I am currently in the first course of the specialization. I have basic knowledge of Python, including functions, data types, regular expressions, and data reading and writing. I have also learned the libraries NumPy, Pandas, and Matplotlib. However, I still find it difficult to understand the code, even though I understand the concepts well. What do you, fellow learners, suggest? Do I need to understand the code in the labs right away, or can I focus on understanding the concepts first and revisit the code later?
These labs are designed to reinforce the concepts being taught and give you hands-on experience. Coding along helps you understand how the theoretical concepts are applied in practice and makes it easier to follow along with the course material. Additionally, this practice will prepare you for the programming assignments and projects that come later in the course.
If you encounter advanced terms or concepts that are not immediately clear, it’s okay to pause and revisit them after you’ve gained more understanding from the subsequent lessons. However, actively coding as you learn will enhance your comprehension and retention of the material.
Concepts then code, that should work fine.
Hi @Haider_Abbas4 this is a common issue, I found myself on the same position when I started, so not worries, it is expected you feel the same way, you don’t need to understand the labs right away, instead it is expected you struggle and find the way to understand and be able to answer the solutions by yourself, try to understand the concepts but also relate each concepts with the code solution can be a good step to have a practical understanding to machine learning.
I hope this helps!