How-to's

Want to pick up data science? Brush up on your math first

William Chen, a data scientist at Quora, the question-and-answer platform, said, “For any aspiring data scientist, I would highly recommend learning statistics with a heavy focus on coding up examples, preferably in Python or R.” So if you’re considering picking up data science online, but are feeling a little shaky with your stat skills, here are a couple of introductory courses to get you started.

It's easy to get lost looking for an introductory course to online. There are thousands of courses, and tens of open courseware websites. So we composed a minimalist list of introductory statistics courses that you can take with little to no previous knowledge. The courses are on-demand every few months and are substantial in content. They're interactive so you don't need any books or read-only tutorials, and get teach through coding up examples, i.e. R or Python. Let's dig in.

1. Foundations of data analysis on edX

This two-part series (Part 1 covers Statistics using R and Part 2 teaches Inferential Statistics) is one of the top reviewed statistics courses available, with a weighted average rating of 4.48 out of 5 stars. This is one of the few courses with high ratings that teaches statistics with a focus on coding up examples. It also covers a lot of probability content, and is a great mix of fundamentals for the beginner data scientist.

Price: Free

Estimated duration: 6 weeks at 3-6 hours per week for each course

2. Introduction to probability—The science of uncertainty on edX

With a rating of 4.91 out of 5 stars, if you want to dive deeper into the world of probability, this is the course for you. Don't let its name fool you, this course is a challenge and much longer than most online courses. While the level at which the e-course covers probability is not necessary a beginner data scientist, the contents are essentially the same as the corresponding courses taught in MIT over the past 50 years, and teach probabilistic models, inference methods, random processes, and more. Added bonus: The teachers are both professors in the Department of Electrical Engineering and Computer Science at MIT!

Price: Free

Estimated duration: 18 weeks at 12 hours per week

3. I "heart" stats: Learning to love statistics on edX

With no coding involved, University of Notre Dame's intro to stat course targets a non-technical audience, making it good for anybody. The course design and instructors are fun, using entertaining examples related to real-life situations we all encounter in everyday life. The professors quip, "If you can add, subtract, multiply, and divide (or just be able to use a calculator to do that!), you will be more than able to handle what will happen as this relationship develops."

By the end of the course, students are promised to be able to identify the most important features of a data set, select statistical tests, think like a detective, and understand the relationship between different variables.

Price: Free

Estimated duration: 9 weeks at 4-6 hours per week

 

The writer is In-charge of the career publication of The Daily Star.

Comments

Want to pick up data science? Brush up on your math first

William Chen, a data scientist at Quora, the question-and-answer platform, said, “For any aspiring data scientist, I would highly recommend learning statistics with a heavy focus on coding up examples, preferably in Python or R.” So if you’re considering picking up data science online, but are feeling a little shaky with your stat skills, here are a couple of introductory courses to get you started.

It's easy to get lost looking for an introductory course to online. There are thousands of courses, and tens of open courseware websites. So we composed a minimalist list of introductory statistics courses that you can take with little to no previous knowledge. The courses are on-demand every few months and are substantial in content. They're interactive so you don't need any books or read-only tutorials, and get teach through coding up examples, i.e. R or Python. Let's dig in.

1. Foundations of data analysis on edX

This two-part series (Part 1 covers Statistics using R and Part 2 teaches Inferential Statistics) is one of the top reviewed statistics courses available, with a weighted average rating of 4.48 out of 5 stars. This is one of the few courses with high ratings that teaches statistics with a focus on coding up examples. It also covers a lot of probability content, and is a great mix of fundamentals for the beginner data scientist.

Price: Free

Estimated duration: 6 weeks at 3-6 hours per week for each course

2. Introduction to probability—The science of uncertainty on edX

With a rating of 4.91 out of 5 stars, if you want to dive deeper into the world of probability, this is the course for you. Don't let its name fool you, this course is a challenge and much longer than most online courses. While the level at which the e-course covers probability is not necessary a beginner data scientist, the contents are essentially the same as the corresponding courses taught in MIT over the past 50 years, and teach probabilistic models, inference methods, random processes, and more. Added bonus: The teachers are both professors in the Department of Electrical Engineering and Computer Science at MIT!

Price: Free

Estimated duration: 18 weeks at 12 hours per week

3. I "heart" stats: Learning to love statistics on edX

With no coding involved, University of Notre Dame's intro to stat course targets a non-technical audience, making it good for anybody. The course design and instructors are fun, using entertaining examples related to real-life situations we all encounter in everyday life. The professors quip, "If you can add, subtract, multiply, and divide (or just be able to use a calculator to do that!), you will be more than able to handle what will happen as this relationship develops."

By the end of the course, students are promised to be able to identify the most important features of a data set, select statistical tests, think like a detective, and understand the relationship between different variables.

Price: Free

Estimated duration: 9 weeks at 4-6 hours per week

 

The writer is In-charge of the career publication of The Daily Star.

Comments