There have been times when I've been selected as a group lead to deliver a presentation on certain core concepts/technologies take Machine learning, cloud computing as an example. Never failed to nail them but I always end up with the feeling that it could have been better, I should have involved the audience, I should have taken less time, I should have presented an example for better understanding and I should have done this and that. Now, I am getting good and I've dealt with most of the issues that I thought I had.

In this write-up, I'd open up my todos/advice before delivering a presentation or a lecture in front of an audience consisting of more than 40 people. I'd also like to ask the readers to suggest me their todos/advice in the comments.
First things first there are several things that are compulsory/crucial regardless of the nature of the talk/lecture/presentation.

0 - Dress Up! (lightning should strike every time you move).
1 - Don't do "hmmmmmmmm", "Ahhhhhhhhhhh", "Yeaaaaaahhhh".
2 - For some reason, I've noticed when I use the word, "maybe", people kind of lose interest? This word doesn't have that confidence/vibe. For some people, they want to hear facts, they are not there to listen to a guy who "maybe" knows what he is talking about.
3 - Your voice really matters. I've called my friend a few times to learn Calculus from him, he's good at math. I tend to lose interest when he's talking (same boring tone). However, while in University, I met this another dude who had a really natural mature masculine voice and I never lost focus, more likely, he never lets the audience lose focus.
4 - Examples, experiences, stories. Please share them!

Let's get to the real things, the technicals. The things that you as an engineer should do or follow.

1 - Clarify the fundamentals by providing easy examples.
2 - Don't just move slides, do something. For Example, if you're talking about machine learning, run a demonstration right in front of the audience - but always find a logical reason, in case it doesn't work(these things happen, you might have run your code a million times but in front of a large audience, the code just doesn't work sometimes). Idk, happened to me. So, Always have a reason like, "internet's slow in this place, the code requires a file to be downloaded from this and that and so on." OR, "this isn't my computer, this computer needs to get updated or the code isn't tested". Trust me, you'll know the reason. The important thing is not to be thrown off by the mistakes. Stand your ground, people make mistakes, don't worry, don't try to just move ahead. Tell the people what the issue is and they will understand. For the general public, only do demonstrations that you're 100% sure will work.
3 - Tell a story. Example, "People! You can really earn a lot of money from machine learning with python doing freelance work. I had a client from the UK, she wanted to detect a certain object from the live camera feed, I trained Yolo with a custom dataset and implemented all the things she needed. She was really impressed and gave me $150 tip."
4 - Know how to wind up.
5 - Practice it, a night before the actual presentation/lecture.

These are the things that I can think of right now, I might be updating this article after criticism. Please take some time to improve it, suggest better things, appreciate it, share it, comment on it, ask for anything. I hope that it helps you.