A 5-step roadmap for today\u2019s landscape<\/h4>\n
Today, more people than ever are trying to learn AI. Although there are countless free learning resources online, navigating this rapidly evolving landscape can be overwhelming (especially as a beginner). In this article, I discuss how I\u2019d approach learning AI, given what I know now and the tools available today.<\/p>\n Given the wide range of backgrounds interested in AI these days, I\u2019ve tried to make this guide widely accessible. However, no guide can help everyone. Here are a few specific groups I have in\u00a0mind.<\/p>\n About me<\/em><\/strong>\u200a\u2014\u200aI\u2019ve worked in AI for the past 6 years. I started as an AI researcher while getting my PhD, then eventually worked as a data scientist at Toyota. Although I still have a lot to learn, the approach below covers (what I think are) the essentials based on my personal experience.<\/p>\n The guiding principle of this framework is to learn by doing<\/strong>. Each step outlines a clear and specific objective through which completion will naturally develop key skills. In other words, rather than reviewing a list of concepts and courses, each step is a task<\/strong> designed to force me to learn essential skills by completing it.<\/p>\n Here\u2019s an overview of the 5-step approach. Each step builds upon the ones before\u00a0it.<\/p>\n If starting from zero, the first thing I would do is familiarize myself with modern AI tools i.e. ChatGPT, Claude, and the like. This is important because frequently using these models will give me a practical understanding of what they can and can\u2019t do <\/strong>and <\/strong>develop my ability to use them effectively through prompting<\/strong>.<\/p>\n On a more meta level, these chat interfaces are incredible tools for learning AI (or anything else, really). I\u2019d use it to explain confusing buzzwords and technical concepts (e.g. LLM, tokens, API, RAG) and be sure to ask follow-up questions<\/strong> until I have a solid understanding of each idea. For those that don\u2019t click, I\u2019d seek alternative resources using Google search and\u00a0YouTube.<\/p>\n Although I could go far with today\u2019s no-code AI tools, they are fundamentally limited. Namely, these tools can\u2019t be easily used to build custom solutions<\/strong> or process information in bulk. That\u2019s why the next thing I would do is install Python on my computer.<\/p>\n Python is the industry standard programming language for AI development<\/strong>. To get it installed, I\u2019d ask ChatGPT for step-by-step instructions. If I get stuck, I\u2019d come back to ChatGPT, explain the issue, and ask for additional guidance.<\/p>\n While using ChatGPT (or any other AI assistant) in this way can streamline the process significantly, I would still take the time to understand each step of the process and ask follow-up questions as needed. This is an important habit to develop because it will avoid accumulating technical debt<\/strong>, which I\u2019ll have to pay later when<\/em> something goes\u00a0wrong.<\/p>\n Python QuickStart for People Learning AI<\/a><\/p>\n Once I\u2019ve become comfortable using ChatGPT and installed Python on my machine, my next step would be to build a simple automation using Python. My approach to generating project ideas would be to think of things I consistently use ChatGPT for<\/strong> (e.g. summarizing research articles), then try and automate it with\u00a0Python.<\/p>\n This would require me to become familiar with OpenAI\u2019s Python API. So, I\u2019d start by reading their documentation<\/a> and reviewing the example code there. Once I felt comfortable with the API, I\u2019d start writing Python\u00a0code.<\/p>\n My first step would be to think through the steps of my automation<\/strong>. For example, if summarizing research papers, the steps might\u00a0be:<\/p>\n If I got stuck, I\u2019d turn to ChatGPT for assistance. For instance, if I didn\u2019t know how to read PDFs into Python, I could ask ChatGPT for help. If it spits out code I don\u2019t understand, I\u2019d ask follow-up questions<\/strong> until I understand each\u00a0line.<\/p>\n It (again) is important that I take this approach to coding with ChatGPT because blindly copy-pasting code from it wouldn\u2019t teach me much. It would also accrue unforgiving technical debt<\/strong>. In other words, I\u2019d get short-term gains but would have to pay for them later via technical difficulties and headaches<\/strong>.<\/p>\n Task<\/strong>: Use OpenAI API (or the like) to build a simple automation<\/p>\n Resources<\/strong>: OpenAI API Intro<\/a> | Paper Summarizer Example<\/a><\/p>\n After Step 3 gets easy for me, I\u2019d seek out more sophisticated projects. Rather than simply making ChatGPT-like API calls, I\u2019d build a project that required me to use embedding models or to train a model\u00a0myself<\/strong>.<\/p>\n Potential project ideas would be things\u00a0like:<\/p>\n For example, if I went with the RAG project, I\u2019d first educate myself on RAG<\/a> by watching YouTube videos<\/a> and reading blog<\/a> posts. Then, I\u2019d break down the system\u2019s basic components and the steps to implement it. Finally, I\u2019d start coding the project, using ChatGPT as a co-pilot like Step\u00a03.<\/p>\n 5 AI Projects You Can Build This Weekend (with Python)<\/a><\/p>\n Although I would have learned a lot about the technical side of AI from Steps 3 and 4, this is not sufficient for generating value with it<\/strong>. For that, I\u2019d need to use what I learned to solve real-world problems.<\/p>\n There are two ways to do this. I could, one, solve my own problem, or two, solve someone else\u2019s problem. Since I (hopefully) already did the former way in Steps 3 and 4, here are a few different ways I\u2019d approach the\u00a0latter<\/strong>.<\/p>\n Let\u2019s say I had graduated from college and wasn\u2019t quite confident enough to freelance yet, so that leaves Option 1<\/strong>. I\u2019d start by making a list of people to reach out to. Ideal contacts would be small business owners or professionals working at a small to medium-sized business.<\/p>\n Then, I would craft a message like the one below and send it to everyone on my list via LinkedIn DM or email. If I struggle to find the right wording, I\u2019d use ChatGPT (yet again) to help\u00a0out.<\/p>\n Although AI entails an interdisciplinary collection of technical skills and knowledge, with today\u2019s tools and resources, it\u2019s never been more accessible. Here, I shared the 5-step approach I\u2019d take to learning it\u00a0today.<\/p>\n That said, it\u2019s important to remember that learning (itself) is hard<\/strong>. You will get confused, you will get frustrated, and you will question why you\u2019re putting yourself through this. However, if you are willing to see it through, you will be rewarded with clarity and knowledge, which is an amazing\u00a0gift.<\/p>\n If you have questions or want feedback on project ideas, feel free to share them in the comments\u00a0\ud83d\ude42<\/p>\n I\u2019m hosting a 6-week (live) AI Bootcamp<\/strong> starting Jan 10 (Learn\u00a0more<\/a>)<\/p>\n \ud83d\udc49 Get a 40% discount using promo code\u00a0SAVE40<\/a><\/p>\n How I\u2019d Learn AI in 2025 (If I Knew Nothing)<\/a> was originally published in Towards Data Science<\/a> on Medium, where people are continuing the conversation by highlighting and responding to this story.<\/p>\n<\/div>\n![\"\"](\"https:\/\/i0.wp.com\/cdn-images-1.medium.com\/max\/1024\/1%2AYCBb6_ABdgqFfIO8yG4W-A.png?ssl=1\")
Who is this\u00a0for?<\/strong><\/h3>\n
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My 5-Step\u00a0Approach<\/strong><\/h3>\n
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Step 1: Use ChatGPT (or the\u00a0like)<\/strong><\/h3>\n
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Step 2: Install\u00a0Python<\/strong><\/h3>\n
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Step 3: Build an Automation (Beginner)<\/strong><\/h3>\n
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Step 4: Build an ML Project (Intermediate)<\/strong><\/h3>\n
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Step 5: Build a Real-world Project (Advanced)<\/strong><\/h3>\n
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Subject: Offering Free Help with AI Projects
Hi [Name],
Your work at [Company Name] caught my attention\u2014[insert a specific detail or
observation, e.g., \u201cit\u2019s clear you\u2019re doing innovative things in X\u201d or \u201cyour
focus on Y stood out to me\u201d].
Over the past few months, I\u2019ve been building practical AI projects to develop
my skills. You can see some examples [here](link to portfolio).
Now, I\u2019m looking to apply my learnings to solve real-world problems
by helping businesses like yours\u2014**completely free of charge**. If there\u2019s a
challenge you\u2019ve been looking to automate or improve with AI, I\u2019d be happy to
explore how I can contribute.
Would you be opposed to a short conversation to discuss this?
Best regards,
Shaw<\/pre>\n\n
Final Thoughts<\/strong><\/h3>\n
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