Northeastern University Courses

Healthcare Financial Management Fundamentals

Explore advanced healthcare finance concepts, including financial statements, long-term financing, FP&A, and financial condition analysis. Gain practical skills for evaluating organizational financial health.

• Coursera
• 19 hours 28 minutes
• Self-Paced
• Paid Course

Healthcare Information Design and Visualizations

Explore data visualization techniques for effective business decision-making. Learn to collect, process, and present data insights through static and interactive displays, emphasizing clear communication and ethical considerations.

• Coursera
• 20 hours 23 minutes
• Self-Paced
• Paid Course

Enterprise Data Wrangling with SQL and Python

Master enterprise data wrangling using SQL and Python—covering extraction, profiling, cleansing, integration, and automation to solve real-world business data challenges.

• Coursera
• 7 hours 57 minutes
• Self-Paced
• Paid Course

Engineering Probability and Statistics Part 1

Discover foundational statistics and probability concepts including variables, distributions, and data analysis techniques for engineering applications.

• Coursera
• 22 hours 22 minutes
• Self-Paced
• Paid Course

Engineering Probability and Statistics Part 2

Explore statistical inference through hypothesis testing, confidence intervals, ANOVA, and sampling distributions to solve engineering problems with data-driven insights.

• Coursera
• 1 day 42 minutes
• Self-Paced
• Paid Course

Engineering Project Management Part 1

Explore project management fundamentals covering planning, budgeting, risk management, and team leadership through systems development lifecycle framework with practical tools.

• Coursera
• 11 hours 51 minutes
• Self-Paced
• Paid Course

Engineering Project Management Part 2

Master advanced project management techniques including network scheduling, resource planning, earned value management, and project control mechanisms for successful engineering projects.

• Coursera
• 13 hours 56 minutes
• Self-Paced
• Paid Course

Ethics and Governance in the Age of Generative AI

Explore ethical and technical aspects of generative AI, including responsible development, bias reduction, and governance strategies. Gain insights into AI model deployment and societal impacts.

• Coursera
• 1 day 2 hours 43 minutes
• Self-Paced
• Paid Course

Ethics and AI: A Philosophical Guide to Responsible Use

Explore philosophical concepts and tools for evaluating AI ethics and regulation. Practice logical reasoning, analyze arguments, and form informed opinions on responsible AI practices.

• Coursera
• 17 hours 42 minutes
• Self-Paced
• Paid Course

Foundations in Human-Centered AI

Explore the principles of designing AI systems that enhance human capabilities rather than replace them, covering historical context, key concepts, and human-centric development approaches.

• Coursera
• 14 hours 9 minutes
• Self-Paced
• Paid Course

Machine Learning and Data Analytics Part 2

Explore advanced data mining techniques including clustering, neural networks, SVMs, and text mining with real-world applications across engineering sectors.

• Coursera
• 18 hours 25 minutes
• Self-Paced
• Paid Course

Machine Learning with Small Data Part 1

Discover modern deep learning techniques for training effective models with limited datasets, addressing challenges in healthcare, military, and industry applications.

• Coursera
• 14 hours 21 minutes
• Self-Paced
• Paid Course

Machine Learning and Data Analytics Part 1

Dive into data mining fundamentals, exploring preprocessing, classification, clustering, and regression techniques through hands-on projects and real-world case studies.

• Coursera
• 15 hours 20 minutes
• Self-Paced
• Paid Course

Machine Learning with Small Data Part 2

Master advanced ML techniques for limited datasets: multi-task learning, meta-learning, NeRF, diffusion models, and 3D Gaussian Splatting for real-world data constraints.

• Coursera
• 11 hours 34 minutes
• Self-Paced
• Paid Course

Machine Learning for Engineers: Algorithms and Applications

Master practical machine learning algorithms through hands-on implementation in Python and PyTorch, covering supervised and unsupervised learning techniques for real-world applications in computer vision, NLP, and robotics.

• Coursera
• 17 hours 31 minutes
• Self-Paced
• Paid Course