As we've successfully crossed the first half of the decade, let's plan well what we'll do with the second half. A lot has happened: a worldwide-scale pandemic, economic crises, work layoffs, and a lot more perilous events. We cannot control our external factors, however we can be conscious of every step we take and align it in the direction of what we want best for our future self. We begin the second half of the decade. What story will you have to tell at the end. Were the '20s years you wasted your life or did you pursue and achieve something worth it? I know most of us here are trying to escape the corporate grind of 9-5. Therefore let's work hard by discipline and implementing routines to stay consistent. Remember, consistency compounds. Happy new year everyone !! 🎉🎉🎊🎊

The AI hype has been exaggerated, especially with NVIDIA's CEO claiming generative AI is going to make everyone a capable programmer/software engineer. At least, most of us here know gen AI hasn't reached this potential - it does not actually reason out responses, but predicts subsequent characters based on probabilities determined by the prompt passed. We could conclude companies like NVIDIA are making attempts to use this hype to drive their stocks up, with which NVIDIA has done successfully. It is therefore necessary to know the basics of AI and ML, to up your game in this space. My concern however is considering whether a Data Scientist can also function as an AI engineer, since they both have similar foundations. I know very well, the saying: 'jack of all trades, master of none'. I still believe it wouldn't hurt to be proficient on both areas.

Mine: c++

Posted my challenge of using a book to learn Python. https://www.skool.com/data-alchemy/my-one-week-python-challenge?p=9b1207b8 Day 6: Learnt how to debug code. Having the right debugging techniques, you're able to find bugs quickly. Learnt to use the 'assert' statement as an instant check for mistakes in code, the logging library to take logs of variable values and time at different points of code and using an IDE debugger which can be helpful to visualize the process of executing code and to determine points where bugs are. Started with web scraping, will continue tomorrow.

Posted my challenge of using a book to learn Python. https://www.skool.com/data-alchemy/my-one-week-python-challenge?p=9b1207b8 Day 4: Practiced regular expressions. They're used to search for specific parts of text based on some elements the user provides. Regular expressions can shorten code - especially code that require verifying the right input. Also learnt about input validation - the author has created his own library of functions similar to the input() function. However, these functions have various added functionalities. One thing I learnt from this is to find out libraries related to the task I want to write code on. It can save me time and make me use less effort - rather than having to figure how to produce the script entirely on my own.