Learning Python with Accountability

"Having a specific use case when learning Python will make your journey 10x easier." That's the advice I'd give my past self if I could. My first attempt at learning Python was over 7 years ago. I remember being so confused, wondering what any of it was for, and I eventually gave up. Since then, I have tried countless other times and found myself staring into that very same void, "Why am I doing this? What will I even use this for?" However, this time I am making steady progress and staying committed because I have a very clear goal: I want to wrangle, clean, analyse, and visualise data with Python. I even have a specific project timeline in mind. And today's lesson on using string methods to build a simple data cleaning function is a reminder that I am on the right path. 

🚀 Python Learning Journey – Day 24 Today, I learned about List Comprehension in Python, a concise way to create lists. Here’s what I practiced: ✅ Basic syntax of list comprehension ✅ Creating lists using for loop in a single line ✅ Using conditions inside list comprehension ✅ Writing cleaner and shorter code List comprehension helped me write more efficient and readable code compared to traditional loops. Step by step, I’m improving my Python skills 💪 #Python #LearningJourney #Beginner #ListComprehension #Day24 #Coding #KeepLearning

📘 Learning AI – Starting with Python File Operations As part of my continuous learning in Artificial Intelligence and Python, I recently explored File Operations in Python. When working with AI systems, handling data efficiently is very important. File operations help in reading datasets, storing processed results, managing logs, and preparing data for further analysis. 🔍 Concepts I practiced: • Reading data from files • Writing and appending data to files • Understanding file modes (r, w, a) • Using with open() for efficient and safe file handling 📚 I followed this playlist to understand and practice the concepts: https://lnkd.in/d-injG8r Building a strong foundation in Python is an important step when learning and working with AI systems. Looking forward to exploring more concepts as part of my AI learning journey. 🚀 #ArtificialIntelligence #Python #FileHandling #Learning #Upskilling #AIJourney

Day 16 Machine learning series python programming DSA ( Data structure algorithm ) Why DSA is Important for Machine Learning (Python)? If you want to become strong in Machine Learning, learning Python alone is not enough. You also need to practice Data Structures and Algorithms (DSA). DSA helps you: Write efficient and optimized code Handle large datasets Improve your problem-solving skills Understand how algorithms work behind ML models Some important DSA topics to practice are: Arrays Strings Dictionaries Sorting Searching Recursion and Time Complexity. A strong foundation in DSA + Python makes it much easier to learn and build powerful Machine Learning models. Start practicing today and strengthen your programming logic. we will explain deeply about DSA in next post.

🚀 Learn Python – Sets If you want to learn how to handle unordered, unique collections of data, mastering Sets in Python is essential. They are the ultimate tool for automatic duplicate removal. I’ve created a structured learning section on my website that explains sets step-by-step with practical examples. 📚 Explore the tutorial: https://lnkd.in/g7pykaF9 🔹 What you will learn • Creating sets with curly braces {} and the set() function   • Automatic duplicate removal for data cleaning   • Understanding unordered and unindexed collections   • Making empty sets correctly (set() vs {})   • Use cases: Mathematical operations and unique value filtering This resource is designed to help developers learn Python with practical examples and structured lessons. Happy Learning! 🚀 #Python #Coding #DataScience #LearnPython #Programming #PythonBasics

🚀 Today’s Learning – My AI Engineer Journey Coming from a Java background, I started learning Python OOP today. At first, one thing confused me a lot — What is "self" in Python? Then I understood it in a simple way: In Java → we use this In Python → we use self Both refer to the current object. Once I understood this, Python classes became much easier to understand. 💡 Small concepts create strong foundations. Consistency matters more than speed. Step by step, learning AI & Python. 🤖 #Python #OOP #AIEngineer #LearningInPublic #JavaToPython #MachineLearningJourney #CareerGrowth #TechLearning

Day 22: List Comprehension in Python Continuing my Python learning journey. Today I explored List Comprehension, a concise way to create lists in Python. It allows us to generate a new list by applying an expression to each item in an existing iterable such as a list or range. Basic Syntax : new_list = [expression for item in iterable] Example numbers = [1, 2, 3, 4, 5] squares = [x * x for x in numbers] print(squares) Output : [1, 4, 9, 16, 25] Using Condition in List Comprehension numbers = [1, 2, 3, 4, 5, 6] even_numbers = [x for x in numbers if x % 2 == 0] print(even_numbers) Output: [2, 4, 6] List comprehension helps write cleaner and more readable Python code when working with lists. #Python #PythonLearning #CodingJourney

🚀 Python Learning Journey – Day 25 Today, I revised Day 15 and Day 16 topics to strengthen my understanding. Here’s what I focused on: ✅ Revisiting key concepts and syntax ✅ Practicing previously learned programs ✅ Improving code clarity and logic building ✅ Strengthening confidence in fundamentals Revision helped me identify small mistakes and improve my problem-solving approach. Consistency and revision are helping me grow step by step 💪 #Python #LearningJourney #Revision #Consistency #Coding #Day25 #KeepLearning

If anyone is interested in developing their skills in Python (Programming Language), a quick thought based on my experience that might be helpful. 💬 Here are some tips for developing this skill: Learned Python through online courses and self-study, focusing on data analysis, statistics, and machine learning applications. Also took help from AI sources