When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

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.

Fundamental Skills in Bioinformatics

Ends tomorrow! Save on skills that make you shine with 40% off 3 months of Coursera Plus. Save now

King Abdullah University of Science and Technology

Fundamental Skills in Bioinformatics

Name: Fundamental Skills in Bioinformatics
Rating: 4.365591397849462 (93 reviews)

Instructors: Jesper Tegner

15,344 already enrolled

Included with

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

93 reviews

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

93 reviews

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Basics of R
Basics of Python
How to analyze bulk RNAseq count data
How to analyze single cell RNAseq count data

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

There are 4 modules in this course

The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.

Module details

The first module will explore the basics of programming through R and this will include: working in R and RStudio, understanding data types, loops and ifs. Additionally, the module will provide an introduction to RMarkDown as a tool for sharing code that we will use in the coding lectures.

What's included

17 videos2 readings4 assignments

17 videosTotal 123 minutes

Brief introduction to the course2 minutes
Lecture: Programming and R4 minutes
Lecture: Introduction to RStudio3 minutes
Coding Lecture: First contact with RStudio9 minutes
Introduction1 minute
Lecture: Data types in R3 minutes
Lecture: Data structures in R6 minutes
Coding Lecture: Data types in R - atomic and vectors 15 minutes
Coding Lecture: Data types in R - lists and matrices17 minutes
Coding Lecture: Data types in R - data frames7 minutes
Lecture: Introduction to Control Flow4 minutes
Lecture: Loops4 minutes
Coding Lecture: If statements9 minutes
Coding Lecture: loop statements9 minutes
Lecture: Loading and Writing6 minutes
Coding Lecture: Loading and Writing18 minutes
Basics + where to learn more5 minutes

2 readingsTotal 40 minutes

Setting up R30 minutes
Available data sets to be used in the course.10 minutes

4 assignmentsTotal 95 minutes

Introduction to R Quiz20 minutes
Data Types in R Quiz15 minutes
Control Flow in R Quiz30 minutes
Loading and Writing in R Quiz30 minutes

The second module will focus on two aims. Firstly, to master the use of logical values and vectors and its applications in quality control. Secondly, to practice the programming skills while learning how to perform basic statistical analysis. This will include: explorative data analysis, correlation, linear models, T-test, and ANOVA. Finally, we will explore the available resources for R programming.

What's included

20 videos1 reading2 assignments6 programming assignments

20 videosTotal 162 minutes

Introduction to Module 21 minute
Lecture: Logical values, logical vectors and operations with them.6 minutes
Coding Lecture: Logical Vectors, part 1.11 minutes
Coding Lecture: Logical Vectors, part 2.7 minutes
Lecture: Data Quality Control.3 minutes
Coding Lecture: Quality Control.6 minutes
Lecture: Exploratory Data Analysis.8 minutes
Coding Lecture: EDA part 1.9 minutes
Coding Lecture: EDA part 2.8 minutes
Lecture: Correlation12 minutes
Coding Lecture: correlation in R6 minutes
Lecture: Linear Models8 minutes
Coding Lecture: example of a linear model6 minutes
Coding Lecture: evaluation of a linear model in R6 minutes
Lecture: t-test & ANOVA19 minutes
Coding Lecture: t-test.8 minutes
Coding Lecture: ANOVA7 minutes
Introduction to the dataset: Data set 4.3 minutes
Guided analysis.26 minutes
Lecture: R packages4 minutes

1 readingTotal 10 minutes

How do R programming assignments work?10 minutes

2 assignmentsTotal 40 minutes

Exploratory Data Analysis and Visualization in R30 minutes
Programming Assignment Basics Quiz10 minutes

6 programming assignmentsTotal 345 minutes

Operating with logical values and matrices180 minutes
Quality control of the data 45 minutes
Correlation analysis30 minutes
Linear models30 minutes
t-test and ANOVA30 minutes
First analysis of an expression dataset.30 minutes

The third module will provide the basics of the Python programming language. First, the module will compare Python and R language and learn the programming syntax of Python. Second, the module will work with two key Python modules: pandas and numpy.

What's included

19 videos1 reading4 assignments4 programming assignments1 ungraded lab

19 videosTotal 151 minutes

Introduction to the module2 minutes
Lecture: Python and R2 minutes
The Python ecosystem11 minutes
Python installation and environments21 minutes
Jupyter Lab18 minutes
Lecture: Python native data structures2 minutes
Coding Lecture: Fundamentals in data types9 minutes
Coding Lecture: Lists and Tuples 9 minutes
Coding Lecture: Sets and Dictionaries8 minutes
Lecture: flow control and functions.1 minute
Coding Lecture: if conditions, for and while loops.17 minutes
Coding Lecture: declare and using functions in Python6 minutes
Lecture: overview of modules in Python2 minutes
Lecture: numpy1 minute
Coding Lecture: numpy10 minutes
Lecture: pandas1 minute
Coding Lecture: pandas14 minutes
Coding lecture: pandas for data exploration9 minutes
Coding Lecture: Visualization9 minutes

1 readingTotal 3 minutes

Free online Python resources3 minutes

4 assignmentsTotal 40 minutes

Python primitive values and data structures10 minutes
Python syntax: for, if statements and functions10 minutes
The numpy package10 minutes
The pandas package10 minutes

4 programming assignmentsTotal 120 minutes

Python data structures30 minutes
Python control flow30 minutes
The NumPy package30 minutes
The pandas package30 minutes

1 ungraded labTotal 45 minutes

Visualization with the pandas package45 minutes

The final module will focus on applying knowledge and understanding of programming in the analysis of real RNA-seq data. R will be used for analysing of bulk RNA-seq and Python for single- cell RNA-seq. The results of both analyses will then be integrated. Finally, the module will provide insights in how to gain deeper knowledge and skills in R.