Are you interested in learning how to program (in Python) within a scientific setting?
This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our BioinformaticsSpecialization(https://www.coursera.org/specializations/bioinformatics), preparing learners to take the first course in the Specialization, “Finding Hidden Messages in DNA” (https://www.coursera.org/learn/dna-analysis). Each of the four weeks in the course will consist of two required components. First, an interactive textbook provides Python programming challenges that arise from real biological problems. If you haven’t programmed in Python before, not to worry! We provide “Just-in-Time” exercises from the Codecademy Python track (https://www.codecademy.com/learn/python). And each page in our interactive textbook has its own discussion forum, where you can interact with other learners. Second, each week will culminate in a summary quiz. Lecture videos are also provided that accompany the material, but these videos are optional.
Course Description
Bioinformatics for Beginners: Biology Meets Programming
Provider
Coursera
Target
• Beginners in Python
• Bioinformaticians
• Computational biologists
Sector
• Bioinformatics
• Biotechnology
• Computational biology
Area
• Python programming for biological data analysis
• Algorithm implementation in bioinformatics
Method
Certification
Duration
Assessment
Learning Outcomes
• Understanding Python Programming Concepts: Ability to write Python code to solve various biological problems, even if you have no prior programming experience.
• Solving Biological Problems with Algorithms: Ability to implement algorithms for analyzing biological data, such as DNA sequence analysis, string matching, and feature computation.
• Working with Biological Data: Ability to process and analyze different types of biological data (e.g., DNA sequences, genome data) and extract meaningful information using Python programming.
• Mastering Advanced Bioinformatics Algorithms: Understanding how to use advanced data structures and algorithms, such as Hidden Markov Models, to solve complex bioinformatics problems.
• Solving Programming Challenges in Biology: Strengthening programming skills through weekly challenges based on real-world biological problems.
• Familiarity with Bioinformatics Tools and Libraries: Ability to utilize bioinformatics libraries like Biopython to perform complex analyses and manage biological datasets.
• Preparation for Advanced Courses: Ready to advance to specialized courses in bioinformatics, such as “Finding Hidden Messages in DNA.
Learning Content
• Week 1: Introduction to Python and Biological Algorithms
• Week 2: Working with Biological Data
• Week 3: Analyzing Genetic Sequences
• Week 4: Data Structures and Algorithms for Bioinformatics