Introduction to Amazon Bedrock
Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.
Siga videos cortos dirigidos por instructores expertos y luego practique lo que ha aprendido con ejercicios interactivos en su navegador.
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Al continuar, aceptas nuestros Términos de uso, nuestra Política de privacidad y que tus datos se almacenan en los EE. UU.Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.
Learn to easily summarize and manipulate lists using the purrr package.
Learn to use the Bioconductor package limma for differential gene expression analysis.
This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
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Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.
Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.
In this course youll learn how to apply machine learning in the HR domain.
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Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.
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Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.
Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.
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Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.
Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network
Learn to analyze and model customer choice data in R.
Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.
Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.