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Introduction to Python for genetics

Many students and professionals of biosciences are not familiar with programming. However, the increasing amount of biological data generated every year, along with advances in biotechnology and the increasing role of informatics in life sciences makes the programming knowledge essential for biologists, biotechnologists, and so on. In this introductory course, you will learn how to model simple genetics problems using the programming language Python. First, you will learn how to implement the commands or data structures in Python. And Finally, we will model some problems in the field of genetics using the knowledge acquired so far.

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Many students and professionals of biosciences are not familiar with programming. However, the increasing amount of biological data generated every year, along with advances in biotechnology and the increasing role of informatics in life sciences makes the programming knowledge essential for biologists, biotechnologists, and so on. In this introductory course, you will learn how to model simple genetics problems using the programming language Python. First, you will learn how to implement the commands or data structures in Python. And Finally, we will model some problems in the field of genetics using the knowledge acquired so far.

Since this is an introductory course, we will not use third-party libraries, such as Biopython, matplotlib, pandas, etc., but only the built-in commands, modules, and data structures.

In the first section of the course, we have a very brief introduction to refresh some concepts of genetics, such as genes, alleles, frequency, etc... In the second part of the course, you'll learn the basic commands, data structures, and functions of Python. In these chapters, you must apply the knowledge acquired so far in the chapter to solve some problems related to genetics in Python. There are more than 20 exercises and challenges to be solved throughout the course.

Therefore, if you want to:

  1. Learn to think algorithmically

  2. Model problems of genetics in a programming language

  3. Learn how to use the most popular programming languages to model problems of biology

...this course is for you.

Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops programming knowledge essential for professionals in life sciences
Taught by instructors who are experts in biology and programming
Teaches Python, a popular programming language for modeling biological data
Builds a strong foundation in programming for beginners in genetics
Suitable for students and professionals in the fields of biosciences and biotechnology

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Career center

Learners who complete Introduction to Python for genetics will develop knowledge and skills that may be useful to these careers:
Bioinformatician
As a bioinformatician, your job is to analyze biological data to extract meaningful information. Using your programming skills, you can develop computational tools for data visualization, statistical analysis, and pattern recognition. This course provides a solid foundation in Python, which is commonly used in bioinformatics. The exercises and challenges will help you build proficiency in using Python for genetic data analysis and modeling.
Computational Biologist
Computational biologists are responsible for developing and applying computational techniques to solve problems in biology and medicine. With your knowledge of Python, you can create models and simulations to analyze biological systems, discover new patterns, and make predictions. This course will help you gain the skills necessary to use Python effectively for computational biology.
Biostatistician
Biostatisticians use statistical methods to design and analyze studies in the field of biology. With your programming skills, you can develop statistical models and analyze large datasets to identify patterns and trends. This course will help you gain the skills necessary to use Python for statistical analysis in the field of genetics.
Genetic Counselor
Genetic counselors provide information and support to individuals and families affected by genetic disorders. Having a background in programming can be beneficial in this field, as it can help you better understand the complex genetic data and interpret the results of genetic tests. This course will help you gain the skills necessary to use Python for analyzing genetic data and modeling genetic risk.
Data Scientist
Data scientists use their programming skills to extract insights from data. In the field of genetics, you can use Python to analyze genetic data, develop predictive models, and identify patterns. This course will introduce you to the basics of Python programming and its applications in the field of genetics.
Research Scientist
As a research scientist in the field of genetics, you can use your programming skills to analyze data, develop models, and design experiments. This course will provide you with a strong foundation in Python programming, which is widely used in genetic research. The hands-on exercises and challenges will help you build proficiency in using Python for genetic data analysis and modeling.
Software Engineer
As a software engineer, you can use your programming skills to develop software solutions for various industries, including biotechnology and healthcare. This course will introduce you to Python programming and its applications in genetics. You will learn how to use Python to analyze genetic data, develop predictive models, and identify patterns.
Technical Writer
As a technical writer in the field of genetics, you can use your programming skills to create user manuals, white papers, and other technical documents. This course will introduce you to Python programming and its applications in genetics. You will learn how to use Python to analyze genetic data and create clear and concise documentation.
Science Teacher
In your role as a science teacher, you will need to teach students the fundamentals of genetics, including the role of programming in the field. This course will provide you with a strong foundation in Python programming, which is widely used in genetic research. The hands-on exercises and challenges will help you build proficiency in using Python for genetic data analysis and modeling.
Science Writer
As a science writer, you can use your programming skills to create articles, blog posts, and other types of written content about genetics. This course will introduce you to Python programming and its applications in genetics. You will learn how to use Python to analyze genetic data and communicate your findings to a non-technical audience.
Quality Assurance Analyst
Quality Assurance Analysts are responsible for testing software to ensure that it meets the required standards. This course will introduce you to Python programming and its applications in the field of genetics. You will learn how to use Python to analyze genetic data and identify any potential errors or defects.
Business Analyst
Business Analysts are responsible for gathering and analyzing data to identify opportunities for improvement within an organization. This course will introduce you to Python programming and its applications in the field of genetics. You will learn how to use Python to analyze genetic data and identify trends and patterns that can be used to make informed business decisions.
Consultant
Consultants provide advice and guidance to organizations on a variety of topics. In the field of genetics, you can use your programming skills to help organizations analyze genetic data and develop strategies for improving health outcomes. This course will introduce you to Python programming and its applications in the field of genetics.
Healthcare Administrator
Healthcare Administrators are responsible for managing the operations of healthcare organizations. This course will introduce you to Python programming and its applications in the field of genetics. You will learn how to use Python to analyze genetic data and identify trends and patterns that can be used to improve the efficiency and effectiveness of healthcare delivery.
Marketing Manager
Marketing Managers are responsible for developing and implementing marketing campaigns. This course will introduce you to Python programming and its applications in the field of genetics. You will learn how to use Python to analyze genetic data and identify trends and patterns that can be used to develop targeted marketing campaigns.

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Python for genetics.
Comprehensive guide to deep learning with Python. It covers a wide range of topics, from convolutional neural networks to recurrent neural networks.
Is an excellent resource for learning how to use Python for biological data analysis. It covers a wide range of topics, from basic programming concepts to more advanced topics like machine learning.
This textbook is tailored towards teaching Python proramming language to students and professionals in fields such as bioinformatics, computational biology, and genomics.
Comprehensive guide to machine learning with Python. It covers a wide range of topics, from supervised learning to unsupervised learning.
Great resource for learning how to use Python for data science. It covers topics such as data cleaning, data manipulation, and data visualization.
Great resource for learning how to use Python for data analysis. It covers topics such as data cleaning, data manipulation, and data visualization.
Great resource for learning how to use Python for scientific computing. It covers topics such as numerical methods, data analysis, and visualization.
Great resource for learning how to use Python for automating tasks. It covers topics such as web scraping, data mining, and text processing.
Fun and engaging way to learn Python. It uses a visual approach to teaching, which makes it easy to understand complex concepts.
This classic textbook provides a comprehensive overview of genetic principles and their application to modern biology.
This textbook comprehensive introduction to genetic analysis, covering topics such as Mendelian inheritance, population genetics, and molecular genetics.
Provides a comprehensive overview of bioinformatics, covering topics such as sequence alignment, gene expression analysis, and protein structure prediction.

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