Python for Genomic Data Science

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Python for Genomic Data Science

This course is part of Genomic Data Science Specialization

Instructors: Mihaela Pertea, PhD

76,061 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

1,814 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

89%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

1,814 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

89%

Most learners liked this course

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

9 assignments

Taught in English

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This course is part of the Genomic Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.

This week we will have an overview of Python and take the first steps towards programming.

What's included

5 videos3 readings2 assignments

5 videosTotal 58 minutes

Lecture 1: Overview of Python13 minutes
Lecture 2.1 - First Steps Toward Programming Part 111 minutes
Lecture 2.2 - First Steps Toward Programming Part 215 minutes
Lecture 2.3 - First Steps Toward Programming Part 3 (8:57)9 minutes
Lecture 2.4 - First Steps Toward Programming Part 4 (9:58)10 minutes

3 readingsTotal 30 minutes

Welcome10 minutes
Pre-Course Survey10 minutes
Syllabus10 minutes

2 assignmentsTotal 36 minutes

Lecture 1 Quiz6 minutes
Lecture 2 Quiz30 minutes

In this module, we'll be taking a look at Data Structures and Ifs and Loops.

What's included

4 videos2 assignments

In this module, we have a long three-part lecture on Functions as well as a 10-minute look at Modules and Packages.

What's included

4 videos2 assignments

In this module, we have another long three-part lecture, this time about Communicating with the Outside, as well as a final lecture about Biopython.

What's included

4 videos2 readings3 assignments

4 videosTotal 46 minutes

Lecture 7.1: Communicating with the Outside Part 1 (6:41)7 minutes
Lecture 7.2: Communicating with the Outside Part 2 (7:38)8 minutes
Lecture 7.3: Communicating with the Outside Part 3 (17:42)18 minutes
Lecture 8: Biopython (13:32)14 minutes

2 readingsTotal 20 minutes

Final Exam Instructions10 minutes
Post Course Survey10 minutes

3 assignmentsTotal 90 minutes

Lecture 7 Quiz30 minutes
Lecture 8 Quiz30 minutes
Final Exam (Read Instructions First)30 minutes

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Instructors

Instructor ratings

(254 ratings)

Mihaela Pertea, PhD

Johns Hopkins University

1 Course76,061 learners

Offered by

Johns Hopkins University

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Showing 3 of 1814

Reviewed on May 24, 2020

First 2 week just python basic learning which I had already learned and its advantage for me.Got more skills from my acceptation.Looking forward advance course also

Reviewed on Jul 14, 2022

It was easy in the beginning but gets hard and changing at the end.It was such an honor th have a course with Professor Salzburg.I would recommend it to all bioinformatics lovers.

Reviewed on Mar 13, 2016

The lectures were really good. I am a microbiologist and have very little background of computer programming. A more detailed course would have he

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Frequently asked questions

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When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.