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Python for Genomic Data Science

Steven Salzberg, PhD and Mihaela Pertea, PhD

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.

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What's inside

Syllabus

Week One

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

Week Two

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

Week Three

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

Week Four

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces Python programming and iPython notebook, which are indispensable tools in the field of genomic big data analysis

Taught by Steven Salzberg and Mihaela Pertea, both recognized researchers in genomic big data science, ensuring the relevance and credibility of the content

Covers essential concepts in Python programming, empowering learners to contribute to the field of genomic big data science

Delves into data structures, conditional statements, loops, functions and more in Python programming, providing a comprehensive understanding of Python for genomic big data analysis

Includes a module on Biopython, a widely used library for biological data analysis, equipping learners with practical skills for the field of genomic big data science

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Reviews summary

Genomics data science python

Learners say that this course is a great introduction to Python for anyone who wants to learn how to use it for genomic data science. The Python-based course includes lectures, readings, and exams that cover everything from basic Python concepts to more advanced topics like using Biopython. Although the sentiment towards this course is largely positive, some learners with no prior Python experience found it difficult and didn't feel like there was enough instruction or guidance. But for those with Python experience, the final exam is highly regarded as a good challenge. Overall, this course is a good choice for biologists and bioinformaticians who want to learn how to use Python and Biopython for genomic data science.

Instructors are knowledgeable and passionate about the subject.

"Excellent course, lectures introduce you many Python topics. By the time of the final exam my programming skills had improved greatly. "

Assignments and deadlines help with time management.

"It was an Excellent Program for me. I learned deeper knowledge for analysing DNA strings, Inclduing Bipython"

Engaging assignments challenge even experienced learners.

"The course was very insightful. I got my concept of Python basics cleared. "

Python skills are useful for genomic data science.

"This was an amazing course. I learned a lot from this course."

"It would have been awesome if Biopython was elaborated on more."

"this is a highly recommended course to become good at python for biology"

The course assumes some prior knowledge of programming, which may not be suitable for complete beginners.

"But for those with Python experience, the final exam is highly regarded as a good challenge."

The quizzes are more difficult than the material covered in the lectures.

"This course teaches you basics only, but when the questions are asked in the quiz they are no where related to what has been taught, and the level of difficulty of those questions is really high."

The final exam is challenging and requires more knowledge than what is taught in the course.

"The final exam was by orders of magnitude more difficult than what the lectures covered."

"I think the lectures do not provide enough guidance or knowledge to complete the assignments, instead, a lot of extra work and research is needed from your end."

Instructors could be more engaging and clear in their explanations.

"The difficulty of the final exam is not compatible with the quality of the given classes, and the lack of exercises focused in Genomic Data Science makes the material a normal programming course."

The course is not beginner-friendly and requires some prior knowledge of Python.

"I went through this course while doing the genomics specialisation. Though I know Python, I went through it just to complete the certification. I understand that the lectures are beginner level, but they are quite dull and tedious to go through."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python for Genomic Data Science with these activities:

Review basic programming concepts

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Revisiting basic programming concepts will provide a solid foundation for learning Python.

Browse courses on Programming

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Go through online tutorials or textbooks that cover programming basics.
Practice writing simple programs to reinforce your understanding.

Read 'Python Crash Course, 2nd Edition'

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This book provides a comprehensive introduction to Python programming, covering essential concepts and practical applications.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

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Purchase or borrow the book.
Set aside time for reading and taking notes.
Work through the exercises and projects included in the book.
Summarize key concepts and refer back to the book as needed.

Form a study group with classmates

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Collaborative learning can enhance your comprehension and provide support throughout the course.

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Identify classmates who are interested in forming a study group.
Establish regular meeting times and a study schedule.
Review course material together, discuss concepts, and solve problems collaboratively.
Provide support and encouragement to group members.

Four other activities

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Practice Python programming exercises

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Practice through drills will help to reinforce the Python programming skills learned in this course.

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Identify an online Python coding exercise resource.
Set aside time each week to complete the exercises.
Review the Python concepts covered in the course before attempting the exercises.
Seek help from online forums or the course instructor if you encounter difficulties.
Track your progress and identify areas where you need improvement.

Follow Python tutorials outside of the course

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Engaging with external resources will supplement the course material and enhance your understanding of Python.

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Find reputable online tutorials or courses that complement the course content.
Set aside dedicated time to work through the tutorials.
Take notes and summarize key concepts covered in the tutorials.
Apply the knowledge gained from the tutorials to the course assignments.

Create a comprehensive course notebook

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Organizing and reviewing your course materials will enhance your retention and recall of key concepts.

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Gather all relevant course materials, including notes, assignments, and quizzes.
Create a digital or physical notebook to store and organize these materials.
Summarize and connect key concepts from different sources.
Review your notebook regularly to reinforce your learning.

Create a Python project

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Working on a real-world project will solidify your Python skills and apply your knowledge to a practical scenario.

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Identify a project idea that aligns with your interests and the course material.
Research and gather resources for your project.
Plan and design the structure of your project.
Implement your project using Python.
Test and debug your project to ensure it functions correctly.
Document your project and share it with others.

Career center

Learners who complete Python for Genomic Data Science will develop knowledge and skills that may be useful to these careers:

Bioinformatician

Bioinformaticians analyze, interpret, and manage biological data. This course provides a strong foundation for a career in Bioinformatics, as it introduces the Python programming language and the iPython notebook, which are essential tools for Bioinformaticians. Additionally, the course covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Bioinformatics.

See salaries and explore the career path for Bioinformatician

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course in Python and the iPython notebook can provide a strong foundation for a career in Data Analysis, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Data Analysis.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data to identify and solve business problems. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Business Analysis.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights for decision-making. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Statistics.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Quantitative Analysis.

See salaries and explore the career path for Quantitative Analyst

Data Scientist

Data Scientists research and develop advanced analytical models that extract meaningful insights from large, complex datasets. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role. A Data Scientist may need to leverage their knowledge of programming to automate data cleaning and transformation tasks, a skill that is covered in this course.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. This course provides a foundational knowledge of Python programming, which is essential for a Machine Learning Engineer. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Machine Learning.

See salaries and explore the career path for Machine Learning Engineer

Epidemiologist

Epidemiologists investigate the causes of disease and other health problems in populations. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Epidemiology.

See salaries and explore the career path for Epidemiologist

Health Data Analyst

Health Data Analysts collect, clean, and analyze health data to identify trends and patterns. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Health Data Analysis.

See salaries and explore the career path for Health Data Analyst

Clinical Data Manager

Clinical Data Managers oversee the collection, management, and analysis of clinical data. This course in Python and the iPython notebook can provide foundational knowledge that can lead to success in this role, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Clinical Data Management.

See salaries and explore the career path for Clinical Data Manager

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a foundation in Python programming, which is one of the most popular programming languages used in software development. The course also covers topics such as data structures, functions, and communication with the outside world, which are all essential skills for a Software Engineer.

See salaries and explore the career path for Software Engineer

Medical Writer

Medical Writers develop and write scientific and medical content. This course in Python and the iPython notebook can provide foundational knowledge that can be useful for a Medical Writer, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Medical Writing.

See salaries and explore the career path for Medical Writer

Healthcare Consultant

Healthcare Consultants advise healthcare organizations on how to improve their operations. This course in Python and the iPython notebook may be useful for a Healthcare Consultant, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Healthcare Consulting.

See salaries and explore the career path for Healthcare Consultant

Regulatory Affairs Specialist

Regulatory Affairs Specialists ensure that medical products meet regulatory requirements. This course in Python and the iPython notebook may be useful for a Regulatory Affairs Specialist, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Regulatory Affairs.

See salaries and explore the career path for Regulatory Affairs Specialist

Pharmaceutical Sales Representative

Pharmaceutical Sales Representatives sell pharmaceutical products to healthcare providers. This course in Python and the iPython notebook may be useful for a Pharmaceutical Sales Representative, as it introduces the essential skills for data manipulation and analysis. The course also covers topics such as data structures, functions, and communication with the outside world, which are all relevant to Pharmaceutical Sales.

See salaries and explore the career path for Pharmaceutical Sales Representative

Reading list

We've selected 14 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 Python for Genomic Data Science.

Python Data Science Handbook

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Serves as a comprehensive reference for data science tasks and techniques in Python, offering practical guidance for the course.

Python for Genomic Data Science

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Genomics data science python

Activities

Career center

Reading list

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