ML Model Optimization Course + 8 ECTS Credits

Online Training

ML Model Optimization Course + 8 ECTS Credits

Name: ML Model Optimization Course + 8 ECTS Credits en El Salvador
Brand: INESEM - INSTITUTO EUROPEO DE ESTUDIOS EMPRESARIALES
SKU: 417763-2501
Availability: InStock

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200 hours

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8 ECTS

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Spanish

In the field of machine learning, model optimization has become an essential skill for any professional who aspires to stand out in the sector. Job demand in this field is booming, and the ML Model Optimization course offers you a unique opportunity to acquire essential knowledge that makes a difference. You will learn to manage loss functions and evaluation metrics, apply advanced techniques such as gradient descent, and discover effective strategies to avoid overfitting, among others. Additionally, you will delve into the world of advanced optimizers such as ADAM and RMSprop, and explore tuning automation with innovative methods.

Instituciones educativas

$313

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Details to take into account

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Multilingual support

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Digital certificate included

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Assistant Phia

Objectives

- Understand the fundamentals of optimization in machine learning. - Identify loss functions and model evaluation metrics. - Apply gradient descent techniques and their stochastic variants. - Implement regulation techniques in supervised models. - Perform hyperparameter tuning and cross-validation effectively. - Develop strategies to avoid overfitting and underfitting in models. - Optimize deep neural networks using advanced optimizers.

Content

Career opportunities

The main professional opportunities of this Model Optimization in ML course are as a data science professional specialized in model optimization, responsible for machine learning with a focus on hyperparameter adjustment and specialist in deep neural networks aimed at reducing overfitting among other functions.

What it prepares you for

By completing the Model Optimization in ML course, you will prepare to improve the performance of machine learning models. You will learn to implement loss functions and evaluation metrics, apply gradient descent techniques and their variants, as well as regulate supervised models to avoid overfitting and underfitting. Additionally, you will develop skills in tuning hyperparameters through cross-validation.

The Model Optimization in ML course is designed for graduates in data science, engineering and related fields, interested in improving their skills in optimizing machine learning models. We will cover everything from optimization fundamentals to advanced techniques such as hyperparameter tuning and strategies to avoid overfitting.

Our training is 100% online, which allows students to self-regulate their study and adapt it to their own needs. We are committed to personalized and autonomous teaching, with an approach based on critical thinking and constructivism.

We have a highly specialized teaching team that will accompany you throughout the entire teaching-learning process. This will allow you to personalize your training even more, since we adapt to your pace and needs.

You will have access to our learning platform, MyLXP, from any device and at any time of the day, allowing you to decide how and when to study. All of this is possible thanks to our Educa LXP (Learning Experience Platform) methodology, an environment designed to boost your educational progress, encourage innovation and offer a personalized learning experience adapted to each need.