How can you learn about AI outside of school?

Learning AI can be overwhelming due to the availability of many resources on the internet. I recommend starting with online courses on Udemy, Coursera, Udacity, and LinkedIn Learning. Start by building a portfolio of projects and making them publicly available on Github. I recommend checking out the Kaggle website, which hosts a ton of publicly available datasets and starter code that you can practice with. Start small and build your knowledge gradually. You can start building a simple linear regression model and then move on to advanced topics afterward.

Learning about AI outside of school can be done through various resources and methods. Here are some suggestions: 1. Platforms like Coursera, Udacity, and edX offer numerous courses on AI, machine learning, and related topics. 2. There are many books, also reading publications like research papers, articles, and blogs can also provide valuable insights. 3. Engaging with online communities like Reddit’s r/MachineLearning or joining forums like Stack Overflow can help you connect with other learners and experts in the field. 4. Building AI projects is an excellent way to apply theoretical knowledge and gain practical experience. You can work on projects individually or collaborate with others through platforms like GitHub. 5. YouTube

There are many free courses available for beginners who eager to learn about AI and pursue further education in this area. On platforms like Coursera, these programs come with subtitles in up to 20 languages. Some courses offer the option to purchase a certificate upon completion or to sign up for more advanced levels. I can suggest a few insightful courses: 1. AI for Everyone by DeepLearning - the course is taught by Andrew Ng, DeepLearning founder, Coursera president and co-founder, professor at Stanford University 2. AI For Beginners and 7 other courses on the basics of AI from Microsoft 3. Introduction to Generative AI from Google 4. Understanding Technology from Harvard University 5. AI Fundamentals for Everyone from IBM

There are many routes that you can go to learn bits & pieces of AI, which is a continual process. Many traditional universities are launching informal bootcamps that cover concepts around Data Science, Machine Learning, and Artificial Intelligence. Some help you build a portfolio of works so that when you complete the program, you have a body of work that you can show. There are also many self learning resources out there that you can find via Googling. Additionally, there are inexpensive MOOC (Massive Open Online Courses) programs you can take from organizations such as Coursera.org, Udacity, and edX. I have personally used Coursera to learn AI outside of School. Last, I would follow AI groups and thought leaders on LinkedIn.

I spent about four months bouncing around from one resource to another. I found lots of opinions and ideas but nothing I could practically and systematically add to my arsenal. Then I discovered the Marketing AI Institute (MAII). I read their book - ?? Marketing Artificial Intelligence: AI, Marketing, and the Future of Business by Paul Roetzer and Mike Kaput - and took their certificate course - Piloting AI ??. Their weekly podcasts and newsletters are two of my essentials. They do a monthly webinar, which I don't miss. I also joined MAII's Slack community, which is now 5,000+ strong, and a great way to connect with like-minded people who are on the same journey. The coordinated organization works for me!

??Books are an essential tool to learn about AI ??. Some books include: ?? "Artificial Intelligence: A Modern Approach. 4th Edition" by Stuart Russell and Peter Norvig (published in May 2021), which brings readers up to date in the field of AI. ?? "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell (published in November 2020), which explains some of the most urgent questions concerning AI today.

We are all busy people. Listening to a few podcasts. On the way to school, work, or while doing sport exercises are small doses where you can start.

Books and podcasts provide a multifaceted approach to learning AI, catering to different learning styles. Books like "Artificial Intelligence: A Modern Approach" serve as a cornerstone in AI education, offering a structured and comprehensive understanding. Podcasts, on the other hand, offer a dynamic and conversational way to stay abreast of the fast-paced advancements in AI, making complex topics more digestible and keeping learners engaged with current discussions in the field.

Honestly, just start. Read or watch some of the basics. Just enough to get you started. Then, just start. I recently saw a TED talk of a guy who said that the first 20 hours you actually practice something, is the steepest learning curve you can ever make. So don’t spend 20 hours researching. Because if you do so, when will you actually start practicing? So, find a first project, and start practicing as soon as possible. You’ll learn quickly from it, just see where it gets you.

Put your learning to the test! Kaggle, a data science platform, hosts AI competitions where you can solve real-world problems and learn from others. Start with beginner-friendly datasets and work your way up. Personal projects are also significant: build a chatbot, predict movie ratings, or analyze your fitness data – get creative!

Definitely for competition the best place to start is Kaggle, it has a broad variety of use cases, datasets, previous solutions, etc. That you can use as examples even if you don't want to join the competition. Some of the competitors are even really experienced researchers and practitioners.

I would recommend running experimentations in a controlled environment. For eg- how much time does it require to summarize a document by self vs using a chat bot and measuring against some metrics- both quantitative & qualitative. Then try improving with better prompts.

I created a network of local government professionals who are interested in learning more about the practical applications of AI. We meet online each month to discuss and share use-cases. I have personally learned a lot from this 1 hour per month meetup. Its also encouraged me to continue to play with AI tools and test the limitations. There is definitely a challenge in public sector work of few people wanting to go first. Most want to go 2nd or 3rd, because then there's a path. But, getting to talk to real trailblazers is invigorating as you get to hear and see real life innovation occurring in cities of all sizes across the country.

Sign up for an AI Hackathon, you will absorb an immense amount of information quickly. Working with enthusiasts; at your level, just starting out and higher. As well as having access to seasoned AI professionals means you get effectively get teachers, tutors and guides for free, all while tackling a project that challenges your theoretical and practical AI skills.

In New Zealand there are lots of hackathon events and the AI Show monthly meetups hosted by NewZealand.AI. You can also look to programs run through universities and the AI Forum

For those looking to learn about AI outside of school, it's important for you to connect with AI enthusiasts, participate in AI events, and engage with those involved in the industry. Books are great resources, but they tend to be more focused on theory and do not provide visibility to the latest developments. As such, you can learn a lot outside of school by putting yourself out there and engaging with other AI enthusiasts, professionals, researchers, and stakeholders. With so many groups, communities, and events out there, you can have a lot of fun and meet great people as you learn about AI.

Bar none, the best way to connect to how AI tools have advanced is to carve out a few hours, ideally a few times a week, to roll up your sleeves and use the tools. This is because: 1) it is only by using these tools that you see where they are today 2) innovation has accelerated to the point where "curriculum" rapidly gets stale, 3) by getting in deep you quickly advance your ability to leverage the tools in your work and life. I keep a hit list on a notion page that I add to throughout the week and just work through it when I get to one of my planned deep dives. One problem: my hit list is growing 3x the rate I can work through it!

One of the things I love that my sister is doing with her 10-year-old is that they are testing and learning about AI tools together. Her daughter has a Shopify store and she’s rewritten the descriptions using AI. She’s using AI for her social media account which her mom helps her with and manages. For a child who is truly interested in AI it’s great if they can explore it together with a parent!

AI is a very wide field. Find out if you are more interested in solving the problem or learning about the methods (aka the how). As there can be many techniques used to solve a problem or to optimize for different outcomes. Besides the basics that can be covered in most online courses, pick your path, be it technical or do you prefer being a super user of no/low code tools. All paths take time and effort, and match that with your interests, skills and technical expertise.

Curriculum AI is great, but you need real world experience. I came up with M.U.D. Everyone must go through MUD to be well-rounded as AI professionals. -Monitor In Sun Tzu's "The Art of War," he talks of monitoring as an aspect of strategic thinking where he explains the importance of observing the terrain, including its features, advantages, and obstacles, enabling one to adaptation and strategic advantage. Understand the terrain of AI first. -Use All chefs taste what they create. You have to know what you are building before you can offer it to others -Develop Developing is a command role. Sun Tzu's teachings progress from observation to tactical understanding to leadership and command positions in warfare. #ai #artificialintelligence

After the initial stage of exploration and learning the basics, you should define your learning outcomes more specifically and focus most efforts on them. Are you technical and want to become an AI developer, or are you a non-technical business leader who want to stay informed for AI use cases and development to make better strategic decisions? Your learning path will be completely different depending on your answer.