This blog post is directed toward high school students that do not have any prior experience in the field of AI and strive to expand their knowledge of AI.

The expected time dedication is one summer, with a flexible requirement of 5 hours per week. The completion of this task is achievable within the academic year, although it may necessitate a longer overall timeframe.

Accomplishing this journey during the summer following my second year of high school, I will update this page if it is not achievable.

Why learn AI

AI is a rapidly expanding field. It will quickly take over many jobs.

Ted talk - Big Data is Better Data

1. Data has gone from a collection of information to a flow of new ideas

2. Machines can now surpass the humans that designed them through Machine Learning

3. Machine Learning is everywhere, from search engines to voice recognition systems

How To Learn AI

Initially, it is essential to acquire proficiency in fundamental skills. Acquiring these skills will enhance your comprehension of more sophisticated AI concepts in the future.

1. Proficiency in fundamental mathematical concepts is essential, encompassing a basic understanding of algebra, geometry, and calculus.

2. A solid understanding of statistical principles, including probability, distributions, hypothesis testing, regression models, and methodologies, is essential.

3. Data management skills including cleaning, storage, retrieval, and visualization are essential.

Next, acquaint yourself with Python, as it is widely regarded as the predominant tool for deploying AI models.

Grouped below are essential packages and tools that are recommended for learning.

1. Pandas and NumPy.

2. Scikit-Learn.

3. PyCaret.

4. PyTorch and Keras.

5. TensorFlow.

6. Matplotlib and Seaborn.

7. HuggingFace, Theano, and LangChain.

Develop Your Personalized Learning Strategy

1. Envision - Set clear objectives for your AI education to stay motivated and focused, whether for a career, projects, or personal interest.

2. Simplify - Organize learning into segments, starting with basic skills and progressing to advanced topics to reduce overwhelm and improve success.

3. Plan - Create a study timeline for artificial intelligence based on your daily schedule. One summer is suggested, but you can extend your plan as needed.

Learn AI with these online courses

1. Dataquest - Intro to Python

   1. Introduction to Python course

   2. Self-paced learning

   3. Very short

2. Big Data AI Ethics

   1. Coursera course

   2. Big data and AI fundamentals

   3. Total of 12 hours needed

3. Machine Learning Specialization

   1. Coursera course

   2. Machine Learning specialization

   3. Requires 10 hours a week for 2 months
      

Learn AI with these books

1. Python Programming for Beginners - Philip Robbins

   1. Easy to read and understand

   2. Covers most of the fundamentals

   3. Not too long

2. Artificial Intelligence Programming with Python - Perry Xiao

   1. Chapters outline specific examples of AI

   2. Good introductory chapters

   3. Long, but informative

Tips for learning AI

1. Practice with hands-on projects to solidify concepts and skills. You can start by automating tasks or creating AI models.

2. Join AI communities for knowledge exchange, networking, and staying updated on trends.

3. Apply your knowledge to real-world projects through internships or open-source contributions to showcase your abilities for high-paying jobs.

Reference: How to Learn AI