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Python is a so powerful tool in data science and this course is helpful for reviewing basic concepts. Even though I still have a long way to my future goal in the data science field, consistency could give us a chance to achieve the goal.
✏ 3 things to keep in mind:
1. Using a list comprehension: Make people's life easier.
2. "Overwrites" might cause bugs: Make your coding life worst.
3. Starting coding is better than reading the concepts: trying to do something is the most useful to learn new things.
Learn by doing
There are two things that inspired me!
First, the data portfolio project makes candidates more chances who want to get into data science fields. In my personal experience, PowerBI and Tableau are easier to approach your first project.
In the contrast, Excel is a little bit too hard for me to handle huge datasets because we don't focus on learning Excel in my college data science course.
Second, start doing your own data science project is the smartest way to learn new concepts. I love the "black box" method which we only learn what we need and keep going for the next step.
In the end, my goal for next year is to find my passion for data analytics and start doing different side projects which can practice more analytics skills such as PowerBI, Docker and SQL, etc.
Overall, Thanks to these two influencers @DanMorgan and Alex Freberg
If you want to learn more about data science, I really recommend watching his YouTube channel which can give people more inspiration.