🔥 AI Roadmap 2024 | Roadmap To Learn AI In 2024 | AI Learning Path for Beginners | Simplilearn

hello everyone and welcome back to our Channel today I've got something really exciting to discuss that is the AI road map for 2024 artificial intelligence has been evolving at an incredible pace and 2024 promises to be a groundbreaking year in the world of AI so let's Dive Right into what we can expect in the coming year and before that if you're one of the aspiring python Enthusiast or a ml Enthusiast that is looking for online training and graduating from the best universities or a professional who elicits to switch careers in Ai and ml by learning from the experts then try giving a short to Simply learns postgraduate program in Ai and machine learning in collaboration with per University and IBM the course link is mentioned in the description box below that will navigate you to the course page where you can find a complete overiew of the program being offered and if you like these videos then like share And subscribe to our Channel and now starting with who is an AI professional so an AI professional is an expert in the field of artificial intelligence possessing the Knowledge and Skills to design develop and Implement AI solutions they play a crucial role in various Industries leveraging AI Technologies to solve complex problems and enhance decision-making process they are in high demand due to the increasing use of AI in Industries like healthcare Finance sence and technology and now we will explore the various career paths for an AI professional starting with AI research scientist then we have machine learning engineer data scientist NLP engineer computer vision engineer AI ethics and bias analyst AI product manager AI software developer so these are the career paths for an AI professional now we'll move to the roles and responsibilities for each profession so starting with AI research s scientist so the roles and responsibilities are conduct research to advance Ai and machine learning Technologies then we have developed and Implement Noel algorithms and models and another work is integrate AI into products and services and then publish research findings in conferences and journals then stay updated with the latest developments in AI research so these are the roles and responsibilities for AI research scientist now moving on to the next role that was machine learning engineer and now we'll see its tools and responsibilities that is design and build machine learning models and systems collect and pre-process data for model training tune and optimize algorithms for performance deploy models into production environments and monitor and maintain machine learning systems and now moving on to the next role that is data scientist data scientist roles and responsibilities are as follows the analyze large data set to extract many meaningful insights they develop predictive models and data driven Solutions and they create data visualizations and reports for decision making they collaborate with business teams to identify data driven opportunities they also ensure that data privacy and security compliance keep in handy and now moving on to the next Ro that is natural language processing engineer NLP engineer and their roles and responsibilities are they develop NLP models for language and understanding and generation they pre-process and clean Text data for NLP task they work on sentiment analysis chat boards and language translation they collaborate with linguist and domain experts for specialized NLP projects they stay current with NLP research and Technologies and now moving on to the next Ro that is computer vision engineer so the computer vision engineer build computer vision algorithms for image and video analysis they develop object detection image recognition and facial recognition systems they collaborate with Hardware teams for embedded Vision applications they Implement image and video processing techniques they also stay updated on computer vision advancements so these were the roles and responsibilities for computer vision engineer now moving on to the next role that is AI ethics and bias analyst so starting with their roles and responsibilities the first one is assess and mitigate ethical concerns and biases in AI systems develop and implement fairness and bias detection algorithms and show AI systems that comply with ethical guidelines and regulations they educate teams on ethical AI practices and they conduct Audits and assessments of AI models now moving on to the next role that is AI product manager now moving on to the next role that is AI product manager and now we'll see their roles and responsibilities so they Define the AI product strategy and road map they collaborate with stakeholders to GA requirements and they prioritize features and functionalities for AI products they also manage the development and deployment for AI solutions they also monitor product performance and gather user feedback now moving on to the next tole that is AI software developer so AI software developer develop software applications that incorporate AI capabilities they integrate Ai apis and libraries into existing software systems they write code for AI model deployment and inference they collaborate with AI researchers and Engineers on software projects they debug and maintain AI related code and applications these roles and responsibilities can vary depending on the specific industry I'm talking about all the roles they can vary on specific industry organization and the level of expertise required so AI professionals may also specialize further Within These roles based on their areas of interest and expertise and now I have an insight for you guys that is if you are one of the inspiring AI or ml enthusiasts looking for online training or graduating from the best universities then I have the short of Simply learn skelic a& ml boot camp and you can find the boot camp details with the link and you will navigate to The Boot Camp Page now moving to the career road map for AI professional so these are the steps you need to follow to become an AI professional so the step one is mastering the fundamentals then we have introduction to machine learning then the third step is deling deeper into deep learning then we have practical experience with data then introduction to natural language processing and then we have immersion in computer vision and then introduction to reinforcement learning and then engage in Practical projects and continuous learning so starting with the step one so what should you do to be a AI professional so the first step is mastering the fundamentals so begin your AI journey by establishing a strong foundation in Core Concepts get acquired with essential mathematical principles such as algebra calculus and probability additionally take the time to become proficient in a beginner friendly programming language like python which is widely utilized in the field of AI explore various online tutorials and education resources to grasp the fundamental aspects of Python Programming now moving to step two that is Introduction to machine learning so machine learning constitutes a pivotal component of AI start by comprehending the concepts of supervised and unsupervised learning supervised learning involves the training of models using label data while unsupervised learning revolves around the identification of patterns within unlabeled data familiarize yourself with popular machine learning algorithms like linear regression and decision trees prioritize gaining an intuitive understanding of these algorithms before delving into their mathematical incases and now moving on to the step three that is delving deeper into deep learning deep learning has witnessed significant Acclaim in recent years commence your deep Learning Journey by acquiring knowledge about neural networks the fundamental building blocks of deep learning gain insight into the structure of neural networks the data learning mechanisms and their predictive capabilities explore crucial Concepts like activation functions back propagation and gradient descent so this was about the step three now we'll move to the step four that is practical experience with data so data is the lifeblood of AI applications learn how to efficiently manipulate and pre-process data discover techniques for data cleaning addressing missing values and transforming data into formats suitable for model training put your skills into practice by working with libraries like pandas and numpy which simplify data manipulation task now moving on to the step five that is Introduction to natural language processing natural language processing is focused on enabling machines to comprehend human language begin by building a foundation in in essential NLP Concepts such as tokenization the division of text into words or sentences stemming reducing words to their root forms and part of speech tagging identifying grammatical elements gain practical experience by experimenting with NLP libraries like nltk now moving on to the step six that is immersion in computer vision so computer vision involves the teaching of machines to interpret visual information Begin by exploring image processing techniques including fil Ing and feature extraction learn about widely used computer vision algorithms such as object detection and image classification creat put your knowledge into action by experimenting with libraries like open CV and tensorflow to implement computer vision applications now moving on to the step seven that is Introduction to reinforcement learning reinforcement learning centers on training agents to make decisions through a process of trial and errow start by understanding Core Concepts such as rewards States and actions familiarize yourself with popular algorithms like Q learning and engage in the environments like open AI gym to practice reinforcement learning then we have the step eight engaging in Practical projects and continuous learning apply your new found knowledge through Hands-On projects begin with small scale projects and progressively take on more complex challenges participate in AI communities and contribute to online forums to collaborate with fellow Learners and gain insights from experienced practitioners stay updated with the latest developments in AI by following AI blogs attending webinars and exploring AI related new sources so in conclusion I want to say that commencing your AI Journey as a no ice may appear daunting but by following this structured road map you can progress systematically and establish a solid foundation in AI Concepts remember to prioritize a deep understanding of the fundamentals engage in Hands-On learning with real world data and undertake projects to reinforce your knowledge Embrace continuous learning and leverage online resources and and communities to enhance your AI skills now moving on to the companies hiring AI professional so Amazon Cap Gemini orle TCS asenta sap IBM cognizant so these are the companies and these are the top most companies that hire AI professionals and now moving on to the average salary for AI professionals so in us a bner AI professional can earn up to $882,000 to $128,000 and then experienced professional can earn from $99,000 to $200,000 and if we talk about India a beginner can earn from 5 lakhs to 12 lakhs perom and if we talk about the experienced professional they can earn from 7 lakhs to 20 lakhs per anom so these data are just the stats from the glass door and they can vary on the different states and the countries so well there you have it folks and before ending I want to take your a minute to hear from our Learners who have experienced massive success in their careers by opting out the boot camp and the postgraduate program in Ai and machine learning you need to keep updating your skills the course material was comprehensive and the faculty was extremely experienced uh The Faculty was able to adjust their teaching style in order to cater to the overall skill set of the class in the rapidly evolving world of technology it's important to keep upskilling for every working professional stay relevant continue learning and if you like this session then like share and subscribe if you have any questions then you can drop them in the comment section below thanks for watching and stay tuned for more from Simply learn staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs and cut Cutting Edge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to 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Channel: Simplilearn

Views: 8,038

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Id: Pg8DFa7i5SQ

Length: 13min 40sec (820 seconds)

Published: Sat Sep 16 2023