Our Courses

Natural Language Processing in Microsoft Azure

Natural Language Processing in Microsoft Azure

Natural language processing supports applications that can see, hear, speak with, and understand users. Using text analytics, translation, and language understanding services, Microsoft Azure makes it easy to build applications that support natural language. In this course, you will learn how to use the Text Analytics service for advanced natural language processing of raw text for sentiment analysis, key phrase extraction, named entity recognition, and language detection. You will learn how to recognize and synthesize speech by using Azure Cognitive Services.

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  • 8 hours
  • English
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MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning

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
  • English
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Dynamic Programming: Applications In Machine Learning and Genomics

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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Machine learning with Python for finance professionals

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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  • English
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Robotic process and intelligent automation for finance

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
  • English
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Machine Learning at the Edge on Arm: A Practical Introduction

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
  • English
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Introduction to Machine Learning on AWS

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
  • English
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AI for Everyone: Master the Basics

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
  • English
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Analyzing Data with Python

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
  • English
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Data Science and Machine Learning Capstone Project

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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  • 28
  • English
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PyTorch and Deep Learning for Decision Makers

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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  • 15
  • English
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Oracle Autonomous Database Administration Workshop

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
  • English
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Introduction to Machine Learning and AI

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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  • 63
  • English
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MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure Machine Learning

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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  • 28
  • English
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Data Science: Machine Learning

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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  • 25
  • English
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Digital Marketing Analytics: Tools and Techniques

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
  • English
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Mathematical Methods for Data Analysis

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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  • 21
  • English
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Computer Vision and Image Processing Fundamentals

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
  • English
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PyTorch Basics for Machine Learning

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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  • English
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Principles of Data Science Ethics

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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  • English
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Applied Data Science Ethics

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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  • English
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Machine Learning Implementation and Operations in AWS

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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  • 6 hours
  • English
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Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

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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  • English
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Google Cloud Speech API: Qwik Start

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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  • 1 hour
  • English
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CertNexus Certified Artificial Intelligence Practitioner

CertNexus Certified Artificial Intelligence Practitioner

The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demonstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP. AI and ML have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.

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  • English
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