دوراتنا

DevOps on AWS

DevOps on AWS specialization teaches you how to use the combination of DevOps philosophies, practices and tools to develop, deploy, and maintain applications in the AWS Cloud. Benefits of adopting DevOps include: rapid delivery, reliability, scalability, security and improved collaboration. The first course introduces you to essential AWS products, services, and common solutions.

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• Self Paced
• الإنجليزية

MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure Machine Learning

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we developed this course: MLOps1 (Azure) - Deploying AI & ML Models in Production using Microsoft Azure Machine Learning

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• Self Paced
• 28
• الإنجليزية

Dynamic Programming: Applications In Machine Learning and Genomics

Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.

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• الإنجليزية

Machine learning with Python for finance professionals

A machine learning course focused on delivering practical Python skills for finance professionals looking to maximise their use of these time-saving tools within their organisation.

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• الإنجليزية

Robotic process and intelligent automation for finance

In this course we explain how automation can play a key role in delivering the requirement to have robust processes and clean data. By using automation tools and machine learning, finance leaders can identify, impl

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• 15
• الإنجليزية

Machine Learning at the Edge on Arm: A Practical Introduction

****This course will provide you with the hands-on experience you’ll need to create innovative machine learning applications using ubiquitous Arm-based microcontrollers.

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• 8
• الإنجليزية

Introduction to Machine Learning on AWS

This course is intended for software developers and engineers taking their first steps with the AWS services that do much of heavy lifting of Machine Learning for you.

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• 15
• الإنجليزية

Machine Learning for Semiconductor Quantum Devices

Learn how to deploy artificial intelligence to control and calibrate semiconductor quantum computing chips

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• Self Paced
• 27
• الإنجليزية

AI for Everyone: Master the Basics

Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.

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• 33
• الإنجليزية

Analyzing Data with Python

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!

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• 15
• الإنجليزية

Data Science and Machine Learning Capstone Project

Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model.

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• Self Paced
• 28
• الإنجليزية

PyTorch and Deep Learning for Decision Makers

Learn how PyTorch, a deep learning framework, can be used to automate and optimize processes through the development and deployment of state-of-the-art AI applications. The course will also help you understand the importance of data quality, how to choose the right model, and the challenges in deploying and maintaining both deep learning and machine learning applications.

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• Self Paced
• 15
• الإنجليزية

Oracle Autonomous Database Administration Workshop

Learn the fundamentals of Autonomous databases and take your DBA skills knowledge to the next level and learn to deploy and administer Autonomous databases. Explore planning, implementing, and deploying an Oracle Autonomous Database, the first and only autonomous database service in the cloud.In this module you will learn how to create applications on Autonomous Database using SQL, APEX, and Oracle Machine Learning.

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• 12
• الإنجليزية

Introduction to Machine Learning and AI

Discover machine learning and how it works, and train your own AI using free online tools.

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• Self Paced
• 63
• الإنجليزية

Data Science: Machine Learning

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

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• Self Paced
• 25
• الإنجليزية

MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how to automate your pipeline’s functions and continuously optimize its performance, which is why we developed this course, MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning

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• 26
• الإنجليزية

Digital Marketing Analytics: Tools and Techniques

Learn how to leverage leading tools and approaches to digital marketing data analysis. Dive into SEO and Paid search strategies, web analytics, online testing, machine learning and AI/Big Data applications to strengthen your digital marketing efforts and leverage your resources most effectively.

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• 10
• الإنجليزية

Mathematical Methods for Data Analysis

Learn mathematical methods for data analysis including mathematical formulations and computational methods. Some well-known machine learning algorithms such as k-means are introduced in the examples.

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• التعلم الذاتي
• 21
• الإنجليزية

Computer Vision and Image Processing Fundamentals

Learn about computer vision, one of the most exciting fields in machine learning. artificial intelligence and computer science.

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• 10
• الإنجليزية

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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• الإنجليزية

Principles of Data Science Ethics

Concern about the harmful effects of machine learning algorithms and AI models (bias and more) has resulted in greater attention to the fundamentals of data ethics.

This data science ethics course for both practitioners and managers provides guidance and practical tools to build better models and avoid these problems. The course offers a framework data scientists can use to develop their projects and an audit process to follow in reviewing them. Case studies with Python code are provided.

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• Self Paced
• الإنجليزية

Applied Data Science Ethics

AI’s popularity has resulted in numerous well-publicized cases of bias, injustice, and discrimination. Often these harms occur in machine learning projects that have the best of goals, developed by data scientists with good intentions. This course, the second in the data science ethics program for both practitioners and managers, provides guidance and practical tools to build better models and avoid these problems.

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• Self Paced
• الإنجليزية

Google Cloud Speech API: Qwik Start

This is a self-paced lab that takes place in the Google Cloud console. The Google Cloud Speech API integrates speech recognition into dev apps; you can now send audio/receive a text transcription. Watch these short videos Powerful Speech Recognition Using Google Machine Learning and Google Cloud Speech: Qwik Start - Qwiklabs Preview

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• Self Paced
• 1 ساعات
• الإنجليزية

Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

In this Google Cloud Labs Specialization, you'll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion.

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• Self Paced
• الإنجليزية

Digital Health

This specialisation introduces students to the emerging and multidisciplinary field of digital health and the role and application of digital health technologies including mobile applications, wearable technologies, health information systems, telehealth, telemedicine, machine learning, artificial intelligence and big data. These digital health technologies are assessed in terms of their opportunities and challenges to address real-world public health and health care system challenges in order to improve the quality, safety and efficiency of these services.

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• Self Paced
• الإنجليزية