How I've Been Learning AI

Summary

In this video, the speaker discusses the evolving role of AI in the tech industry, offering advice on how to integrate AI tools into workflows. Emphasizing the importance of a solid foundation in Python, cloud services, and AI concepts, they suggest following open-source resources and hands-on practice. The speaker shares their personal experience, highlighting the value of continuous learning and applying AI for automation and personal growth. They encourage viewers to start small, implement AI responsibly, and focus on gaining practical skills to stay relevant in the fast-changing tech landscape.

Takeaways

• 😀 Embrace the opportunities AI brings to your field, but focus on implementing AI into workflows rather than being afraid of it.
• 😀 AI technologies evolve rapidly, so it’s crucial to follow experts and stay updated with the latest developments in the field.
• 😀 Use open-source and free resources, such as the recommended course, to gain a solid foundation in AI and cloud technologies.
• 😀 The course you follow should include demos and resources that allow you to practically apply your learning with real examples.
• 😀 Learn by doing: recreate and modify code from demos to understand how AI works and build your skills hands-on.
• 😀 Take the time to understand code line-by-line, and use tools like Co-pilot to help explain concepts when necessary.
• 😀 Dedicate focused time to learning, as diving deep into these concepts will pay off with a strong foundation in the field.
• 😀 The practical implementation of AI in workflows, like automating tasks or improving reporting, is a key factor in advancing your career.
• 😀 Apply AI tools to your own workflows to demonstrate value, such as using AI for data analysis, cleaning, and reporting.
• 😀 Supplement your learning with additional resources like AI engineering books and blogs on Python to build the necessary skills.
• 😀 If you’re new to Python, start with introductory material before diving into more complex AI topics.

Q & A

What is the main concern the speaker expresses about AI in the field?

The speaker is concerned about the potential for AI to replace jobs in the tech field, particularly in roles like cloud engineering. However, they acknowledge that fear can be productive if channeled into proactive learning and growth.

What advice does the speaker give regarding the use of resources and following people in the AI field?

The speaker advises following experts in the AI field and staying updated on the latest changes, as AI is evolving rapidly. They recommend unfollowing people who don't work in the field and focusing on resources from professionals who are actively involved in AI.

How does the speaker suggest someone new to AI should start learning?

The speaker recommends starting with a solid foundation in AI materials, such as a free and open-source course that includes demos and resources. They suggest following the course in a specific order and understanding each concept step by step, even recreating scripts from scratch.

What is the value of hands-on experience in AI learning according to the speaker?

Hands-on experience is crucial for understanding AI concepts. The speaker emphasizes the importance of running Python scripts, understanding what each line of code does, and experimenting with the code by recreating it from scratch. This approach will deepen understanding and provide practical knowledge.

How long does the speaker estimate it will take to go through the recommended materials?

The speaker estimates that it will take about a month to get through the material, dedicating significant time to learning and practicing, as they did during February and March when they spent 12-14 hours a day working on AI.

What does the speaker say about the complexity of AI learning materials?

The speaker notes that the complexity of AI learning materials increases as you progress through them. However, by the end, the concepts will make much more sense if approached in the correct order and with a clear understanding of the fundamentals.

What is the significance of the speaker’s personal experience with AI in their career?

The speaker highlights how incorporating cloud services into automation at work helped them get promoted from a CIS admin to a cloud engineer in 2017. They now suggest using AI tools to automate tasks like data parsing and reporting, similar to how they used cloud services in the past.

Why does the speaker emphasize the importance of understanding AI tools in the context of workflows?

The speaker stresses that understanding how to implement AI tools in real-world workflows is key to leveraging their potential. This involves using AI for automations and tasks like data cleaning, reporting, and improving workflows, which can enhance one's career and skills.

What resources does the speaker recommend for learning Python?

The speaker recommends a blog post that offers guidance on learning Python, depending on the learner's starting point. They suggest working through the Python material before diving into the AI course if the learner has no prior Python experience.

What is the speaker's perspective on the speed of change in AI?

The speaker emphasizes that AI is evolving quickly, with trends changing every month. For example, the focus shifted from MCP to agents, and then to RAG. The speaker urges learners to stay updated by following current professionals and resources in the field to keep up with this fast-paced evolution.