Sports Science Courses

Risk Modelling and Survival Analysis - Actuarial Science

1 rating

Explore stochastic processes, Markov chains, risk modeling, and survival analysis in actuarial science. Learn key concepts and tackle past exam questions using R for practical applications.

• YouTube
• 11 hours
• Self-Paced
• Free Video

Nemeth Braille Code for Math and Science by Susan Osterhaus

1 rating

Learn the Nemeth Braille Code for mathematics and scientific notation, including introductory concepts, reference materials, and computerized tutoring tools.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Alan Turing Institute

Simulation - The Challenge for Data Science - J. Doyne Farmer

1 rating

Exploring challenges in simulation models for data science, focusing on parameter estimation and initialization. Discusses fusion with machine learning and potential impact on policy analysis and forecasting.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

Wondrium

Dune - The Science of Science Fiction

1 rating

Explore the ecological concepts and scientific foundations behind Frank Herbert's Dune, examining its unique planetary ecosystem, the spice melange, and its connections to real-world environmental theories and challenges.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Unreal Engine

Explore the Sports Broadcast and Motion Graphics Sample - Webinar

1 rating

Discover how to create dynamic sports broadcast graphics using Unreal Engine, from customizable templates to live operation and batch rendering techniques.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Statistics - A Full University Course on Data Science Basics

1 rating

Comprehensive introduction to statistics for data science, covering methods for data collection, analysis, and interpretation. Emphasizes practical applications with real-life examples to develop analytical skills.

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

Intro to Data Science - Crash Course for Beginners

1 rating

Comprehensive introduction to data science fundamentals, covering statistics, data visualization, and programming essentials for beginners. Ideal for those seeking a solid foundation in key concepts and practical applications.

• freeCodeCamp
• 1-2 hours
• Self-Paced
• Free Video

Data Structures - Intro to Computer Science - Harvard's CS50 (2018)

1 rating

Explore fundamental data structures in C programming, including linked lists, hash tables, trees, and tries. Learn implementation techniques and practical applications in computer science.

• freeCodeCamp
• 2-3 hours
• Self-Paced
• Free Video

Arrays and Sorting Algorithms - Intro to Computer Science - Harvard's CS50 (2018)

1 rating

Explore arrays, strings, and sorting algorithms in C programming. Learn debugging techniques, memory concepts, and computational complexity while building practical coding skills in this comprehensive computer science lecture.

• freeCodeCamp
• 2-3 hours
• Self-Paced
• Free Video

Computational Thinking & Scratch - Intro to Computer Science - Harvard's CS50 (2018)

1 rating

Explore computational thinking and Scratch programming in Harvard's CS50 intro. Learn binary, ASCII, RGB, algorithms, and create interactive projects using Scratch's graphical interface.

• freeCodeCamp
• 1-2 hours
• Self-Paced
• Free Video

Steve Brunton

Data-Driven Science and Engineering

1 rating

Explora técnicas avanzadas de aprendizaje automático, sistemas dinámicos y control con ejemplos prácticos en Matlab y Python, basados en el libro "Data-Driven Science and Engineering" de Brunton y Kutz.

• YouTube
• 20 hours
• Self-Paced
• Free Video

Great Learning

Essential Statistics for Data Science - Learn Statistics for Data Science

1 rating

Comprehensive overview of essential statistics for data science, covering central tendency, hypothesis testing, ANOVA, and more. Ideal for aspiring data scientists seeking foundational knowledge.

• YouTube
• 5 hours 26 minutes
• Self-Paced
• Free Video

Great Learning

Mathematics for Data Science - Essential Math for Machine Learning

1 rating

Explore essential math for data science, including probability, statistics, machine learning, and deep learning. Learn through real-world case studies and gain insights into the crucial role of mathematics in data analysis.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Statistics for Data Science

1 rating

Comprehensive exploration of statistical concepts for data science, covering descriptive and inferential statistics, probability distributions, hypothesis testing, and various analytical methods through practical examples.

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

Serious Science

Earth Science

1 rating

Explore Earth's systems, climate change, and human impacts through expert lectures on topics like carbon cycles, freshwater ecosystems, climate modeling, and glaciology.

• YouTube
• 4 hours 30 minutes
• Self-Paced
• Free Video