How I’d Learn AI in 2024 (if I could start over)

Here’s the roadmap that I would follow to learn artificial intelligence (AI).
📚 Get the FREE roadmap here ➡️ https://bit.ly/data-alchemy

⏱️ Timestamps
00:00 Introduction
00:34 Why learn AI?
01:28 Code vs. Low/No-code approach
02:27 Misunderstandings about AI
03:27 Ask yourself this question
04:19 What makes this approach different
05:42 Step 1: Set up your environment
06:54 Step 2: Learn Python and key libraries
08:02 Step 3: Learn Git and GitHub Basics
08:35 Step 4: Work on projects and portfolio
13:12 Step 5: Specialize and share knowledge
14:31 Step 6: Continue to learn and upskill
15:39 Step 7: Monetize your skills
16:53: What is Data Alchemy?

🛠️ Explore ProjectPro
https://bit.ly/3q837w8

👋🏻 About Me
Hey there! I’m Dave, an AI Engineer and the founder of Datalumina, where our mission is to facilitate entrepreneurial and technological proficiency in professionals and businesses. Through my videos here on this channel, my posts on LinkedIn, and courses on Skool, I share practical strategies and tools to navigate the complexities of data, artificial intelligence, and entrepreneurship.

🎓 My Courses
https://www.skool.com/data-alchemy
https://www.skool.com/data-freelancer

🔗 Let’s Connect
https://www.linkedin.com/in/daveebbelaar/
https://www.instagram.com/daveebbelaar/

📥 Datalumina’s Newsletter
https://www.datalumina.com/newsletter

#ai #roadmap #datalumina

📌 Video Description
In this video, Dave shares a comprehensive and actionable roadmap for anyone looking to start their journey into the exciting world of artificial intelligence (AI) in 2024. Whether you’re a complete beginner or someone looking to pivot your career towards AI, this video lays out a step-by-step guide that demystifies the process of learning AI from the ground up. Dave highlights the significance of AI in today’s tech landscape and addresses common misconceptions that newcomers might have.

With a focus on practical learning, the video emphasizes the importance of choosing between a code-centric or a low/no-code approach, making AI accessible to a broader audience. Dave’s unique approach involves asking a critical question that shapes the learning path, ensuring that viewers embark on a journey tailored to their goals and interests.

The roadmap detailed in the video covers essential steps such as setting up your learning environment, mastering Python and key libraries crucial for AI, understanding the basics of Git and GitHub, and the importance of working on projects to build a strong portfolio. Dave also talks about the importance of specialization and the continuous process of learning and upskilling in fields like generative AI, large language models, chatbots, and machine learning.

Furthermore, Dave shares insights on how to monetize your AI skills, turning your passion into a profession. The video concludes with an introduction to Data Alchemy, a concept that encapsulates the transformative power of AI knowledge.

For those eager to dive into the AI world, Dave offers a free roadmap accessible through the link provided in the video description. This invaluable resource serves as a compass for navigating the complexities of AI learning, making it an essential watch for anyone interested in artificial intelligence, machine learning, and related technologies.

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