A few months ago, I transitioned to using Python at work and quickly realized the importance of getting familiar with its built-in functions. There are approximately 70 of these functions, though in my day-to-day tasks, I tend to rely on only about two dozen. One of the challenges I faced was not always being able to recall their names instantly, or occasionally forgetting to add parentheses after the function name. These small oversights often disrupted my workflow, forcing me to pause and reconsider the syntax instead of focusing on the problem at hand. I wanted to streamline this process so that the correct syntax would come naturally to me, without the need for constant mental searching. To address this, I turned to an old but effective method: building muscle memory. The idea was to learn all 70 function names and their basic definitions thoroughly so that I could recall them promptly when needed. Comparatively speaking, 70 functions seemed manageable—when I studied languages like English and Spanish in university, I often had to memorize between 200 to 400 new words in a single week. If I could handle that, mastering 70 functions should be feasible. I decided to adapt a technique I used during my language studies. Back then, I color-coded my notes: green for the new word, black for the pronunciation, and blue for the definition in my native language. For Python's built-in functions, I adopted a similar strategy. I began by writing down each function name in green, followed by its basic syntax and definition in black. I also added examples in blue to illustrate how each function could be used in practical scenarios. By repeatedly typing out the names and definitions, I hoped to ingrain them into my memory. Another tool I found useful was flashcards. I created a set of digital flashcards, each featuring a function name on one side and its definition and example usage on the other. I quizzed myself regularly, both in the morning before work and during breaks, to reinforce what I had learned. As I persisted with these methods, I noticed significant improvements in my ability to recall function names and their correct syntax. The process became smoother, allowing me to focus more on solving problems and less on memorization. Over time, I developed a stronger intuition for which functions were best suited for different tasks, enhancing my overall efficiency. Beyond just memorizing the functions, I also started exploring how they could be combined to create more powerful and concise code. For instance, functions like map(), filter(), and reduce() can transform repetitive loops into elegant one-liners. Similarly, zip() can pair elements from multiple lists effortlessly, and any() and all() provide quick ways to check for certain conditions across collections. In conclusion, while Python's built-in functions may seem daunting at first, they are essential tools that can significantly enhance your coding capabilities. By leveraging tried-and-true learning techniques, such as color-coding and flashcards, you can quickly become proficient in using them. This not only helps you write cleaner and more efficient code but also keeps you focused on the bigger picture—solving complex problems with ease.