Data Mining, Machine Learning, and Deep Learning (Big Data)

Name: Data Mining, Machine Learning, and Deep Learning (Big Data)
Brand: Educa PHAROS
SKU: AFO028NW7
Availability: InStock

Cross-cutting

Digital Skills

Duration

40 hours

PRESENTATION

The Data Mining, Machine Learning, and Deep Learning (Big Data) Course offers you the opportunity to immerse yourself in the fascinating world of artificial intelligence and data analysis. Today, the technology sector is booming, and the demand for skilled professionals in these areas is higher than ever. Throughout the course, You will develop key skills in supervised and unsupervised learning, as well as in deep learning, preparing you to tackle the challenges of analyzing large volumes of data. This knowledge will It will enable users to uncover hidden patterns and generate valuable insights for strategic decision-making across various industries. By choosing this course, you'll position yourself at the forefront of the job market, opening doors to exciting and well-paying career opportunities. With a robust theoretical foundation and high-quality educational resources, you'll be equipped to become an expert in the field of Big Data and artificial intelligence.

Objectives

– Understand the key concepts of supervised and unsupervised learning in data analysis.

– Identify and apply supervised learning algorithms to solve specific business problems.

– Explore clustering and dimensionality reduction techniques in unsupervised learning.

– Implement deep neural networks to improve accuracy in complex tasks.

– Evaluate machine learning models using standard metrics to ensure their effectiveness.

– Use big data tools to manage and process large volumes of information.

– Develop skills to interpret results and communicate findings effectively.

Syllabus

TEACHING UNIT 1. SUPERVISED LEARNING (I) Introduction Linear, Multiple, and Logistic Regression (I) Linear, Multiple, and Logistic Regression (II) Support Vector Machines (SVM) Decision Trees TEACHING UNIT 2. SUPERVISED LEARNING (II) KNN (K-Nearest Neighbors) Naive Bayes Evaluation of Supervised Models Example Exercise Proposed Exercise TEACHING UNIT 3. UNSUPERVISED LEARNING Introduction to clustering: purpose and metrics K-means clustering Hierarchical clustering, other techniques, and examples Principal Component Analysis (PCA) PCA Example Exercise TEACHING UNIT 4. DEEP LEARNING Artificial Neural Networks (ANN) (I) Artificial Neural Networks (ANN) (II) Artificial Neural Networks (ANN) (III) Sample Exercise Assigned Exercise

Request for Information

Name *

Last Name *

Country

Phone

Email *

Company

Job Position

Sector

Message

I have read and agree to the Privacy Policy

Related MOOCs

Workplace Risk Prevention, Ergonomics, and Mental Health

The Course on Workplace Risk Prevention, Ergonomics, and Mental Health addresses the growing need to ensure environments...

Digital Disconnection and Legal Compliance in the Workplace

In the age of remote work, hyperconnectivity has put companies under the scrutiny of the Labor Inspectorate....

The Right to Digital Disconnection, Health, and Work Ethics

In a world of global digitization, hyperconnectivity has gone from being an advantage to becoming a challenge...

Are the Educa PHAROS courses eligible for credit?

Many courses can be credited toward the master's programs at Structuralia.

Facts about our area

+ 1.483

Hours

+88.999

Minutes

264

Courses

Are the masterclasses live?

Who is it intended for?

What features does Educa PHAROS have?

What guarantees does Educa PHAROS offer?

Why is Educa PHAROS the best solution?

Educa PHAROS is a next-generation training model that places a company’s human capital at the forefront. Through a platform that adapts to each company’s corporate identity and offers a total of more than 900 courses, it provides tailored training for each organization. The unlimited flat-rate plan provides each company with the number of courses that best suits its needs, as well as the ability to determine which employees will have access.