The 2024 AI (Artificial Intelligence) Developer RoadMap
An illustrated guide to becoming a AI Engineer in 2024 with links to relevant courses
Hello guys, if you want to become an AI Engineer in 204 or want to learn Artificial Intelligence, Generative AI, and Prompt Engineering then you are thinking on right direction.
More and more companies are asking their workforce to learn Generative AI and it’s only going to increase. AI Integration will be next big thing when you have to add AI capabilities to existing application to enhance them and that’s why learning AI skills in 2024 is a great idea.
But question comes how? Well, don’t worry, I will tell you. In the past, I have shared best AI courses and best courses to learn ChatGPT, one of the most popular Generative AI example and LLM and in this article I will teach you step by step what skills you need to master AI development and integration.
If you haven’t heard about AI or Artificial Intelligence then let me give you a brief overview. You can consider artificial intelligence as the way to make computers mimic the human brain to learn from data and make decisions based on this data.
Artificial intelligence engineers are in-demand in many companies, and most of them are moving to use this field to improve their products and user experience. This article will help you learn the steps you need to become an artificial intelligence engineer.
Though, if you are new to AI and looking for a course which not only teach you fundamentals but also show you how to create things, I mean project based course then you can start with Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT by Kirill Eremenko and his SuperDataScience team on Udemy, or AI For Everyone by Andrew Ng on Coursera, both are a great course to learn AI from scratch.
The 2024 AI Engineer RoadMap
Here are key skills you need to learn to master Artificial Intelligence in 2024, it includes programming language as well as things like Machine Learning and Deep Learning which forms the basis of how AI works.
Here is the comprehensive AI Developer RoadMap I have created which include all the skills you need to succeed to become an AI Expert in 2024.
This is very comprehensive and it will take some time before you can master all the skills and many cases you don’t need to learn all, so I have also listed the most essential skills after this roadmap with resources which anyone can learn to become an AI Developer in 2024
1. Learn Python Programming Language
The first thing you have to learn to become an AI developer is to learn programming languages. There are a lot of them, and every company can ask you to have the skills in one or more languages, but python is the most used one among all other languages. It’s also one of the most popular programming language for AI development and integration.
1.1. Python for Everybody
This is the most known course for learning python language on the internet. It is created by Michigan University and offered through Coursera and will help you be an intermediate user of the python language in just a few months.
You will start learning the basics of this language first, then move to learn the data structure. Later, you will use python to access the web, interact with the database, and more. More than 1.6 million people have already joined this program to learn Python.
Here is the link to join this course — Python for Everybody
And, if you need more choices, you can also see this list of best Python courses which contains best online courses to learn Python in 2024
2. Learn Statistics
Most people new to the artificial intelligence field don’t understand that statistics are the critical thing that makes artificial intelligence work. You can make an AI algorithm without understanding the statistics or improving it.
The artificial intelligence will search for the patterns in the data and use them to recognize things like cats and dogs in the images.
2.1. Introduction to Statistics
This beginner course for learning statistics will help you understand the basic terms in this field. You will start learning the descriptive statistics and exploring the data and sampling. Then move to learn probability, which is essential in statistics to understand since you will use it a lot in your journey.
Learn different distributions and regression, which is very important, and much other statistics-related information for beginners.
Here is the link to join this course — Introduction to Statistics
3. Learn Mathematics
You can’t be an artificial intelligence engineer if you don’t learn math. It is also essential if you are trying to learn statistics. Artificial intelligence doesn’t require you to become a math expert or have a Ph.D. level in this field, but at least some of the basics of this science are enough, and if you want to learn more about math, that will be much better.
3.1. Mathematics for Machine Learning
The good thing about this specialization is that it will teach you what you need to understand in math if you learn machine learning, a subset of the artificial intelligence field.
It is for beginners entirely and will probably take two months to complete. You will learn about linear algebra, multivariate calculus, and the principal components analysis. More than 62K people have already joined this course.
Here is the link to join this course — Mathematics for Machine Learning
4. Learn Machine Learning
Machine learning is considered a subset of artificial intelligence and science that makes machines learn from the data you feed to them without programming it to do that thing. It can be used to recognize things in pictures, predict diseases, filter the messages in the email, detect fraud transactions in the bank, and more.
4.1. Machine Learning
This course is created by Andrew Ng and earlier offered by Stanford University is the most known one on the internet for learning machine learning. You will start this course by understanding this science and its different types.
Then moving to the experimental phase and learning the linear regression, logistic regression, regularization, the neural network that mimics the brain function to learn from data, support vector machine (SVM), and more.
Here is the link to join this course — Machine Learning
5. Learn Deep Learning
We said before that machine learning is a type of artificial intelligence, and now you can consider deep learning as a subset or type of machine learning. Machine learning uses some algorithms for making the model. Deep learning will use the artificial neural network that mimics the human brain to solve the issue of learning from data and making predictions.
5.1. Machine Learning, Data Science and Generative AI with Python
A complete course for learning machine learning, deep learning, and even data science. You will start as a beginner by understanding some of the statistics concepts and then move to learn machine learning with python.
You will also learn to make a recommendation system and deal with real-world data. Finally, learn about deep learning and make neural networks that learn from data.
Here is the link to join this course — Machine Learning, Data Science and Generative AI with Python
6. Learn Generative AI
Learning Generative AI is another essential component of an AI developer’s roadmap for several compelling reasons. Generative AI techniques, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), empower developers to create models that generate new, realistic data based on patterns learned from existing datasets.
This capability is invaluable across various domains, including image and text generation, style transfer, and even drug discovery. Understanding Generative AI not only enhances an AI developer’s toolkit but also fosters creativity and innovation.
Additionally, as the technology advances, generative models are playing an increasingly pivotal role in applications like content creation, simulation, and data augmentation.
By mastering Generative AI, developers gain the ability to design intelligent systems that not only analyze existing data but also generate novel and meaningful content, pushing the boundaries of what AI can achieve in both research and practical applications
6.1 Generative AI course on Coursera
This is a great course to start with Gen AI in 2024. With financial aid available and already boasting an impressive enrollment of 270,008 learners, this course, instructed by Google Cloud Training, is part of Coursera Plus and has garnered a rating of 4.6 based on 3,721 reviews.
Designed for beginners with no prior experience required, the course offers flexibility with a one-hour completion time and a self-paced learning approach. Learners will gain insight into Generative AI, understanding its definition, functionality, model types, and applications.
Additionally, the course provides details on shareable certificates and assessments, with a focus on preparing learners to develop their own Gen AI applications using Google Tools.
Here is the link to join this course — Generative AI course on Coursera
If you need an alternative course then Andrew Ng, founder of Coursera and creator of AI for EveryOne specialization also has a course called “Generative AI for Everyone” which is another great resource to learn Generative AI.
By the way, instead of joining these courses and specialization individually, you can also join the Coursera Plus, a subscription plan from Coursera which gives you unlimited access to their most popular courses, specialization, professional certificate, and guided projects.
7. Learn Prompt Engineering
In 2024, Prompt engineering is essential for AI developers as it involves crafting effective instructions or prompts that guide AI models in generating accurate and relevant outputs.
By mastering prompt engineering, developers can significantly enhance the performance and capabilities of AI systems across various applications, including natural language processing, image recognition, and recommendation systems.
Understanding how to formulate prompts that elicit desired responses from AI models is crucial for optimizing their functionality and ensuring they deliver meaningful results.
As the importance of AI in various industries grows, proficiency in prompt engineering will become increasingly valuable for developers looking to advance their careers in AI development.
To gain expertise in prompt engineering and kickstart your journey as an AI developer, I recommend enrolling in the “The Complete Prompt Engineering for AI Bootcamp (2024)” course offered by Udemy.
This comprehensive course covers essential concepts and techniques in prompt engineering, equipping learners with the skills and knowledge needed to excel in the rapidly evolving field of AI development.
8. Learn ChatGPT
In 2024, as the demand for artificial intelligence (AI) solutions continues to rise, mastering ChatGPT is becoming increasingly important for AI developers.
ChatGPT, based on cutting-edge language generation models, enables developers to create sophisticated conversational AI systems that can understand and respond to human language with remarkable accuracy and fluency.
By learning ChatGPT, developers gain access to powerful tools for building chatbots, virtual assistants, customer support systems, and more, revolutionizing the way businesses interact with customers and users.
With its ability to understand context, generate natural-sounding responses, and adapt to diverse conversational styles, ChatGPT opens up new possibilities for AI-driven communication and interaction.
As businesses across industries increasingly rely on AI-powered conversational interfaces to engage with customers and streamline operations, proficiency in ChatGPT becomes a valuable asset for AI developers seeking to stay at the forefront of innovation.
To acquire expertise in ChatGPT and harness its potential in AI development, I recommend enrolling in the “ChatGPT Complete Guide: Learn Midjourney, ChatGPT 4 & More” course offered by Udemy.
This comprehensive course provides hands-on training in leveraging ChatGPT to create intelligent chatbots and virtual assistants, empowering learners to build impactful AI solutions that drive business success.
Conclusion
That’s all about the 2024 AI Developer RoadMap. In conclusion, the AI developer roadmap for 2024 provides a clear path for aspiring professionals. From mastering programming and core AI concepts to staying updated on ethical considerations, the roadmap is a guide for success. As we enter 2024, the demand for AI skills is higher than ever.
By following this roadmap, developers can navigate the evolving AI landscape, contribute to meaningful projects, and stay adaptable in a dynamic field. It’s not just a roadmap; it’s an essential tool for those looking to thrive in the world of artificial intelligence.
Once again Thanks for reading! I have explained the steps you need to follow to be an artificial intelligence engineer. Still, you maybe need to have more skills than these practical skills like communication, problem-solving, work in a team to have a position in this field.
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Thanks for reading this article so far. If you like this AI Developer roadmap then please share the word and share with your friends on social media. I appreciate your kind support.
P. S. — If you want to learn Machine Learning and Deep Learning before AI then you can also checkout Machine Learning A-Z: Hands-On Python & R In Data Science course on Udemy. It’s one of my favorite course to start with Machine Learning and you will definitely like it. If you need more choices, see these free Machine Learning courses as well
