Learning Python for Data Science from Zero (Part II— Intermediate Level)

Sharing from a finance professional who has established an AI startup.


Hudson Ko

2/23/20234 min read

person using macbook air on brown wooden table
person using macbook air on brown wooden table

My Learning Journey in 5 Stages

  1. (Baby Level — Test your passion and basic ability)
    Data Camp’s “Introduce to Python” course

  2. (Beginner Level — Real Start)
    Data Camp’s “Data Scientist” career track

  3. (Intermediate Level — Certificates Hunter)
    Coursera’s “Applied Data Science with Python” by University of Michigan or equivalent courses on EdX

  4. (Advanced Level — Time to build something yourself)
    A Postgraduate degree OR/AND Learning by doing and post on Medium

  5. (Master Level — The More you learn, the Less you know)
    Build your own portfolio on GitHub

In this article, I will continue to share my personal learning journey on intermediate level. If you are a beginner and do not know where to start learning Python for Data Science, you may go back to the article here.

3. Intermediate Level (3–12 months)

After completing the courses on Data Camp, you should have obtained some general knowledge about Python for Data Science and equipped with some hand-on experience in programming.

However, it’s still far from enough to claim yourself with intermediate level of Python/Data Science. It’s because the Data Camp’s interactive playground never exists in the reality. For any jobs, you will have to write a Python script starting from a blank page.

Also, during job interview, you are often asked to describe some data science theories and concepts verbally in addition to programming test. Therefore, it’s necessary to learn some mathematics and logics behind the algorithms and do some programming from zero. More importantly, it’s time to add some valuable certificates to your CVs and then start job hunting.

To be honest, many people give up in this stage due to the difficulties and heavy workload. Motivation will drop gradually when you are facing those assignments and test.

My suggestion is to pick the courses that really interest you or pick those offered by the school or company that you admire. At least, you know you are working for a certificate you want. Such rewards will provide some additional motivation for you to continue learning.

The two famous learning platforms Coursera and EdX have now provided hundreds of courses about Python and Data Science. Many of them are offered by famous universities and companies.

  • Coursera provides two subscription options — (a) monthly subscription or (b) charges by courses. You may choose the way that fits your schedule. (I remembered I subscribed for two months and completed as many as I could.)

  • EdX is more like a freemium (“Free” + “Premium”) with most of the courses free to take. But you will have to pay if you want to get the certificates.

Back to the day when I first learnt Python & Data Science in 2016–2017, there were much fewer choices. The best one I found was the Applied Data Science with Python Specialization offered by the University of Michigan. Even until today, this program remains one of the most popular ones on Coursera.

The program is well structured with 5 intensive courses, including data visualization, machine learning, text mining and social network analysis. There are many exercises and tests based on real world data, providing an excellent training for the learners to have a taste of working as a data scientist.

However, the workload of this course is nearly half of a Master’s degree, which is a bit tough for those who work full time. (That’s why it is associated with the Master of Applied Data Science degree from the school.)

But I am sure that you will learn a lot about data science knowledge and practical skills in programming after completing the program. For example, you will gain some knowledge about Natural Language Processing (NLP) to understand the power of ChatGPT, and the famous Page Rank theory developed by Larry Page, the Google founder.

Sounds interesting, right? More importantly, this program would examine your passion and capability to become a Data Scientist. No pain no gain. Hold tight. This would be the boundary that separates you from other 85% Python/Data Science learners.

In fact, I had also taken many other courses on Coursera and EdX in order to gain in-depth knowledge in the fields of artificial intelligence and deep learning. Most of them are quite mathematical and technical, which could be a bit hard if you are not a science person. Below are some useful and interesting choices.

  • Machine Learning Specialization offered by Standford University and DeepLearning.AI, and instructed by the famous Andrew Ng

  • Deep Learning Specialization offered by DeepLearning.AI

  • Python for Data Science Projects offered by IBM

  • CS50’s Introduction to Artificial Intelligence with Python offered by Harvard University

If you are able to finish the Michigan’s Applied Data Science Program and 1 to 2 more specialization courses, you are definitely an intermediate user of Python for Data Science now. (Of course, only if you can remember most of the content and are familiar with the concepts and programming work.) Now, you should have the confidence to write on CV — Python (Intermediate) and add some famous data science certificates.

Ready for job application? Yes or No.

  • Yes, if you are looking for a Data Analyst role in a non-IT company that mainly focuses on data processing and visualization.

  • No, if you aim at Data Scientist/Data Engineer position which requires stronger programming foundation and some backend knowledge.

For the learning journey from Advanced to Master level, please refer to the next article here.