Create a practical data product using NLP and machine learning, demonstrating real-world data science skills.
Create a practical data product using NLP and machine learning, demonstrating real-world data science skills.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Specialization or Data Science: Statistics and Machine Learning Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.5
(1,226 ratings)
36,849 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
What you'll learn
Create a usable public data product
Apply exploratory data analysis techniques
Build efficient prediction models
Develop presentation materials
Implement natural language processing
Demonstrate end-to-end project execution
Skills you'll gain
This course includes:
0.4 Hours PreRecorded video
3 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
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There are 7 modules in this course
This capstone project course enables students to create a practical data product that showcases their data science skills to potential employers. Working with real-world problems and industry partners, students develop a complete data science project from problem understanding to final presentation. The curriculum covers data acquisition, exploratory analysis, predictive modeling, and creation of a data product with accompanying presentation materials.
Overview, Understanding the Problem, and Getting the Data
Module 1 · 1 Hours to complete
Exploratory Data Analysis and Modeling
Module 2 · 1 Hours to complete
Prediction Model
Module 3 · 41 Minutes to complete
Creative Exploration
Module 4 · 40 Minutes to complete
Data Product
Module 5 · 11 Minutes to complete
Slide Deck
Module 6 · 10 Minutes to complete
Final Project Submission and Evaluation
Module 7 · 1 Hours to complete
Fee Structure
Instructors
Expert in Biostatistics and Neuroinformatics
Brian Caffo, PhD, is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He earned his PhD in Statistics from the University of Florida in 2001. Specializing in computational statistics and neuroinformatics, he co-created the SMART working group
Chief Data Officer and J Orin Edson Foundation Chair at Fred Hutchinson Cancer Center
Dr. Jeff Leek serves as the Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics in Public Health Sciences at the Fred Hutchinson Cancer Center. Previously, he was a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. He earned his PhD in Biostatistics from the University of Washington and is known for his significant contributions to genomic data analysis and statistical methods for personalized medicine. His research has advanced our understanding of molecular mechanisms related to brain development, stem cell self-renewal, and immune responses to trauma, with findings published in top scientific journals such as Nature and Proceedings of the National Academy of Sciences. Dr. Leek developed a highly acclaimed Data Analysis course for Biostatistics students at Johns Hopkins, which has consistently received teaching excellence awards. He is also recognized for his efforts in creating educational initiatives that leverage data science for public health and economic development, including massive open online courses that have engaged millions worldwide.
Testimonials
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4.5 course rating
1,226 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.