Ai in High School: How to Get More Closely Involved with AI
In recent years, AI (artificial intelligence) has taken over the world by storm, and with the releases of so many different AI applications, AI has become a driving force in shaping the future of our society. Additionally, with so much demand and potential applications for Ai, there is unlimited potential for it to grow. Because of the high demand for AI, and its relevance to so many different fields, AI-related jobs have become very high paying and in demand. So, we’ve created an algorithm for enthusiast high schoolers to get a head start on getting more deeply involved in the AI field.
Learn a Programming Language and become familiar with its library
Programming is essentially writing the step-by-step instructions for your computer to follow, and make up the building blocks of AI. Therefore, it is essential that you know how to code at least one language. Some recommended languages to start off with are:
Python: A very beginner friendly language, easy to learn and implement There are also a wide variety of AI-specific frameworks that were created specifically for the language, and it is a very powerful tool for data analysis, making it one of the most popular languages to use for beginners and experts alike.
Java: Another popular AI language because of its easy debugging and usability traits. It also has Ai-specific frameworks created especially for itself, and is cross-platform, which allows for projects to be implemented and run on multiple different platforms.
C++: A low level language which makes it incredibly efficient at executing code, making it a great code for more complex and resource-intensive code applications. However, C++ is a more difficult language to code in, making it not the most beginner friendly language to work with.
Lisp: Another widely used language in AI, because of its high level of flexibility, and its ability to rapidly prototype. In fact, Lisp was developed in the 1950s as a research platform for AI, making it highly suited for processing symbolic information. However, Lisp has a syntax that is very different from other languages, and its library is not highly modernized, making it a more “outdated” language.
R: An open source, platform independent language primarily used for data analysis. R is great for statistics, and is also suited for Machine Learning, where it can be used to make algorithms. However, it also is a more complicated language to learn, just like C++, so it is recommended that you have prior experience in coding before learning it.
Some good resources to learn how to code are Codecademy, LeetCode, The Odin Project, or FreeCodeCamp.
Learning/ Developing specialized AI skills
AI requires a strong foundation in math, as basic knowledge of Statistics, Linear Algebra and Calculus are essential as they are the backbone for creating AI algorithms and models. So, it is recommended that you try and build up a strong math foundation.
Understanding and having a basic idea of subfields like ML - Machine learning, DL-deep learning NLP - Natural Language Processing, CV - Computer Vision, SI - Super-intelligence is important. You should also get familiar with organizing and storing data, as well as the concept of algorithms. Some resources that can deepen your understanding of these subjects include:
DISCLAIMER: A lot of these courses require a prior understanding of Calculus, Statistics, or Linear Algebra, so if you have not taken those math courses yet you likely find it challenging to understand many of the concepts.
Coursera
An global online learning platform that offers anyone the access to their massive variety of online classes and degrees. These classes are self-paced, so you can progress through them at the speed you like, but because it is a MOOC, the courses offered are not that personalized.
Note! - The State of California has partnered with Coursera to allow residents to get access to Coursera Plus for free, just contact your local library in California to get it.
Some recommended courses on there include:
Youtube channels: There is a lot of high-quality content on Youtube, such as online lectures about AI or tutorials about using AI. Some useful channels on there include: Clever Programmer, Freecodecamp, Simplilearn, Edureka
Books
A very useful resource when learning something new. Some recommended books are:
“Pattern Recognition” by Duda Hart and Stork
“Reinforcement Learning’ by Sutton et al.
“Artificial Intelligence: A Modern Approach” by AI experts Stuart Russell, Peter Norvig
“Deep Learning” by Jon Kohn, Grant Beyleveld, and Aglae Basens.
Artificial Intelligence Basics by Tom Taulli
“Artificial Intelligence for Dummies” by Luca Massaron and John Mueller's
Udemy
An online learning and teaching marketplace with a massive variety of courses. There, you can receive an idea of how AI works with real-world data, and how it can be applied in real life.
Some recommended courses are:
The Beginner's Guide to Artificial Intelligence (Unity 2022)
Artificial Intelligence A-Z 2023: Build 5 AI (incl. ChatGPT)]
Udacity
Another MOOC online platform with a subscription based model for their courses, which means that users have to pay monthly for their course until they have finished it. The Udacity platform also provides Nanodegrees, which are paid programs in the fields of technology and business, and mostly comprises of three to four single courses.
Some recommended courses are:
Khan Academy: An online educational organization created to help educate students through videos and problems. You can use Khan Academy to help improve your math foundations or learn more about AI.
Do projects
Now that you’ve understood the major concepts and subfields of AI, try to put what you’ve learned to the test. Start off with simple tasks such as applying an ML algorithm to a dataset, then slowly advance to more complex projects like building a recommendation system.
THE CHEAT CODE:
If all of this information feels like too much or you can’t figure where you want to start from, there is a cheat code to all of this. Signing up for AI camps can make life much easier, as you will receive much more targeted feedback and advice than if you are taking MOOCs, and experienced mentors will already have the most effective curriculum planned for you based on your skill level.
If you are interested in learning more about some of the best AI programs offered, make sure to check out this link: Best AI Bootcamps in 2024
Additional Bonus Tips:
Join AI and ML communities on LinkedIn, Telegram, reddit, etc. Communicating with others in these groups is a great way to learn more information and they can also help answer your questions. to practice. You will also be motivated to work harder if you see others putting in effort. With that said, Good Luck and Happy Learning!
About Inspirit AI
AI Scholars Live Online is a 10 session (25-hour) program that exposes high school students to fundamental AI concepts and guides them to build a socially impactful project. Taught by our team of graduate students from Stanford, MIT, and more, students receive a personalized learning experience in small groups with a student-teacher ratio of 5:1.
