I’m a 23 year old graduate with Accounting and Finance as my major. I’m intrigued by the topic of Data Analytics and I wish to learn the same. I did my research and found out that Python is the most important language for DA. But I have no knowledge of coding or any computer language.
(I learned how to make a very basic website using HTML as a part of an optional subject called I.T. , during my college days)
So where should I start?
Should I do the “Scientific Computing with Python” or “Data Analysis with Python” available on freeCodeCamp?
Or
Should I do some other course? Maybe Google’s DA Certification program from Coursera.
Just a few months ago, I was in a similar position, starting out as a complete beginner and wanting to learn how to program. Currently, I am at a somewhat “Intermediate/Advanced” level in Python. Maybe I can help you?
Starting out, I watched this Tutorial for Python, it’s around 4 hours long but covers a wide range of topics and basic features in Python. It’s by freeCodeCamp and is beginner-friendly!
Then, don’t forget to put what you know into practice. This is where sites and courses come in handy. I recommend you to try the Scientific Computing with Python course or solve simple problems in sites like Codewars, where you can dive deeper into Python.
Completing all these will take about a month or two. After that, you will have a good knowledge of what, where and how to further use Python for Data Analytics.
The Scientific Computing with Python course focuses on building up your basic knowledge of Python such as different data types, objects and explores more topics such as Networking and Relational Databases (dont’t worry about what these means, it’s clearly explained in the course).
Meanwhile, the Data Analysis with Python course will explore the use of libraries (again, don’t worry) to analyze and visualize data.
To answer your question, I strongly recommend the Scientific Computing with Python course first after watching the tutorial, and then the Data Analysis with Python. However, in the end, it’s all up to you, if you are ready to dive into Data Analysis, of course. The important thing is to not give up even when you feel like.