So if you follow me on Instagram (if you're not, what are you doing?😂), you'll of seen my post about the 'completion' of 'Python for Data Science and Machine Learning Bootcamp, by Jose Portilla'.
And if you seen my first ever blog post (again if you're not, what are you doing?!😂), you'll of seen why I don't think too highly of online courses. With that being said, the knowledge gained is useful however to get to that next level, you need to do more.
In this post, I talk about the course (which I would recommend) and also why I haven't 'Completed' Python for Data Science and Machine Learning, even though my certificate might indicate that I have 'completed' it.
This section involved the use of Numpy, Pandas, SeaBorn and Matplotlib. As I went through the course there were lots of opportunities to reinforce skills learnt in previous sections. For me personally, I found it quite satisfying to create aesthetic visualisations. Also, as I learnt more, I learnt about the power of these libraries and how they can create big things!!
Each section also had a project which was good however I feel like there should've been more projects and that they some of them should've been more complex.
Again, this section had great topics such as Regression algorithms, Classification algorithms, Cluster algorithms and more...
Again this section had projects however I don't think they were the most interesting tbh.
Further Learning (Reference Title):
Referencing back to my first blog post, I posted this:
(Credit to @data_science95 for a great post, check them out!)
I intend to act upon it, using the methods shown above. This includes sharing open source code, writing blog posts (this) and deploying projects for all of you to see.
In conclusion I haven't 'finished' learning because nobody finishes learning. Especially in Computer Science, things are always changing. It's nice to receive a certificate however there's more work to be done!!
If you have any topics that you want me to blog about then please let me know in the comments!!!
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