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Welcome to the Data Science Specialization using R!

The Beginner’s Guide to the Data Science Specialization using R!

In my first video, I introduced the learners to the Data Science Specialization using R. I have covered topics such as data manipulation, data visualization, statistical inference, and machine learning. I have also talked about the importance of using R in data science and the benefits of the Data Science Specialization. You are now ready to dive deeper into the world of data science with R and learn from my expertise. If you haven't watched my first video please find it below:



Course Dependency Table:

To help my viewers better understand the structure and dependencies of the Data Science Specialization using R, I have provided a course dependency table. This table will show which courses build upon the knowledge learned in previous courses and which courses are prerequisites for others.

For the courses, we consider two forms of dependency:

  • Hard dependency: Students will be required to know material from the prerequisite course. Taking the dependent course simultaneously will be challenging and only possible for highly motivated students willing to work ahead of the course schedule for the prerequisite. Taking hard dependent courses out of order is not possible unless the student already knows the material covered in the prerequisite course.
  • Soft dependency: Knowledge of material from the prerequisite course is recommended and useful. Concurrently taking the prerequisite course and the dependent course is possible. It is not recommended to take them out of order, but would be possible for highly motivated students willing to self-teach components of the prerequisite course as needed. 

Course Number

Course Name

Soft Dependency

Hard Dependency

1.

Data Scientist Toolbox

 

 

2.

R Programming

1.       Data Scientist Toolbox

 

3.

Getting and Cleaning Data

 

1.       Data Scientist Toolbox

2.       R Programming

4.

Exploratory Data Analysis

 

1.       Data Scientist Toolbox

2.       R Programming

5.

Reproducible Research

 

1.       Data Scientist Toolbox

2.       R Programming

6.

Statistical Inference

 

1.       Data Scientist Toolbox

2.       R Programming

7.

Regression Models

 

1.       Data Scientist Toolbox

2.       R Programming

3.       Statistical Inference

8.

Machine Learning

1.       Exploratory Data Analysis

1.       Data Scientist Toolbox

2.       R Programming

3.       Regression Models

9.

Data Products

1.       Exploratory Data Analysis

1.       Data Scientist Toolbox

2.       R Programming

3.       Reproducible Research

10.

Capstone Projects

All Courses

All Courses

This table will help you understand the order in which you should take the courses and how each course builds upon the knowledge gained from the previous one.


Subscribe to my social media accounts:

If you have enjoyed my first video and want to see more, you can subscribe to my social media accounts. This way, you will receive updates whenever I release a new video or post.


Here are the links to my social media accounts:




Conclusion:

In this blog post, we introduced our first video, discussed the course dependency table, and provided links to your social media accounts. We hope that you will find this information useful and continue to learn from our expertise. Best of luck with your data science journey!


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