10 Ways to Learn Artificial Intelligence as a High School Student

Getting started on your Artificial Intelligence journey can be an exciting but fairly intimidating process. With the abundance of resources, you might not be sure where to start. Don’t worry, you’re not alone, and we’re here to help you kickstart your journey!  

Why learn AI in high school?

Learning AI in high school will equip you with in-demand skills such as problem-solving, and critical thinking and familiarize you with analytical concepts like regression and statistical inference. With the rapid growth of companies like OpenAI, there is a demand for interdisciplinary innovation and research in the field. Being equipped with these skills will help you contribute to this growth and even apply them to other fields such as medicine and finance. 

To help you out, in this blog, we have detailed 10 ways in which you can develop your AI skills from scratch! 

1. Enroll yourself in online courses

If you want a beginner-friendly way of approaching AI, while being able to learn at your own pace, you should consider enrolling yourself in an online course. These courses usually assume little to no previous knowledge of the subject, so if you’re a complete beginner, this is a great fit for you. You could do a crash course on AI, start off with machine learning, or even take a linear algebra course to familiarize yourself with the math behind it all!

a. Veritas AI - AI Scholars Program: If you’re interested in a more application-based approach for a course that ends with a final project, then this boot camp is for you. This is a 10-session program that is beginner-friendly and requires no prior experience. You will dive into topics such as linear regression, image classification, neural networks, and natural language processing (NLP). This course will require you to work on application-based projects in teams under the guidance of experienced mentors. You can apply for the program here.

b. Coursera- AI: Coursera has an abundance of courses covering AI and how to get started. You should take the courses offered by a prestigious educator, such as IBM, Stanford University, or the University of Pennsylvania. Courses offered by these organizations range from AI in Healthcare to AI for Business and AI Foundations for Everyone. The courses could be paid or free depending on what you choose. 

c. Google Cloud Courses on Coursera: The courses offered by Google cover a range of topics such as Introduction to Generative AI, Introduction to Image Generation, and Introduction to Large Language Models. They’re very beginner-friendly, and allow you to revisit the course content, letting you take the course at your own pace. 

d. Online AI courses on edX: This is a platform similar to Coursera, but primarily focuses on CS and AI-related courses. They have exclusive courses offered by prestigious universities and organizations such as Harvard, IBM, and Google. Some of these courses include CS50's Introduction to Artificial Intelligence with Python by Harvard University, AI for Anyone by Google, and AI for Everyone: Master the Basics by IBM.

2. Join online artificial intelligence forums 

If you want to engage in active conversation about AI and learn from like minded peers, you should consider joining AI forums and communities online. You could approach these forums with questions or spark discussions about the latest innovation in the field. If that sounds interesting to you, you should consider the following forums:

a. Stack Overflow: If you’re planning on pursuing a tech major, or have studied any amount of computer science, chances are you already know of Stack Overflow. This website is a community-based space to find and contribute answers to any technical challenges you may face. While not purely dedicated to AI, you will find plenty of resources and discussions relating to AI and ML, in particular, any errors you might face while running your code, or any software-related issue. 

b. Reddit’s r/artificalintelligence and r/artifical subreddits: Subreddits are a great way to catch up to the latest in AI for anyone who’s a beginner. Both these forums are similar, but r/artificalintelligence promotes more social conversation around AI while r/artifical is better for discussions about the newest development in AI. You could also consider more specific subreddits like r/ChatGPT, to deep dive into one topic and ask more detailed questions. The best part about Reddit is that you will find peers of your own age on Reddit, discussing modern ways of tackling issues

c. Learn AI Together Discord server: A Discord server is a much more casual space to talk about AI as compared to something like Stack Overflow. The servers are also a lot more active, which increases your chances of getting a reply to your post and engaging in meaningful discussion, as opposed to other platforms, where your post may be easily overlooked. 

3. Join a high school club

If an online discussion doesn’t sit right with you, and you would rather take a more hands-on and in-person approach, then a high school club related to AI would be a great place to engage with more people your age. Clubs allow you to approach problems together and create an innovative, collaborative atmosphere. These clubs usually meet every week, participate in projects, and organize events. 

If there isn’t an AI club in your school, try making one of your own and build a space full of like-minded individuals! If there is already a computer science or tech-related club in your high school but not an AI one, you can always join those and incorporate AI into it! You can be inspired by looking at duPont Manual’s AI club and Thomas Jefferson’s machine learning club!

4. Build a personal project

If you would like to dive into the applications of AI and learn better through a hands-on approach, then a personal project would be a great way to do that. A project in AI could involve exploring the intersection with another topic (like medicine, finance, sports), a research paper, or building an application from scratch. This would also help you figure out which field within AI you’re interested in. Having a personal project under your belt is also a very good look on your college application if you wish to pursue a tech-related major. A great way to do this would be by joining a mentorship program like Veritas AI.

As part of the Veritas AI Fellowship, you will work directly with an experienced mentor from a top university to build your project. This 12-week program aims to teach you how to build your own learning model, app, software, or research paper, by taking a hands-on approach. However, keep in mind that the program requires you to be familiar with python, so make sure to work on your python skills before you apply! Previous projects by students who participated in this program include “Detecting Tweets Relating to Disasters Using Natural Language Processing” and “Predicting diabetes patients chances of Readmission Using Random Forest and deep learning models”. You can check these and more projects here.

5. Participate in AI Hackathons

If you wish to build your network and test your AI skills, then participating in an AI hackathon would be a great way to do so! These hackathons help bring together groups of creative, like-minded individuals to build a project from scratch, using both software and hardware tools. Over a small amount of time, you will be expected to find a way to solve a real-world problem. You will also get to be a part of seminars and workshops for beginners, which will help you get familiar with basic AI concepts before making a project. This makes hackathons a very inclusive environment, regardless of your background in AI. You can consider one of the hackathons below:

a. Kaggle Days: This is a beginner-friendly hackathon focused on Data Science but also includes elements of AI. The event is hosted by Kaggle, one of the world’s largest online communities for data scientists and machine learning engineers. Kaggle hosts hackathons throughout the year, in both online and offline settings, so you can participate in the comfort of your own home. The event usually lasts 9-11 hours. 

b. AutoGPT Arena Hacks: This hackathon is hosted through lablab.ai, which lasts 3-weeks, and you can join in at any time. This hackathon is built around developing an agent-  which is a computer program that is designed to perceive its environment and take actions to achieve a specific goal- that takes natural language input and can handle tasks. These hackathons are beginner-friendly and incentivize participation with great prizes such as OpenAI credits. 

You can check out more AI hackathons like these here!

6. Learn Programming Languages (Particularly, Python!) 

A great way to get started on your AI journey is by learning a programming language that is essential to machine learning models such as Python, C++, and R. You can learn these languages at various platforms such as Coursera, Udemy, and edX. If you are interested in applying AI, then Python is hands down the most widespread language for this. That’s where we would suggest you start! 

Make sure to choose your language based on which part of AI you’re interested in. For example, R is essential for data science and is required to perform any statistical analysis on a set of data, while Python and C++ are used to program applications based on the results of the analysis. 

7. Read newsletters, blogs, and books about AI 

You can also keep up with the desirable skills in the industry and make sure you know how to use them by subscribing to newsletters and reading blogs. Reading literature on a topic like AI might not seem important, but knowing the abilities of certain tools and the latest developments is essential to being a successful AI coder. 

A few suggested newsletters are Data Signal, The Algorithm by MIT, and Import AI which is written by Open AI’s Jack Clark. You could also follow blogs like Distill and Google’s official AI blog, which will help you learn certain concepts from different perspectives. Books such as Deep Learning (Adaptive Computation and Machine Learning series) would be a great resource once you’re more familiar with the basics and want to explore advanced ideas, since the concepts in the book may not be easy to understand for a beginner. 

8. Subscribe to YouTube channels about AI and machine learning 

If you’re a visual learner but are hesitant to pay for a course and want to learn at your pace, then YouTube channels are a great way of doing so! These channels range from tech-focused ones discussing the latest developments and innovations in modern fields , to ones that cover content in a more conventional course-style manner. 

If this is something you’re interested in, check these channels out:

a. StatQuest with Josh Starmer: The goal of StatQuest is to break down large concepts into understandable bite-sized pieces. However, Josh makes sure that the content doesn’t lose its value, and that you still get all the important information you need from the ground up to make you smarter. You can check out this index that maps out his content in a course-like manner.

b. DeepLearningAI: This channel offers various tutorials and lecture videos that will help you understand different applications of AI and Machine Learning. It was founded by Andrew Ng, who founded Google Brain and is a famous AI practitioner. This channel also features interviews with professionals in the field along with Live Q&A sessions. This will help you gain valuable insights from experts in the industry and guide your AI journey. 

c. Sentdex: If you’re more interested in seeing the applications of these concepts in a hands-on manner, then Sentdex run by Harrison Kinsley is a great choice! This channel covers a range of tutorials related to AI and machine learning, specifically using python. They are beginner-friendly and are meant to help you build your analytical and innovative skills through practical learning. 

9. Contribute to Open Source Projects

An open-source project is one that is available for free for anyone to use, modify, and distribute, further encouraging collaboration and creating a constructive environment. Taking a go at a beginner level open course project will help you put your AI skills to use, in a way that is recognized and actually helps solve real-world problems. This would also look great on your portfolio, as having your contribution to a reputed open-source project is considered valuable, showcasing your creative skills and your ability to work with a team. Note: contributing to open source projects often requires a slightly more advanced level of programming skills. This probably wouldn’t be where we would start off if we were new! Here are some example projects you could look at: 

a. Llama 2 by Meta and Microsoft: Llama’s mission is to unlock the power of large language models. Since it’s powered by Meta and Microsoft, it’s a reputed project to contribute to, and will give you the chance to be a part of something big. This is the perfect project to contribute to if you’re interested in language models like ChatGPT. 

b. Open Assistant: This project is aimed at giving everyone access to a chat-based LLM. The contributors are determined to create a Chatbot that is capable of writing emails, and cover letters. They also want the chatbot to have the ability to be personalized according to a user’s preferences.

c. Detectron2: If you’re more interested in computer vision and image classification, then this project backed by Facebook is a great place to start. The aim of this project is to create a software system that pushes the bounds of computer vision by creating state of the art object detection algorithms. You will need to be familiar with Python and PyTorch to contribute to this project. 

10. Apply for an internship

Consider applying for an internship only after you have enough experience in the subject and want to use those skills you’ve developed in a more hands-on environment. Not all internships are open to high school students and are usually highly selective if they are. However, if you have the required skills and meet the criteria, you might end up finding the right internship! An internship will help you engage with veterans in the field and learn from their experience and insights. 

One way to find an internship is through organizations like Ladder Internships, which is a selective program for high school students to work with startups in various fields like computer science, technology, artificial intelligence, machine learning, and more. As part of Ladder Internships, you will work on real-world projects in the field of computer science and technology. At the end of the program, you will present your work to showcase tangible outcomes on your CV. Students have previously interned with board members of companies to build a database of startups that are gamifying health care protocol, improving website experiences, building the backend and frontend hosts, and building technical MVPs using generative AI. 

Bonus Tip - Do a research program about AI and machine learning

Research programs are a great way to dive deep into artificial intelligence. As a beginner, it is also a good starting point to help you explore the many areas (and intersections!) of AI to identify what interests you. Working on individual research projects is definitely a valuable addition to college applications if you are looking to pursue a related degree at university. There are programs that offer research mentorship opportunities to high school students to work on independent research papers in their field of interest. 

One such program is Lumiere Education, which is good for beginners looking to start their research journey in AI. Lumiere is a selective research program for high school students, founded and run by Harvard and Oxford PhDs. You get to work one on one with a PhD mentor to develop an independent research paper. They offer research opportunities across various fields including artificial intelligence, machine learning, computer science, data science, robotics, and more! This is a good fit for you if you are interested in research, especially if it is at the intersection of different fields!

If you’re looking to build unique projects in the field of AI/ML, consider applying to Veritas AI! 

Veritas AI was founded by Harvard graduate students, and through the programs, you get a chance to learn the fundamentals of AI and computer science while collaborating on real-world projects. You can also work 1-1 with mentors from universities like Harvard, Stanford, MIT, and more to create unique, personalized projects. In the past year, we had over 1000 students learn data science and AI with us. You can apply here!

Image Source: Ladder Internships Logo