Okay.
You almost made it.
This is the last lecture of the course, and I just want to say thank you.
Thank you for being here, for sticking with it and for investing time in your learning.
I hope the course helped you understand the topic better, give you some new ideas, and maybe even
inspired you to keep learning.
You wanna get your certificate?
Make sure that every lecture is marked as completed.
Go to each section and check that every lecture has a checkbox.
You can also check each individual section to identify if there are any missing lectures.
For example, in this section there's one lecture missing, but in the next one there are 18 lessons
that are missing and which still require a checkbox apply.
Once everything is done, your certificate will appear on top of the course page right about there.
I also encourage you to share your certificate on LinkedIn.
It's a great way to celebrate your learning, connect with others, and maybe even start a conversation
about how AI is changing the way we work, for better or worse.
I'd love to see your posts and hear your thoughts.
So what's next for you?
Well, this is a fast changing industry right now.
There's always more to learn, and for me personally, that's exciting.
Whether you're a developer, a tester, or, you know, just starting out, keep growing.
This course was just the beginning, and I don't want to pretend we have covered everything there is
to learn.
So here are some ideas for what you can explore next.
First of all, explore more AI coding tools.
There are many other tools out there that I haven't covered in this course, like GitHub, copilot,
Replit, and even some experimental agents.
Each has its own strengths and ways of working.
Apart from this, specialize in one tool.
Choose one that fits your workflow or your goals and get really good at it.
Learn its shortcuts, its limits, all its functionalities and how to think with it.
How to work together and apart from this, get better at prompt engineering.
Get better just a bit every day.
Practice how you can give better instructions to the AI.
The more precise and clear you are, the better the result you will get and also the faster it will
be.
Whether you're writing code, generating tests, or just building entire apps, you will benefit from
this long term.
Also, go deeper with coding.
Start a small side projects or build something useful at work.
Don't just use the AI to build.
Use it to learn.
As you go.
Talk to the AI.
Ask it to explain what it is doing.
Refine your thinking.
You want to turn coding into a conversation because that's where real learning happens.
And last but not least, level up your debugging skills.
AI tools can generate a lot of code quickly, but not always correctly.
Knowing how to debug and fix the code is becoming one of the most valuable skills.
So in the future, the most important skills will be the ability to understand, debug and guide AI.
So don't be afraid to take on challenges.
Do what is hard.
Do what others are afraid to do because that's where the real growth happens.
Also, check the resources folder for this lecture.
It's packed with ideas on what you could learn next.
Right after this lecture, you will be asked again to leave a review for the course you'll be doing
me and other learners a huge favor.
If you could take just 1 or 2 minutes to write one.
Let others know if this course was helpful or not and what you got out of it.
If you would like to connect, feel free to send me a message or a connection request on LinkedIn.
I enjoy hearing what people are working on, and I'm always happy to answer questions or chat about
what is happening in IT and tech.
And that's it.
Thank you for being part of this course.
I really hope to see you in another one soon.
And until then, keep learning, keep building, and stay curious.