Summarizing learnings from “How to get into AI”
An AI Beginner friendly post. This post summarizes key learnings from “How to get into AI”, session-1 on Maven where Noelle led the session and shared wonderful insights 🔹 Where to start? Think “You + AI”—AI is here to enhance what you already do. Whether you’re in tech, marketing, healthcare, or any other field, AI can help you work better, faster, and smarter. 🔹 Learn by building – Don’t just read, experiment! Solution Accelerators on GitHub can give you a head start. These pre-built frameworks help you quickly develop AI solutions for real-world problems. Great beginner-friendly projects: ✔ Call Support AI ✔ Movie Review Sentiment Analysis You can clone the open-source code, create your own workspace, and start 💡 A smart way to learn AI (from Noelle’s approach): 1️⃣ Who am I? → What skills do I have, and how can AI enhance them? 2️⃣ Which AI tech fits me? → Focus on the right tools instead of trying to learn everything. 3️⃣ The Three Lenses: Academic Lens – Start by picking one university to follow. Policy Lens – Follow an expert in AI policy or regulation. Product & Market Lens – Pick an AI product (AWS, Google Cloud, Azure), analyze its go-to-market strategy, build a project on GitHub, reverse-engineer its requirements, and showcase your skills on LinkedIn! 4️⃣ Share as You Learn – Learning becomes even more valuable when it sparks discussions and insights from others. And don’t forget to take the I❤️AI Challenge if you haven’t already! #AHA #AIBeginner #NeverTooLateToLearn