2026 Study Goal: Machine Learning Fundamentals
One of my main study goals for 2026 is to gain a deeper understanding of Machine Learning. It was previously a sub-discipline of AI, but has become synonymous with it as its been the impetus in the latest breakthroughs like ChatGPT.
ChatGPT
Before ChatGPT and large language models brought AI into the mainstream, machine learning was often treated as a buzzword. Today, AI is clearly a disruptive force, reshaping how people work and think about technology.
While tools like ChatGPT are impressive, they also reveal limitations—hallucinations, shallow reasoning, and weak long-term memory. LLMs have their place and will continue to improve, but they are only one part of the broader ML landscape.
Online ML Courses
I’m starting with the Google Machine Learning Crash Course as my December 2025 study focus, followed by a more structured MOOC such as an edX Machine Learning course. I’ve found that learning terminology is especially important—knowing that “stochastic” means random or that a “token” represents a word makes abstract concepts far easier to grasp.
Self-Study 1.5 hrs --> 11 hrs
To make meaningful progress, I’m increasing my study time from 1–2 hours per week to about 10–12 hours per week, roughly 2 hours a day. By January 2026, my goal is to complete the Google course, internalize the glossary, and clearly understand the core concepts.
Python ML Projects
Along the way, I’ll experiment in Python, starting with simple ML projects like email spam detection. My focus is on building strong fundamentals—knowledge that will remain valuable even as tools and trends continue to evolve.

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