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Python for Research: Advanced Techniques and Applications

Master Python coding through hands-on research projects, from data analysis to scientific computing - build practical skills for real applications.

Master Python coding through hands-on research projects, from data analysis to scientific computing - build practical skills for real applications.

Elevate your Python skills from introductory to advanced level with Harvard's comprehensive course. Bridge the gap between basic Python knowledge and its application in research settings. Review Python 3 basics before diving into specialized research tools like NumPy and SciPy. Explore statistical learning with scikit-learn and tackle diverse case studies across scientific disciplines. Gain hands-on experience applying Python to real-world research scenarios.

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Python for Research: Advanced Techniques and Applications

This course includes

12 Weeks

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

21,144

Audit For Free

What you'll learn

  • Review and reinforce Python 3 programming basics

  • Master essential Python tools for research, including NumPy and SciPy

  • Apply Python skills to diverse case studies across scientific disciplines

  • Explore statistical learning techniques using the scikit-learn library

  • Develop practical coding skills for real-world research applications

Skills you'll gain

Python Programming
Scientific Computing
Data Analysis
NumPy
SciPy
Scikit-learn
Statistical Learning
Research Methods

This course includes:

PreRecorded video

Graded assignments, exams

Access on Mobile, Tablet, Desktop

Limited Access access

Shareable certificate

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There are 4 modules in this course

This course is designed to advance Python programming skills for research applications. It begins with a review of Python 3 basics and then introduces essential scientific computation modules like NumPy and SciPy. The curriculum includes six case studies from various disciplines, allowing students to apply their skills to real-world research scenarios. A new module on statistical learning using scikit-learn has been added, enhancing the course's relevance for data-driven research. Throughout the course, students will practice applying Python tools to practical research settings, bridging the gap between introductory programming and advanced research applications.

Week 1: Python Basics

Module 1

Week 2: Python Research Tools

Module 2

Weeks 3 & 4: Case Studies

Module 3

Week 5: Statistical Learning

Module 4

Fee Structure

Instructor

Pioneer in Digital Phenotyping and Network Science

Professor Jukka-Pekka "JP" Onnela serves as Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and Co-Director of the Master in Health Data Science program. Born in Oulu, Finland in 1976, he earned his doctorate in network science from Helsinki University of Technology (now Aalto University) in 2006, where his dissertation received the university's Dissertation of the Year award. His academic journey included positions as a Junior Research Fellow at Oxford University, a Fulbright Scholar at Harvard Kennedy School, and a postdoctoral fellow at Harvard Medical School before joining Harvard Chan School in 2011. His groundbreaking research focuses on statistical network science and digital phenotyping, introducing the concept of "moment-by-moment quantification of individual-level human phenotype using personal digital devices." He directs the Onnela Lab, which developed the open-source Beiwe Research Platform for smartphone-based digital phenotyping, and received the prestigious NIH Director's New Innovator Award in 2013 for his pioneering work in digital phenotyping. His research has revolutionized the use of cell phone data to study human social behavior and its connections to health outcomes.

Python for Research: Advanced Techniques and Applications

This course includes

12 Weeks

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

21,144

Audit For Free

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.2 course rating

51 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.