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Data Analytics in Bioinformatics

BIF600

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BIF600 - Data Analytics in Bioinformatics

Course 1: Programming Essentials - BIF601

First course in the Data Analytics in Bioinformatics program.

Knowing how to program will allow a bioinformatics researcher to write code to manage and analyze data sets. This seven-week course will teach the fundamentals of the Python programming language. The Python language has been chosen for its easy-to-learn nature and its widespread use in bioinformatics and related industries. The course will commence by teaching basics such as variables and types, conditionals and loops followed by more advanced topics like object-oriented code, methods and libraries.

Course 2: Intro to Data Modelling - BIF602

Second course in the Data Analytics in Bioinformatics program.

This course focuses on introducing students to the fundamentals of data modelling. Students will get familiar with different data storage models, learn to manipulate data using SQL and get an overview of currently existing biological databases. Further into the course, students will get exposed to the statistics principles helpful in data analysis, as well as machine learning fundamentals. Students will also cover the most popular ML algorithms and modelling best practices in depth. The course goal is to equip students with a solid base to be able to handle data science projects end-to-end.

Course 3: Bioinformatic Methodology - BIF603

Third and final course in the Data Analytics in Bioinformatics program.

In this collaborative and interactive course, students will gain a professional insight into the methodologies that are widely used by bioinformatics experts to understand biological data. By exploring different data types, students will be introduced to the basic problems and objectives common in the bioinformatics field, as well as the skills and tools that a bioinformatics scientist/analyst needs in order to accomplish these objectives.

Upon successful completion of all three courses within the program, students will receive a certificate of completion.

System Requirements:

  • Processor: At least a dual-core, 64-bit processor
  • RAM: 4GB of RAM, with 8GB recommended
  • Disk Space: 20GB or more free space
  • Operating System (one of the following):
    • Windows 8.1 or newer (64-bit)
    • macOS 10.13 or newer (64-bit)
    • Any 64-bit Linux system

For more information, please contact Teresa Artuso at teresa.artuso@senecapolytechnic.ca.


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