How I’d Learn AI (If I Had to Start Over)🎯Explore the Simplilearn course on the website at https://bit.ly/Manish-Simplilearn

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Watch how to configure Oracle on VS Code https://youtu.be/6mwAx4sGhwk

Course Suggestion
Artificial Intelligence Engineer https://www.simplilearn.com/masters-in-artificial-intelligence
SQL Certification Course https://www.simplilearn.com/sql

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The camera gear I use in my Videos
https://www.amazon.in/shop/manishsharma?listId=DU9UM0XL97KM&ref=idea_share_inf

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Connect With Me on My Social Media
https://www.instagram.com/RebellionRider/
https://www.facebook.com/TheRebellionRider/

https://www.linkedin.com/in/mannbhardwaj/

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FAQ
Which book to refer to learn –
PL/SQL https://amzn.to/2QE1jX0
Performance Tuning https://amzn.to/2sgiAw4
1z0-071 Exam https://amzn.to/2sgfeJw
Python Programming https://amzn.to/305UEbh

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AFFILIATE DISCLOSURE:
Some of the links used in the description will direct you to Amazon.in. As an Amazon Associate, I earn from qualifying purchases at no additional cost to you.
#rebellionrider

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How to Learn AI From Scratch in 2024
I remember my early days diving into the world of Artificial Intelligence—navigating through endless resources, coding challenges, and those late-night debugging sessions. I had no idea about How to Learn AI From Scratch. If I had to start over today, I’d streamline my journey with the wisdom gained over the years. 🌟

With my journey in AI culminating in projects that leverage machine learning for real-world solutions and earning the 1z0-071 SQL Expert Certification, I’ve realized the importance of a structured learning path. Here’s how I’d approach it:

1️⃣ Foundation First: Start with the basics of programming. Python is the go-to language for AI. Dive into courses on Python and fundamental algorithms.

2️⃣ Math & Stats: Understand the math behind the magic. Focus on linear algebra, probability, and statistics. Khan Academy and MIT OpenCourseWare are great resources.

3️⃣ Machine Learning Mastery: Move to machine learning with Andrew Ng’s Coursera course. His approach is comprehensive and beginner-friendly.

4️⃣ Hands-on Projects: Apply what you learn. Platforms like Kaggle provide datasets to practice on real problems.

5️⃣ Stay Updated: AI is ever-evolving. Follow renowned journals and conferences like NeurIPS and CVPR. A study by Gartner indicates that by 2025, AI will be embedded in nearly every new software product.

6️⃣ Community & Mentorship: Join AI communities. Engaging with others can offer insights, support, and collaboration opportunities.

7️⃣ Ethics in AI: Finally, always consider the ethical implications of your work. Understand the potential biases and impacts of AI solutions.

The journey in AI is challenging but immensely rewarding. With dedication and the right resources, you can master this fascinating field. 🚀

🔗 Swipe left for some of my favorite resources and tools in AI.

Chapters
0:00 AI roadmap
0:18 Machine Learning Vs AI
1:04 AI course Suggestion
2:04 Is Math required for learning AI?
3:12 Which Programming Language is best for AI?
3:44 Python libraries for AI
5:08 Do we need SQL for AI?
5:34 SQL Course Suggestion for AI
6:04 Do we need to learn machine learning for AI?

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