Health Data Analysis Courses

This interactive DataCamp course complements the Coursera course Introduction to Probability and Data by Mine Çetinkaya-Rundel.

• DataCamp
• Self-Paced
• Free Trial Available

Data Warehousing Concepts

1 rating

This introductory and conceptual course will help you understand the fundamentals of data warehousing.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Data Manipulation with pandas

1 rating

Learn how to import and clean data, calculate statistics, and create visualizations with pandas.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Data Manipulation in SQL

1 rating

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Big Data Fundamentals with PySpark

1 rating

Learn the fundamentals of working with big data with PySpark.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Data Structures - Full Course Using C and C++

17 ratings

Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.

• freeCodeCamp
• 10 hours
• Self-Paced
• Free Video

Career Certificate

Learn Data Structures and Algorithms in Python

1413 ratings at Boot.dev

Master Python algorithms and Big-O complexity while building skills to write performant code, tackle technical interviews, and understand fundamental computer science concepts.

• Boot.dev
• 32 hours
• Self-Paced
• Paid Course

Data and Health Indicators in Public Health Practice

1260 ratings at Coursera

Explore epidemiology's role in public health, from problem-solving methodologies to data analysis. Learn to identify issues, propose solutions, and evaluate interventions using reliable health data and indicators.

• Coursera
• 6 hours 10 minutes
• Self-Paced
• Paid Course

Understanding and Visualizing Data with Python

2733 ratings at Coursera

Explore data analysis and visualization using Python, covering statistics fundamentals, univariate and multivariate data, sampling techniques, and practical applications with popular libraries.

• Coursera
• 19 hours 37 minutes
• Self-Paced
• Paid Course

Bioconductor for Genomic Data Science

387 ratings at Coursera

Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.

• Coursera
• 8-9 hours
• Self-Paced
• Paid Course

Applied Social Network Analysis in Python

2728 ratings at Coursera

Explore network analysis using NetworkX, covering connectivity, centrality, and network evolution. Learn to model real-world phenomena as networks and apply analysis techniques to various datasets.

• Coursera
• 1 day 2 hours 11 minutes
• Self-Paced
• Paid Course

Data Science Capstone

1241 ratings at Coursera

The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academ…

• Coursera
• 5-6 hours
• Self-Paced
• Paid Course

Career Certificate

Big Data

16 ratings

Gain hands-on experience with big data tools and systems. Learn to organize, analyze, and interpret data for better business decisions. Apply insights to real-world problems through predictive modeling and graph analytics.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 6 courses

Innovation Systems for Science, Technology, Energy, Manufacturing, and Health (Spring 2017)

4 ratings

This course focuses on science and technology innovation system, including case studies on energy, computing, advanced manufacturing, and health sectors, with an emphasis on public policy and the federal government's role in that system.

• MIT OpenCourseWare
• 31 hours
• Self-Paced
• Free Video

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

4 ratings

This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learning.

• MIT OpenCourseWare
• 28 hours
• Self-Paced
• Free Video