دوراتنا

Machine Learning Implementation and Operations in AWS

Machine Learning Implementation Operations in AWS is the fifth Course in the AWS Certified Machine Learning Specialty specialization. The course has a major focus on designing and implementing machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:00-1:30 Hours Video lectures that provide both Theory and Hands -On knowledge.

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• التعلم الذاتي
• 6 ساعات
• الإنجليزية

Machine Learning Rock Star – the End-to-End Practice

Machine learning reinvents industries and runs the world. Harvard Business Review calls it “the most important general-purpose technology of our era.” But while there are so many how-to courses for hands-on techies, the…

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Introduction to Machine Learning: Supervised Learning

In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM.

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• 40 ساعات
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Modern Robotics: Mechanics, Planning, and Control

This Specialization provides a rigorous treatment of spatial motion and the dynamics of rigid bodies, employing representations from modern screw theory and the product of exponentials formula. Students with a freshman-l…

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Prompt Engineering for ChatGPT

ChatGPT and other large language models are going to be more important in your life and business than your smartphone, if you use them right. ChatGPT can tutor your child in math, generate a meal plan and recipes, write software applications for your business, help you improve your personal cybersecurity, and that is just in the first hour that you use it. This course will teach you how to be an expert user of these generative AI tools.

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• 19 ساعات
• الإنجليزية

IBM AI Foundations for Business

This specialization will explain and describe the overall focus areas for business leaders considering AI-based solutions for business challenges. The first course provides a business-oriented summary of technologies and…

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PyTorch Basics for Machine Learning

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

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Methods and Application in Human-Robot Interaction

Explore the two interaction modalities between humans and robots: verbal and emotional. Learn how to setup a study to evaluate the quality of the interaction from both, the robot’s and the human’s perspectives. Discover application areas for robots and what their role in the future society might be.

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Analytics for Decision Making

Discover the foundational concepts that support modern data science and learn to analyze various data types and quality to make smart business decisions.

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• 2
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Data Collection and Integration

The "Data Collection and Integration" course provides students with comprehensive techniques for gathering data from diverse sources, including files, relational databases, web pages, and APIs. Participants will gain practical experience in collecting and integrating data for further processing and analysis. The course emphasizes the utilization of appropriate tools and packages, such as Pandas, Beautiful Soup, and SQL, to effectively handle real-life datasets and address data integration challenges.

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• 28 ساعات
• الإنجليزية

Foundations of Data Analytics

Learn the fundamental techniques for data analytics and to be prepared for learning and applying more advanced big data technologies.

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Data Analytics and Visualization in Health Care

Learn best practices in data analytics, informatics, and visualization to gain literacy in data-driven, strategic imperatives that affect all facets of health care.

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Exploratory Data Analysis in AWS

Exploratory Data Analysis in AWS is the second course in the AWS Certified Machine Learning Specialty specialization. The main focus of this course is to analyze Data Streams and Data Analytics services in AWS along with exploring Data Analysis in AWS. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.

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• 5 ساعات
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Econometrics: Methods and Applications

Welcome!
Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making.
* What do I learn?

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• 66 ساعات
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Introduction to Robotics with Webots

The overarching learning goal of this specialization in robotics is to create an appreciation for the tight interplay between mechanism, sensor, and control in the design of intelligent systems. By the end of this specia…

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Extract, Transform and Load Data in Power BI

This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI.
In this course, you will learn the process of Extract, Transform and Load or ETL. You will identify how to collect data from and configure multiple sources in Power BI and prepare and clean data using Power Query. You’ll also have the opportunity to inspect and analyze ingested data to ensure data integrity.

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• 20 ساعات
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Explainable deep learning models for healthcare - CDSS 3

This course will introduce the concepts of interpretability and explainability in machine learning applications. The learner will understand the difference between global, local, model-agnostic and model-specific explanations. State-of-the-art explainability methods such as Permutation Feature Importance (PFI), Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanation (SHAP) are explained and applied in time-series classification.

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• التعلم الذاتي
• 30 ساعات
• الإنجليزية

Try It: Introduction to Google Analytics

This course is an introduction to using an analytics platform to unlock the power of data. Explore how data from digital products and tools can prepare you improve ROI, develop user insights, and generate revenue results. This course prepares you to learn more advanced approaches to digital analytics and data analysis used by data analysts, marketers, product managers, and other business professionals.

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• 1
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Big Data Computing with Spark

Learn the theory and gain hands-on experience of big data systems, using Spark as the exemplary platform.

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• 57
• الإنجليزية

Healthcare Analytics and Decision Making

Healthcare leaders deal with important challenges that can affect public health. Learn about health informatics solutions and financial systems needed to manage planning, quality assurance, risk management, and evidence-based decision-making.

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• 45
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Sport Analytics: Data Driven Decision Making

In sports, gut instincts are great but data analytics are necessary. Learn the fundamentals of how to use data, facts, and metrics to identify problems, make informed decisions and propose innovative solutions to guide strategic, real world business decisions in the sport industry and for sports teams.

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• 5
• الإنجليزية

Introduction to Human-Robot Interaction

Discover the basic concepts of human-robot interaction and how robots work. Learn how to design a human-robot interaction and different ways in which users can interact with robots.

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• الإنجليزية

Python for AI & Development Project

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Build a Deep Learning Based Image Classifier with R

In this 45-min guided project, you will learn the basics of using the Keras interface to R with Tensorflow as its backend to solve an image classification problem. By the time you complete this project, you will have used the R programming language to build, train, and evaluate a neural network model to classify images of clothing items into categories such as t-shirts, trousers, and sneakers. We will be training the deep learning based image classification model on the Fashion MNIST dataset which contains 70000 grayscale images of clothes across 10 categories.

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• 3 ساعات
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AI Foundations for Everyone

Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an indus…

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