Unlocking the Path to AI Mastery: A Comprehensive Guide to Embark on Your Journey as a Machine Learning Developer
It is the year 2023, and AI and Machine Learning have once again become popular buzzwords. It seems like every second, a new AI tool is developed; it’s said that AI is taking over the world or should I say: “AI is eating the world”. AI/Machine Learning developers, who build these AI tools, are making a lot of money, and as a result, everyone wants to become one.
Whether you’re a beginner or a novice who knows nothing about machine learning development, or an experienced coder, this article will serve as a comprehensive guide to help you become a highly sought-after Machine Learning Developer.
Read on 😎
Learning machine learning or AI can be a daunting task, given its vastness. Without proper guidance, one might not know where to begin. Fortunately, someone like me, with prior experience, can offer a helpful guide to ease the process. To make it easier to follow, I will number my guide.
Start here by reading the article. below; you can take three (3) days to comfortably go through it, It will give you a very solid foundation on everything AI/Machine Learning:
Then take two (2) weeks to comfortably read this really amazing medium article which has been put like a course called “Machine Learning for Humans” by Vishal Maini; it will give you a very good breakdown of all the technical aspects and terms that are used in Machine Learning development/engineering; terms like Deep Learning, Support Vector Machine (SVM), Recurrent Neural Networks (RNN) and all the fancy jargons that we see all over anything AI/Machine Learning.
The link to the article is below:Now at this point, you would have gained your foundational knowledge in AI / Machine Learning and you are ready to pick a technical path to become a Machine Learning Developer / Engineer.
Path 1: The Raw Machine Learning Engineer/Data Scientist Route
This path involves taking a course on Udemy, which is highly recommended. You will learn how to work with data, use algorithms, models, and various machine learning frameworks to build projects under Prediction, Computer Vision, NLP, and Deep Learning.
This is the course:
Path 2: The IBM + Watson AI Route
IBM provides a free course under their Digital Nation Africa program for those interested in this path. You will utilize the IBM tools and frameworks to build projects that are easier to create than those in Path 1.
Path 3: The AWS + ML Path
With Amazon Web Services and its various AI modules, you can build projects that are even easier than you might expect. However, you need to understand how to use AWS, which can be a bit challenging. AWS Engineers are some of the most highly paid software professionals in the world. Fortunately, AWS offers many free learning resources, including a foundation course on Udacity.
Path 4: Microsoft Azure + ML
While Microsoft Azure is not as popular as other options, there are still many free courses available for learning. However, their market share isn’t too big when it comes to AI and Machine Learning tools. Fortunately, that is changing as Microsoft owns one of the biggest AI platforms now: Chat-GPT
Path 5: GoogleAI
Google has a free learning program on everything AI that you can take for free right now with certifications; it's very practical and hands-on and I highly recommend!! You can start by clicking on the link below:
Heyyyy, so I hope this has been crazy helpful and educative in getting you started on the journey to becoming the ultimate Machine Learning Developer. But hey, don’t just stop here. Go out there and explore other paths that may tickle your fancy but I didn’t mention. Don’t be basic, be bold and blaze your own trail. Peace out 😎 ✌🏾
You can connect with me on:
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