Free Courses To Become A Data Scientist

There are so many resources out there nowadays that claim they will make you a data scientist. When I first started taking classes online, it took me a while to understand which courses are good. I started one course, then after a few days or weeks realized that it is not helpful. Again moved to something else. I wish I could find a solid guide that will tell me what exactly to study, where to start, and how to carry out the learning journey. Though I found some material but still I had to struggle a lot. That’s why I decided to share a total study and course plan that will eventually give you enough knowledge to find a job as a data scientist. And the best part is, it is free!

I am going to show a pathway to become a Data Scientist in Python only. Because I am a python user and I like it. Also, I believe if you are a beginner, it is good to learn one language very well. Then move on to learn more. Here is the step by step free study plan:

1. Learn Python

If you do not know Python, this free course is a good start. Udacity has this free course ‘Intro To Computer Science’ that teaches python programming language with lots of examples and practice problems which is very good for beginners. Unfortunately, if you go to Udacity’s home page and search for it, it redirects you to another course now. But luckily, in this link, you will be still able to find all the materials.

This Python course should give you enough knowledge to start learning data science tools.

2. Learn Data Science Libraries of Python

Coursera has a wide range of courses where you can learn for free. It is a blessing for learners. They have a specialization “Applied Data Science With Python” by the University of Michigan. It contains the following five courses:

a. Introduction to Data Science in Python

b. Applied Plotting, Charting & Data Presentation in Python

c. Applied Machine Learning in Python

d. Applied Text Mining in Python

e. Applied Social Network Analysis in Python

I just need to warn you about one thing. If you choose to take these courses, you have to keep patience. Because the assignments are hard, especially if you are a beginner. You just need to keep trying and do your best. But because the assignments are hard, you will really learn the material very well, if you can do the assignments. You just need to spend enough time on it. You do not need to pay anything, if you do not want a certificate and learn only. You can audit all the courses for free.

Here is the instruction to find the audit option. Do not enroll in the specialization page. It is free only for 7 days. Go to the individual course’s page. Then you will see an enroll option at the top of the page. Do not even enroll from there. Keep scrolling down on the individual course’s page. You will find another enroll option after each week’s curriculum discussion and faculty information. Click on that enroll option a window will open and at the bottom of it you will see a very small ‘audit’ option. Click on that audit option and enroll from there. Even if you cannot finish on time you can audit it again. You can audit a course as many times as you want. Here is a video that walks you through the process:

3. Learn SQL

SQL is one of the essentials for data analysts or data scientists. If you finished course one of the specializations above, learning SQL should be easy. There are some common ideas. Here is a specialization that teaches you enough SQL to start as a data scientist:

This specialization has four courses:

a. SQL for data science

b. Data Wrangling, Analysis, and AB Testing with SQL

c. Distributed Computing With Spark SQL

d. SQL for Data Science Capstone Project

I already explained how you can audit these courses before.

4. Learn More

After taking the courses above you will be ready to apply for the jobs. You will find many opportunities where you will be a good fit. But there is a lot more to learn if you want to advance in data science. For example, it is good to know some statistical concepts while you are dealing with data. The applied machine learning course in step 2 above teaches you, how to use a machine learning library scikit-lean which is very good. It gives the basic concepts of a lot of machine learning algorithms and you can use them by calling them from the scikit-learn library. It works in a lot of problems. But still learning to write the algorithms from scratch will give you more power. Here are the links to one statistics specialization course and a machine learning course:

Statistics With Python

Machine Learning

It may look like a lot for a beginner. But remember you do not have to learn everything in a day. Whenever you are changing career or starting something new, it will take time. If you can do the data science specialization mentioned in step 2 then learning SQL will be very easy and fast. So, it is not as hard as it looks. Just one more tip. It is a lot easier to stay motivated and patient when you have a good learning partner. Probably you already know it, just a reminder.

#datascientist #freelearning #becomeADataScientist #machinelearning #sql

This Post Has 2 Comments

  1. Thanks for this article. It's helpful. However, I am finding it difficult to follow your guide on how to enroll on the individual course's page on Coursera.

    1. Hello Ogah, Please check I added a video in the article now that walks you through the process. I hope it will help

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