”Œ Online
β””
PDF

1⃣ Python for Data Analysis book
β”Œ Online
β””
PDF

πŸ”’ Fundamentals of Data Visualization book
β”Œ Online
β””
PDF

πŸ”’ R for Data Science book
β”Œ Online
β””
PDF

πŸ”’ Deep Learning for Coders book
β”Œ Online
β””
PDF

πŸ”’ DS at the Command Line book
β”Œ Online
β””
PDF

πŸ”’ Hands-On Data Visualization Book
β”Œ Online
β””
PDF

πŸ”’ Think Stats book
β”Œ Online
β””
PDF

πŸ”’ Think Bayes book
β”Œ Online
β””
PDF

πŸ”’ Kafka, The Definitive Guide
β”Œ Online
β””
PDF

#DataScience #Python #DataAnalysis #DataVisualization #RProgramming #DeepLearning #CommandLine #HandsOnLearning #Statistics #Bayesian #Kafka #MachineLearning #AI #Programming #FreeBooks

https://t.iss.one/CodeProgrammer βœ…
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Free Certification Courses to Learn Data Analytics in 2025:

1. Python
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2. SQL
πŸ”— https://edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql

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

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

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

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

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

8. R
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9. Tableau
πŸ”—https://imp.i384100.net/MmW9b3

10. PowerBI
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11. Data Science: Productivity Tools
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12. Data Science: Probability
πŸ”—https://mygreatlearning.com/academy/learn-for-free/courses/probability-for-data-science

13. Mathematics
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14. Statistics
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15. Data Visualization
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16. Machine Learning
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17. Deep Learning
πŸ”— https://imp.i384100.net/R5aPOR

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

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

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

21. Probability
πŸ”— https://pll.harvard.edu/course/data-science-probability

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

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

24. Data Analysis
πŸ”— 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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