AI Engineer ROADMAP 2024 - How to Become AI Engineer | Step-By-Step Guide

every year major Tech giants like Google Microsoft Apple and Amazon spend billions on AI recent reports showed that 154 billion have been invested in the global AI sector this year that's why the demand for skilled AI Engineers is higher than ever moreover a forecast showed that the AI Market will reach almost $2 trillion by 2030 that's why if you want to build a carer in this exciting field you probably wondering how and where to begin my name is Daniel and for this video I have put together complete AI engineer road map it's a detailed step-by-step guide on how to become a pro in AI engineering and guys if you're wondering about resources that can help you learn more about AI engineering or other it skills I will leave some useful links in the description below feel free to check them out after watching this video okay let's start what is AI engineering here's the thing folks AI engineering is quite a new field many people still don't quite understand what it involves that's why I think before getting to the road map itself it's important to have some things explained so what is AI engineering about well guys in simple words it's all about creating tools systems and methods to make artificial intelligence practical in the real world while many are busy building AI abilities and advancing specific tools AI engineering takes a different approach it looks for and finds answer to some important questions how can AI assist people in reaching their goals what are the current practical limitations of AI system and finally how do we guarantee ethical standards while using artificial intelligence what do AI Engineers do all right what kind of responsibilities do AI Engineers have okay folks an AI engineer uses machine learning algorithms and naral net networks to get insights to understand business's data they make things like ads and language translators using their programming software engineering and data science skills these Engineers create important tools that help companies make big decisions and as an example here is the list of their responsibilities exploring and changing prototypes experimenting with and when necessary train and retrain AI systems working with the robotic team and electronic Engineers using smart computer met me and Technologies building different types of AI applications trying different tools and techniques to process data and finally one of their most common requirement developing and managing machine learning and AI systems that meet the needs of and users so as you can see guys this job is all about using different tools and methods to handle data and create AI systems and yes it looks complex but I think it's super exciting AI engineer ER road map now first of all folks it's important to understand that if you plan to become an AI engineer you must come prepared the good news is having a college or university degree to become an AI engineer isn't a strict requirement yes a degree in computer engineering statistics or data science might be a good basis but today AI is all about practical skills and staying updated and S I see employers value hands-on experience and skills more than formal educ in this field anyway where should you start step one learn some programming so if you're thinking about diving into the world of AI engineering programming is your ticket in learning languages like python are Java C++ is key but don't worry guys you don't have to learn all of them I would personally recommend starting this python it's by far the most popular programming language but it's not just about knowing the syntax you have got to grasp CL classes data structures algorithms and memory management step two get some knowledge of Statistics now when it comes to eii engineering statistical expertise is super important guys matrices vectors and Matrix manipulation are on the menu if you are comfortable with derivatives and integrals you are on the right track also get familiar with gausin distributions means and standard deviations in addition to that you will need some solid understanding of probability that's why make sure you're aware of Concepts like guess Bas gaussian mixture models or shrouded Marco models all right people time to move to the next step step three learn some mass and algorithms guys before we move on I try to make educational content in an entertaining way make it fun instead of boring and in return I just ask to like this video And subscribe to my channel if you enjoy the content I make that's all now it's time to die into the world of algorith GMS I know it might seem a bit scary especially if you have been away from Mass for a while but the thing is understanding things like gradient descent like range quadratic programming and partial differential equation is crucial for AI Engineers sure it requires more mass than for example frontend programming but with practice and patience you can make it step four get to know natural language processing guys natural language processing or NLP is a big part of AI Engineering in NLP we blend Linguistics and computer science to work with text audio and video data to navigate this field it's vital to master libraries like genim and nltk it's also important to understand cool algorithms like word to wack sentiment analysis and summarization and the next step is step five become familiar with narrow networks and deep learning all right now imagine teach teaching computers to handle tasks that are too tricky for us humans and that's where machine learning steps in using naral networks inspired by our brain pattern recognition abilities starting from basic single layer networks you get to the concept of deep learning here data travels through multiple layers unraveling complex patterns these deep neural networks shine in solving intricate challenges like translation speech recognition and image classification okay moving on to step six machine learning algorithms and Frameworks at this step learning how machine learning algorithms operate such as linear regression KNN naive base and support Vector machine can be incredibly helpful fults also diving into deep learning algorithms like convolutional neural networks recurrent neural networks and generative adversarial networks equips you to handle unru structured data using Frameworks like P torch theot tensor flow and coffee you can put these algorithms into action building amazing AI models and last but not least step seven learn about spark and Big Data Technologies as an AI engineer you will dive into massive amounts of data and to handle all this data you need to be familiar with tools like Apache spark this will help you make sense of streaming and real time production data plus there are other big players in the game like Hadoop Cassandra and mongod Deb because folks they are big data tools that will come in handy okay and there is the main technical skills you will need as an AI engineer but guys I will tell you right way technical skills alone won't be enough how to find the job in the engineering okay that's all great but after you learn all the skills how do you grow professionally how do you get to the next level how to be prepared for job interviews well folks I have got a few suggestions for you get relevant experience and there are a few ways you can do that freelance opportunities freelancing can be a good way to start working on your first projects and when choosing a project try to focus on getting new experience rather than money open source projects guys diving into open- Source projects is a fantastic way to get hands on in a real AI environment you can pick into expert code bases see how AI Engineers work they magic and even spot and fix bucks hackaton hackathons are like fast-paced AI competitions you get the short time to build a specific AI projects working with interesting people and learning tons along the way plus you live with a cool project for your portfolio engage with AI engineering community secondly people don't forget to engage with the eii engineering community Community networking in the AI field is the key to Landing great jobs like maybe in any development field Linked In I use LinkedIn all the time to connect with expert in my field and it might be a good idea for you as well engaging with experts posts and comments helps you build professional relationships meetups go to local AI meetups and conferences these events could be goldmines for meeting professionals who can mentor you or just tell you a valuable advice online communities join online AI communities to stay updated and connect with like-minded professionals communities are perfect for learning from others and keeping your skills sharp boost your education finally guys the most important thing as I said earlier nowadays you don't need formal University degree to become an AI engineer there are awesome online certification programs courses and boot camps that can help you become an AI engineer they don't cost a lot of money or take up all your time that's why guys I consistently continue to review certificates courses and boot camps on my Channel all that in order to help you choose the best one that fits you moreover I left useful links in the description with the best AI educational programs that can help you to become an AI engineer feel free to check them out guys all right my fellow developers that all about my AI engineer road map as usually don't forget to like this video And subscribe to my channel thanks for watching until next [Music] time

Channel: Daniel Dan - Self Made Programmer

Views: 10,808

Keywords: ai engineer roadmap, ai engineer roadmap 2024, ai engineering roadmap, ai engineering roadmap 2024, how to become an ai engineer, ai engineer, artificial intelligence roadmap, ai roadmap, artificial intelligence roadmap for beginners, ai roadmap for beginners, how to become artificial intelligence engineer, roadmap to artificial intelligence, ai developer roadmap, ai developer guide

Id: i0WzJ6L2pqE

Length: 10min 42sec (642 seconds)

Published: Sat Nov 25 2023