FAQ: Data Science -- Where to Start?

Data is the new oil. Perhaps this statement has now become a cliche. It goes without saying that data science has become the hottest job of the decade. It was predicted that there will be a shortage of data scientists, and that shortage is already prevalent now.

The reality of it all is this, the academe lags behind in preparing students to fill this gap. Data science is simply not taught in school, and the demand for it grows by the minute. While on the subject of data science, I have been often asked: "Where do I start preparing to gain practical skills for data science?" And too often, my answer is Python. But Python in itself is a broad topic and I will be a little more specific in answering that in question in this post.

In my line of work, having knowledge of Python really gives you an edge, not just an advantage. So if you want to start a career in data science, building a Python skillset is simply practical.

Knowledge, and even expertise, in Python can go a long way. It can be applied to ETL (or extract transform and load), data mining, building computer models, machine learning, computer vision, data visualizations, all the way to advanced applications like artificial neural networks (ANN) and convolutional neural networks (CNN). In any of the mentioned aspects of data science, Python can be applied and building expertise really becomes valuable over time.

Complete Python Bootcamp: from Zero to Hero

For beginners, those who have no idea how to program in Python or those who have only heard about it for the first time, the online course(s) really work. The course that has really helped me in getting a head start is Complete Python Bootcamp: from Zero to Hero. I have mentioned this often enough and will continue to advise the course to anyone who wants to learn Python.

While taking on this course, the other recommendation is building knowledge in jupyter notebooks. This will boost your Python productivity. Also, it helps you understand (and re-use) other peoples code as well as aid you in sharing yours, if you wish to. In fact, several of those online courses share code in the form of jupyter notebooks.

To complete the answer, the Python library to master for data science is pandas. Pandas is often referred to as the Python Data Analysis Library and it rightfully deserves that reputation. More often than not, pandas is involved in data analysis, where it really shows its muscle. My recommended course for learning and mastering pandas is Data Analysis with Pandas and Python.

There goes my answer and I hope that helps you build the needed skillset to build a career on data science. These are by no means the only training courses you need, it simply addresses the "where to start" part of it, in my opinion. The more you use Python in your daily activities, the better honed you become and it will be easier for you to talk in the Python lingo before you notice it.

RELATED: Huge Discounts on Python Courses at Udemy

So, how did your data science journey, or Python experience start? Was this able to answer your question? Share your thoughts in the comments below.

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