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I'm excited to share with you another degree program that is similar to the Computer Science Degree Program we discussed earlier. This program is offered by the Open Source Society University and is completely free.

The ossu/data-science curriculum is designed for learners who are self-motivated and interested in exploring the world of Data Science at their own pace. The program provides a comprehensive undergraduate curriculum in Data Science by using courses from some of the world's top universities. Best of all, there is no financial burden for learners who enroll in this program.

Curriculum

The program curriculum includes all the necessary and optional courses that you need to master data science and prepare for your professional life. The data science program focuses on theory, mathematics, algorithms, statistics, and data science tools. Here is the complete list of the topics that we will be covering in this program:

1. Introduction to Data Science: Understanding the basics and scope of Data Science.
2. Introduction to Computer Science: Essential for beginners; those proficient in any programming language can skip this.
3. Programming Courses:
   1. Python for Everybody
   2. Introduction to Computer Science and Programming Using Python
   3. Introduction to Computational Thinking and Data Science
4. Data Structures and Algorithms: Taught in Java (Java Programming, Algorithms, Part I & II).
5. Databases: From Database Management Essentials to MongoDB for Developers.
6. Mathematics: Including Single Variable Calculus, Linear Algebra, and Multivariable Calculus.
7. Statistics & Probability: Courses cover descriptive to inferential statistics.
8. Data Science Tools & Methods: Tools for Data Science, Data Science Methodology, Data Wrangling.
9. Machine Learning/Data Mining: Courses range from introductory to specialized topics like Process Mining.

⚠️Disclaimer

This program does not grant an official degree upon completion. It is a self-taught curriculum based on freely available resources, including videos, code examples, and quizzes. Participants do not need to enroll formally; all materials and guidelines are accessible through the designated GitHub repository https://github.com/ossu/data-science. This program is structured to provide an extensive learning experience similar to a Data Science degree; however, it is unofficial and does not grant academic accreditation or recognition from educational institutions.

How to Get Started

1. Duration and Planning

You can complete the program in 2 years if you allocate around 20 hours per week for studies. To help you plan, use this spreadsheet to estimate your end date. Simply input your start date and weekly study hours in the Timeline sheet. You can keep track of your progress by updating the Curriculum Data sheet with the completion date of each course.

2. Order of Classes

You need to understand that some courses can be tackled simultaneously, while others need to be done one after the other. You can view the provided graph to understand the sequence of topics and courses.

Image from ossu/data-science

3. Tracking Your Progress

Create a Trello account and copy the provided board to your account. You can find instructions on how to do this here. After that, move cards to the 'Doing' or 'Done' columns as you progress through your courses.

4. Choice of Programming Languages

Python, R, and SQL are the primary programming languages used in the data science community. The curriculum covers all three of these languages, but it is important to note that one should focus on understanding core concepts rather than just the language itself. These fundamental concepts need to be thoroughly understood so that they can be applied using any programming tool.

5. Prerequisites

A prerequisite for this course is a basic understanding of math and statistics at the high school level.

Conclusion

Enrolling in a free Data Science undergraduate program is an excellent starting point, but it's important to remember that this is just the beginning. Becoming the highly sought-after 'super data scientist' requires more than just coursework. It demands dedication to expanding your knowledge through specialized topics, actively engaging in projects, and gaining practical experience through internships. You must be willing to build your career step by step, laying a solid foundation with each new skill and experience.

By adhering to this structured and focused program, you are setting yourself on a path toward mastering Data Science. Remember, the journey towards becoming a proficient data scientist is as important as the destination. Embrace and enjoy your learning process as each step brings you closer to achieving your professional goals in this exciting and ever-evolving field.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology management and a bachelor's degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.