Free Artificial Intelligence Course for Beginners from Microsoft with Codes and Videos
https://github.com/microsoft/generative-ai-for-beginners
#AI #Microsoft #LearnAI #TechForBeginners #FreeCourse
Motivational Text:
Embark on your journey into the world of Artificial Intelligence with this free beginner-friendly course from Microsoft! Whether you're new to AI or looking to strengthen your foundational knowledge, this course offers step-by-step guidance, practical codes, and video tutorials to help you master the basics of generative AI. Start learning today and unlock your potential in the ever-evolving field of technology!⭐️ 💻 #AIForEveryone #TechEducation #FutureSkills
https://www.tgoop.com/CodeProgrammer
https://github.com/microsoft/generative-ai-for-beginners
#AI #Microsoft #LearnAI #TechForBeginners #FreeCourse
Motivational Text:
Embark on your journey into the world of Artificial Intelligence with this free beginner-friendly course from Microsoft! Whether you're new to AI or looking to strengthen your foundational knowledge, this course offers step-by-step guidance, practical codes, and video tutorials to help you master the basics of generative AI. Start learning today and unlock your potential in the ever-evolving field of technology!
https://www.tgoop.com/CodeProgrammer
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ChatGPT cheat sheet for data science.pdf
29 MB
Title: ChatGPT Cheat Sheet for Data Science (2025)
Source: DataCamp
Description:
This comprehensive cheat sheet serves as an essential guide for leveraging ChatGPT in data science workflows. Designed for both beginners and seasoned practitioners, it provides actionable prompts, code examples, and best practices to streamline tasks such as data generation, analysis, modeling, and automation. Key features include:
- Code Generation: Scripts for creating sample datasets in Python using Pandas and NumPy (e.g., generating tables with primary keys, names, ages, and salaries) .
- Data Analysis: Techniques for exploratory data analysis (EDA), hypothesis testing, and predictive modeling, including visualization recommendations (bar charts, line graphs) and statistical methods .
- Machine Learning: Guidance on algorithm selection, hyperparameter tuning, and model interpretation, with examples tailored for Python and SQL .
- NLP Applications: Tools for text classification, sentiment analysis, and named entity recognition, leveraging ChatGPT’s natural language processing capabilities .
- Workflow Automation: Strategies for automating repetitive tasks like data cleaning (handling duplicates, missing values) and report generation .
The guide also addresses ChatGPT’s limitations, such as potential biases and hallucinations, while emphasizing best practices for iterative prompting and verification . Updated for 2025, it integrates the latest advancements in AI-assisted data science, making it a must-have resource for efficient, conversational-driven analytics.
Tags:
#ChatGPT #DataScience #CheatSheet #2025Edition #DataCamp #Python #MachineLearning #DataAnalysis #Automation #NLP #SQL
https://www.tgoop.com/CodeProgrammer⭐️
Source: DataCamp
Description:
This comprehensive cheat sheet serves as an essential guide for leveraging ChatGPT in data science workflows. Designed for both beginners and seasoned practitioners, it provides actionable prompts, code examples, and best practices to streamline tasks such as data generation, analysis, modeling, and automation. Key features include:
- Code Generation: Scripts for creating sample datasets in Python using Pandas and NumPy (e.g., generating tables with primary keys, names, ages, and salaries) .
- Data Analysis: Techniques for exploratory data analysis (EDA), hypothesis testing, and predictive modeling, including visualization recommendations (bar charts, line graphs) and statistical methods .
- Machine Learning: Guidance on algorithm selection, hyperparameter tuning, and model interpretation, with examples tailored for Python and SQL .
- NLP Applications: Tools for text classification, sentiment analysis, and named entity recognition, leveraging ChatGPT’s natural language processing capabilities .
- Workflow Automation: Strategies for automating repetitive tasks like data cleaning (handling duplicates, missing values) and report generation .
The guide also addresses ChatGPT’s limitations, such as potential biases and hallucinations, while emphasizing best practices for iterative prompting and verification . Updated for 2025, it integrates the latest advancements in AI-assisted data science, making it a must-have resource for efficient, conversational-driven analytics.
Tags:
#ChatGPT #DataScience #CheatSheet #2025Edition #DataCamp #Python #MachineLearning #DataAnalysis #Automation #NLP #SQL
https://www.tgoop.com/CodeProgrammer
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- Learn by Doing: Perfect for beginners and coders upgrading to Python 3! Hands-on examples, exercises, and projects.
- Jupyter Notebook Edition: Entire book redesigned as interactive notebooks! Run code, visualize results, and experiment live.
- Free & Open Source: Licensed under CC BY-NC-SA—download, share, and contribute!
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Use
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ChatGPT Cheat Sheet for Business (2025).pdf
8 MB
ChatGPT Cheat Sheet for Business - DataCamp
Unlock the full potential of AI with our comprehensive ChatGPT Cheat Sheet for Business! Tailored specifically for professionals and entrepreneurs, this guide offers actionable insights on leveraging ChatGPT to streamline workflows, enhance customer interactions, and drive business growth. Whether you're a marketing specialist, project manager, or CEO, this cheat sheet is your go-to resource for mastering conversational AI.
From crafting compelling content to automating routine tasks, learn how to harness the power of ChatGPT in real-world business scenarios. With clear examples and step-by-step instructions, you’ll be able to integrate ChatGPT seamlessly into your operations, improving efficiency and innovation.
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https://www.tgoop.com/CodeProgrammer⭐️
Unlock the full potential of AI with our comprehensive ChatGPT Cheat Sheet for Business! Tailored specifically for professionals and entrepreneurs, this guide offers actionable insights on leveraging ChatGPT to streamline workflows, enhance customer interactions, and drive business growth. Whether you're a marketing specialist, project manager, or CEO, this cheat sheet is your go-to resource for mastering conversational AI.
From crafting compelling content to automating routine tasks, learn how to harness the power of ChatGPT in real-world business scenarios. With clear examples and step-by-step instructions, you’ll be able to integrate ChatGPT seamlessly into your operations, improving efficiency and innovation.
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👩🏻💻 Guys , GenAI Community has created a free Python training course where you will learn both Python and its application in generative artificial intelligence!
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Linear Algebra for Data Science.pdf
611.5 KB
🚀 Master Linear Algebra for Data Science with Gilbert Strang’s Essential Guide!
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Discover "Linear Algebra for Data Science" – an 80-page powerhouse booklet by MIT’s legendary professor Gilbert Strang. Crafted during the Corona era as part of his ZoomNotes series, this concise resource distills practical linear algebra concepts into clear, actionable insights.
📘 What’s Inside?
- Core topics: Matrix Factorizations, Eigenvalues, Vector Spaces, and more!
- Data Science connections: Learn how linear algebra powers ML, statistics, and optimization.
- Perfectly complements Strang’s MIT video lectures for a seamless learning experience.
💡 Why Choose This Booklet?
- MIT-approved clarity: Strang’s teaching brilliance shines in every page.
- Compact & focused: Skip the fluff – dive straight into key concepts.
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80 Python Interview Questions.pdf
410.4 KB
- Covers frequently asked questions in Python interviews
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Applied Machine Learning in Python: a Hands-on Guide with Code 🧠
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Each chapter is downloadable
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🌟 Dive into the world of Transformers and Self-Attention with one of YouTube's best-kept secrets! 🧠✨ Nobody breaks down complex AI concepts like Professor Bryce – his passion for teaching and dedication to clarity make every lesson unforgettable. 💡📚
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Free Certification Courses to Learn Data Analytics in 2025:
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🔗 https://imp.i384100.net/5gmXXo
2. SQL
🔗 https://edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql
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🔗 https://edx.org/learn/r-programming/harvard-university-statistics-and-r
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🔗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
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🔗https://imp.i384100.net/rQqomy
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🔗https://imp.i384100.net/MmW9b3
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🔗 https://lnkd.in/dpmnthEA
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🔗 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
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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
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Good morning all 😊
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