Computational Fluid Dynamics Courses

Computational Data Science in Physics I

Explore realistic physics research examples using computational methods to analyze LIGO data, detect gravitational waves, and fit signals within physical models using Jupyter notebooks.

• MITx Online
• 6 weeks, 10-15 hours/week
• Self-Paced
• Free Online Course

Computational Data Science in Physics II

Master computational methods for physics research, including hypothesis testing, semi-parametric methods, deep learning, and analyzing LHC data to measure W and Z boson properties.

• MITx Online
• 7 weeks, 10-15 hours/week
• Self-Paced
• Free Online Course

Computational Data Science in Physics III

Dive into numerical simulations for physics research, from differential equations to lattice models, culminating in applications relevant to contemporary lattice QCD.

• MITx Online
• 7 weeks, 10-15 hours/week
• Self-Paced
• Free Online Course

Introduction to Mechanics: Kinematics and Dynamics

Dive into calculus-based physics, exploring kinematics, Newton's laws, circular motion, and resistive forces in this comprehensive mechanics introduction.

• MITx Online
• 5 weeks, 10-12 hours/week
• Self-Paced
• Free Online Course

Introduction to Mechanics: Rotational Dynamics

Explore rotational dynamics in this calculus-based physics course covering rigid bodies, torque, angular momentum, and gyroscopes.

• MITx Online
• 4 weeks, 10-12 hours/week
• Self-Paced
• Free Online Course

Advanced Fluid Mechanics 1: Fundamentals

Master the fundamental principles of fluid dynamics, covering kinematics, hydrostatics, buoyancy, inviscid flow, Bernoulli's theorems, and control volume analysis for engineering applications.

• MITx Online
• Self-Paced
• Free Online Course

Advanced Fluid Mechanics 2: The Navier-Stokes Equations for Viscous Flows

Master the Navier-Stokes equations for viscous flows, analyzing pipe, channel, and Stokes flows while applying dimensional analysis and lubrication theory to solve industrial fluid problems.

• MITx Online
• 16 weeks, 8-12 hours/week
• Self-Paced
• Free Online Course

Computational Music Theory and Analysis

Explore computational approaches to music theory using Python and MIT's music21 toolkit, covering algorithms, corpus studies, machine learning, and music generation techniques.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Advanced Fluid Mechanics 3: Potential Flows & Boundary Layers

Master potential flow theory and boundary layer analysis for high Reynolds number flows, exploring vorticity, circulation, lift, and turbulence transition.

• MITx Online
• Self-Paced
• Free Online Course

Computational Thinking for K-12 Educators: Sequences and Loops

26 ratings at Coursera

Develop computational thinking skills for K-12 education, focusing on sequences and loops. Learn to create block-based programs, solve programming puzzles, and explore effective teaching strategies.

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

Computational Thinking for K-12 Educators: Conditional Loops and If Statements

Explore conditional loops and if statements for K-12 programming education. Learn to create interactive games, debug common issues, and implement effective teaching strategies like Peer Instruction.

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

Computational Thinking for K-12 Educators: Abstraction, Methods, and Lists

Explore abstraction, methods, lists, and recursion in programming. Develop teaching strategies for K-12 CS education, including culturally relevant pedagogy and low-frustration learning experiences.

• Coursera
• 9 hours 4 minutes
• Self-Paced
• Paid Course

Computational Thinking for K-12 Educators: Variables and Nested Loops

Explore abstraction, lists, and nested loops through interactive projects. Develop problem-solving skills and learn to guide classroom discussions on programming concepts for K-12 students.

• Coursera
• 15 hours 58 minutes
• Self-Paced
• Paid Course

Computational Thinking for K-12 Educators Capstone

Prepare K-12 educators to guide students through the AP Computer Science Principles Create Task, focusing on algorithm design, abstraction, and project management skills.

• Coursera
• 11 hours 26 minutes
• Self-Paced
• Paid Course

American Museum of Natural History

Ecology: Ecosystem Dynamics and Conservation

8 ratings

Explore ecosystem dynamics, conservation, and recovery through Gorongosa National Park case study. Learn to analyze complex ecological factors and address real-world conservation challenges.

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