Learn Python data analysis

This is exactly how I would learn Python for data analysis for free if I had to start over 👀 I still remember how overwhelming it felt not knowing what to learn first. These five free courses take you from Python fundamentals to analyzing, cleaning, and visualizing real data. But do not just watch the courses. Code along, practice with a real dataset, and turn what you learn into projects. Which course are you starting with? Let me know in the comments. 👇 I would recommend starting with this free CodeCamp beginner Python course. It will teach you the basics like variables, conditions, loops, functions and data structures. And spend about 30 minutes a day coding along with the instructor instead of just watching. There's something called tutorial trap. This is basically your foundation in Python. Next take this Kaggle Python course. This one gives you short hands-on exercises so you can practice the fundamentals instead of simply watching someone else code. Once you understand the basics, move on to Kaggle's Pandas course. This is where Python becomes useful for data analysis. You will learn how to read datasets, select and filter information, group and summarize data, handle missing values and combine multiple datasets. All important skills for data analysis. After that move to this data cleaning course because real world data is actually really messy. You will learn how to fix missing values, inconsistent entries, formatting, working with dates, and how you recognize some anomalies. After you have done that, you move on to this data visualization course. You will learn how to create basically line charts, bar charts, heatmaps, scatter plots, distributions, basically all the cool visualizations that you will actually build them. So the path is: 1. Python fundamentals, 2. Hands-on practice, 3. Data manipulation, 4. Data cleaning, and then 5. Data visualization. After completing the course, use AI to practice. For example, you take a real dataset, try to answer 3 questions yourself first. Then give your code to ChatGPT and ask, "Review my approach, explain what I got wrong, and show me how I can improve it." This is where you use AI as your tutor. Do not copy the answer. Compare it with your original code and make sure you understand what we're using it for, not for cheating. Once you have the basics, then build three projects: a product analysis, a customer retention analysis, and an exploratory data analysis with visualizations. If you want, I can cover projects in detail in one of my next videos. Basically, you're going to build a portfolio that proves that you can work with data. Add those projects to your LinkedIn and GitHub. My favorite part is that all five courses are completely free. And of course, you already knew this because you follow me. Let me know what I should cover in the next video and I'll see you on the other side.