What is your goal for acquiring AI Engineering skills?

[Shaheerairaj]

🤖 Welcome to our AI Engineering course!

As we embark on this learning journey together, I'm curious about what brings you here 😄. AI engineering skills are becoming increasingly valuable across industries, but everyone's motivation for learning them is unique and personal.

Share with us:

• What specific goals are you hoping to achieve by developing AI engineering skills?
• Is there a particular problem or challenge you're passionate about solving with AI?
• How do you envision applying these skills in your current role or future career?
• What impact do you hope to make with the knowledge gained from this course?

Whether you're looking to transition careers, enhance your current skill set, build innovative applications, or just fascinated by the possibilities of AI - your perspective adds value to our learning community and I hope to hear from all of you 😄 .

[idrak-dareshani]

There is overwhelming material out there related to AI, and it tends to take us off the track. My main goal is to upskill myself and what are practical applications of this skill and also how I can monetize it. personally, AI and ML are fun to learn when they are focused on a particular area. if we try to learn everything, we get lost.

[Shaheerairaj]

Completely agree Idrak. One of the purposes of this course was to give a step-by-step practical introduction into the world of Gen AI and LLMs and how we can use these models to build real-world applications.

Hope you have fun in this course.

[idrak-dareshani]

I have few questions:

• Do we need to know how to build our own LLM for specific purpose?
• Are there any LLMs available which are topic specific only like Health care or specific to an industry?
• What is the benefit to use AWS or other cloud providers for LLMs solutions?

[Shaheerairaj]

Hi @idrak-dareshani . Some excellent questions you have.

1. Building our own LLM is probably not a job for most people as it requires massive amounts of investments to build these Neural Networks and train them from scratch. What is most likely possible for us is to fine-tune them which will be covered in later advanced courses.
2. For sure. If you were to go to huggingface (which is the worlds largest hub for ML and AI models) you can find many models that have been finetuned for specific purposes. A quick search for 'healthcare' comes up with all of the following results https://huggingface.co/models?sort=trending&search=healthcare
3. There is huge benefit. As these models are so large, inference on a large scale is impossible from a laptop. We always need to use some kind of cloud storage to deploy and use them for inference. Most of the worlds usable IT infrastructure is already on cloud anyways so it is natural for all our LLM specific products to be deployed there as well. This will also be a topic covered in future courses.

Hope this answers yours questions. Let me know if I can be of further assistance 😄

[Marcelluse]

Hello,
I am hoping to upskill with AI and ML to look at ways to apply that skill in practical terms in the legal tech industry.
What is the best programming to learn for a beginner wanting to enter the AI field or is it necesary to learn a programming language?

[Shaheerairaj]

That's a great question Marcelluse. With the rise of LLMs and how good they are becoming at coding and complex reasoning, it is becoming easier for engineers to code out the solution of whatever project or product they need to build. But as good as they are, for now they are at the end of the day just tools for people to use.

I believe they are at a point where a non-technical person is able to build great demos/PoCs/MVPs for the product they have in mind, but when it comes to more complex jobs in high-end companies, those positions still require good knowledge of coding as they deep dive more into very nuanced use cases.

In short:

• Knowing how to code is becoming less and less important (but not yet irrelevant)
• It is more important to know how to use different AI tools to solve a problem and which tools are better for which use-cases
• There will always be a need for people who know how to code themselves for much more technical roles that require deep expertise and nuanced use-cases
• The landscape for Machine Learning/AI Engineering is becoming more about knowing how to build efficient and scalable systems

Does this help? What are your thoughts?