Last Updated: 9/1/2024

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To develop an app that uses generative AI for personalized educational content, I recognize the need to master several key areas: programming fundamentals, AI concepts, machine learning, and specialized knowledge in generative AI. Below is the learning pathway I’m currently following, with topics ordered to build my knowledge progressively. As I gain a deeper understanding of this field, I may refine and adjust this plan to better suit my learning needs.

** Specific learning materials, such as textbooks or MOOCs, will be updated later.*

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Programming Fundamentals

I’m starting with Python, the most widely used language in AI and machine learning. My focus is on mastering Python to build a strong foundation in programming and prepare for more advanced topics.

ChatGPT, LangChain & LlamaIndex

While learning Python, I’m also experimenting with ChatGPT, LangChain, and LlamaIndex. These tools are essential for integrating chat functionalities and interactive features into my app. I’m exploring how to use LangChain to create these features and using LlamaIndex to build Retrieval-Augmented Generation (RAG) systems for dynamically retrieving information as students interact with the app.

Mathematics and Statistics for Machine Learning

AI and machine learning rely heavily on mathematics, particularly linear algebra, calculus, and probability. I’m taking courses and reading books to strengthen my mathematical and statistical foundation.

Introduction to AI

To grasp the big picture and potential applications of AI, particularly in education, I’ve completed MOOC courses and attended workshops.

Ethics in AI

Understanding the ethical implications of AI—such as privacy, bias, and fairness—is critical. I’ve completed a course on AI ethics to ensure that my app is developed responsibly.

Machine Learning

I’ve taken an online course that provided a comprehensive introduction to machine learning, including supervised and unsupervised learning, which is crucial for building AI applications.

Deep Learning

Deep learning is essential for generative AI. I’ve studied topics such as neural networks, convolutional networks, and sequence models through a dedicated course.

Natural Language Processing (NLP)

NLP is critical for analyzing students’ interactions with the app, allowing models to understand and process text data. I’m focusing on mastering this area.

Processing Unstructured Data for LLM Applications and Embedding Models