if you want to learn AI from scratch then this video is exactly what you need I will give you a complete step-by-step road map from learning the basics to monetizing new or new skills now first we need to decide on the reason and the end goal ask yourself why do I want to learn AI is it purely for career purposes or have you tried generative AI tools and want to know more about them kind of like a hobby because the answer to this question will partially determine what you will learn and how you will learn for example if I was to learn AI to find a job later I would need to take a longer more difficult approach I would need to learn all the basics learn how to code learn data science and so much more the best part about this approach is that it gives access to so many career options for example here's a job offer for a junior data scientist that pays $1 100 to $120,000 a year or here's another one with a salary between $40 and $170,000 there are over 10,000 job offers in LinkedIn with a salary over $120,000 so yeah I would say learn AI for career purposes could be a great decision on your part however if I was just enthusiastic about AI I would lean more towards practical Solutions mastering existing tools and models this in turn opens doors to different types of skill monetizations such as freelancing selling courses and so on another question you need to ask yourself at this stage is code or no code the no code approach is easier but it is far more limiting for example let's say you want to generate an image if you don't know how to code all you can do is use services like M Journey or dolly or opt for platforms like run diffusion give you a bit more control over the results and allow you to more precisely tweak the model however in this case you're practically limiting yourself to the services and what they allow you to do so if you decide that you can train the model a bit better for your specific task you might not be able to do so the code focused approach on the other hand gives you far more flexibility both in terms of the models you can use and the things you can do with those models for example let's say you want to create deep fake videos a no code way of doing things would be scouring the web for available tools paying for subscriptions having almost no control over the outcome and hoping that the results would be somewhat decent but if you know how to code and ready for a challenge you will be able to deploy one of the available deep fake models right on your computer tweak every parameter to your liking give the model access to as much data as you want and as a result get a Flawless deep fake and by the way here's a list of great deep fake models that you can try again you have to have at least some coding skills and be ready to spend hours tweaking everything and I'm sitting here talking about a career in Ai and I didn't even mention how you can learn all that for this I recommend artificial intelligence engineer master's program by simply learn this program is a collaboration of Simply learn and IBM and during the program students will get access to hackathons Master Class es and ask me anything sessions by IBM Additionally the program gives access to 25 projects and integrated Labs with Hands-On learning basically you won't be studying the theory alone you will also practice a lot just look at the list of tools and programs covered there's everything from python to Chad gbt the program starts light with a few introductory lessons then Dives deep into how it all works and python so along with learning all about AI you will also learn how to code when when there's a lot of data science related courses at the beginning do you know why because AI is all about data and data science then there are courses about machine learning computer vision reinforcement learning and so much more after completing the program students get a certificate that will make it clear for all the recruiters that you are on the edge of the latest knowledge just look at all the jobs this certificate makes possible AI engineer data scientist machine learning engineer this program is a serious Ace that by the way has been rated at world's number one online boot camp the next cohort is starting soon with limited seats available so click the link in the description to supercharge your brains okay but let's say you recently watched Mr Robot and now want to learn coding good then start with python python is the go-to language for anyone trying to learn AI of this I'm certain firstly python is easy to learn its syntax is straightforward and readable especially when compared to other programming languages this helps beginners quickly get a grasp of programming cont Concepts without getting bugged down by complicated structures when I tried to learn C this was really hard another reason to go python is a strong Library support libraries like tensorflow PCH and pyit learn are essential in AI development they basically give freebuild functions and Frameworks that help simplify complex AI tasks allowing you to focus more on solving problems rather than building tools from scratch python also has a large and active Community which means there are plenty of resources available such as tutorials documentation and forums and as an IC and the cake your knowledge of python can be used not only in the AI field python integrates well with other languages and tools so whether you're working on web applications data analysis or scientific Computing python is equally capable of everything so once You Learn Python you can practically do anything but python alone won't cut it to learn AI effectively you need to reverse engineer existing models and tools there is no better place to find them than GitHub many projects models and data sets are shared in GitHub by the People for People now what is that I said learn GitHub well despite looking like a regular website GitHub is far more complicated and takes some time to learn how to properly use it hey if you manage to do it you will literally get access to the knowledge of coders from all over the world models data sets or even complete projects for you to learn from GitHub has it all and as a bonus your GitHub is actually your programming portfolio so when you start applying for AI jobs you you will be able to actually prove that you know your stuff I can stress how important reverse engineering is in learn AI again we're talking about a Cod and approach now with a no code approach you don't have to do any reverse engineering reverse engineering is the simplest and quickest way to learn how AI Works to look inside that black box that takes an input and gives an answer so go ahead and download a couple projects that seem interesting to you and align with your skill level slightly exceeding it then start going through the code and see what each line does I'm telling you after you reverse engineer a couple such projects you will feel far more comfortable with AI and your own skill you will be able to break these projects into individual pieces and combine them into something new something that works just for you or if you want to balance between the code and no code I would advise you to try and deploy couple different models on your computer not all models require deep programming skills for many open source projects you only need the most basic knowledge of python and a couple librar if you decide to go this way I recommend you choose models that have some sort of a visual interface so that you could operate them more easily I'd say that this way of doing things can be a next step for people who already feel confident with web-based AI models but don't feel ready for programming challenges when learn AI it's crucial to not limit yourself to one specific thing at least in the beginning when you're just starting you need to try as many things as possible this is the only way to find out what you're really interested in that works for you if you feel feel that image generation is something you want to look deeper into maybe you should also check out the video generation models or if you are into language processing then maybe you should also take a look at data science there are so many directions you can choose and that's why I advise you to look into different options earlier once you complete a couple introductory courses and try new things yourself it will be the time to pick your option to choose the direction you want to grow can be language processing data science or even developing AI models it's all up to you making this choice is a crucial step in everyone's AI Journey once you do pick a clear Direction It all becomes slightly easier just find a course and complete it then another one then another one then you reverse engineer as many existing projects as you can and try to come up with your own project trying to create it from scratch then you refine it get rid of mistakes optimize the algorithms and debug debug debug though this is only if you decide to choose a coding approach if you pick a simpler way without coding all those previous steps with completing education courses are practically irrelevant to you you know what you like and you just practice it for example if you're into image generation you just open up M Journey some documentation for it and start trying things out trying different prompts different parameters different keywords and so on but try to do it at least systematically create a file where you would note all the prompts you try and how each parameter affects the result then once you feel like you can do everything with M Journey go on and try to deploy a stable diffusion model on your computer rinse and repeat try out different things different prompts and different combinations of them training the model on your data find the best data type that works for you and so on and the last step would be to start monetizing your new skills if you opt for a no code approach good solution for you would be to create an education course and try selling it or you can also go freelance and offer your services to people or you can train your model and try to make it publicly available for people to use kind of like run diffusion from earlier or you can just start selling from and as I mentioned before a code based approach opens far more doors you can straight up start applying for AI related jobs at this point you already have completed many courses you have a great GitHub portfolio and a couple projects under your belt you know how to reverse Engineers someone else's work and you can work with different models yourself the chances of getting a job are pretty high in this case and salaries that go over $100,000 are also very much possible learning AI isn't to walk in the park it's a pretty complicated process for some it might take only a couple months to get up to speed but if you have limited time and resources I'd say year would be enough to go from zero to competent AI engineer but if you are more interested in simple ways of monetizing your existent AI skills we recently made a video with the best AI side hustles be sure to check it out next thanks for watching and see you there