Microsoft Azure Women in AI Program

Bridging the Gender Gap in AI  

It is a simple truth: the field of artificial intelligence is far too male-dominated. According to a recent research by the World Economic Forum and LinkedIn, only 22% of jobs in artificial intelligence are held by women, with even fewer holding senior roles. 

Artificial intelligence will reshape every corner of our lives in the coming years—from healthcare to finance, from education to government. It is therefore troubling that those building this technology do not fully represent the society they are poised to transform. 

“In order to get a more diverse workforce in AI, we need to increase the pipeline, hire more women and minorities into AI positions and create an environment that gives them opportunities to thrive so that we can retain them,” offered Jennifer Chayes, Managing Director of Microsoft Research New England, NYC and Montreal. Technology could benefit or hurt people, so the usage of tech is the responsibility of humanity as a whole. 

The training is sponsored by Microsoft and is free of charge for Women who want to certify and work in the field of AI, the exam fee of 15 USD will be reimbursed upon successfully passing the exam. 

Register now:

  • Malaysia – March 20, June 10 Register  
  • Indonesia – April 3, May 15 Register  
  • Vietnam – April 10, May 28, June 2 Register 
  • Philippines – March 27, April 15, May 22 Register 
  • Korea – March 25, April 17, May 1 Register 
  • Thailand – April 21, May 15 , June 5 Register 
  • Singapore – March 24, April 24, June 12 Register 
  • Sri Lanka – May 8, June 9 Register 

*Registration ends one week before the training

Prerequisites 

Candidates for this training should be residents of the country they are registering for. Basic knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services is required. This training is intended for candidates with both technical and non-technical backgrounds. Candidates have to be women who are working in the data science field, fundamental programming language knowledge is necessary for taking up the AI-900 certification exam. Registering for the training requires candidates to commit to a full day training which is followed by a AI-900 certification exam.  

Key Benefits of AI-900 Certification

Candidates will receive a vast amount of knowledge on Artificial Intelligence and the ability to identify Microsoft Azure services to support them. Grow your career as an Azure Data Scientist Associate or Azure AI Engineer Associate with the fundamental knowledge of Microsoft Azure AI Fundamentals certification. IT market is flooded with jobs for people who work with data and use Microsoft Azure Services.  Candidates having Microsoft certification badges in their CV have a huge advantage. Certification is a quick way to let others know that your skills have been validated. 

Training Synopsis 

Microsoft Azure AI Fundamentals 

1 Day Instructor-led training 9am – 5pm

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth. 

Audience profile 

The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. 

Job role: AI Engineer, Data Scientist, Developer, Solutions Architect  

Preparation for exam:AI-900 

Skills gained 

  • Describe Artificial Intelligence workloads and considerations 
  • Describe fundamental principles of machine learning on Azure 
  • Describe features of computer vision workloads on Azure 
  • Describe features of Natural Language Processing (NLP) workloads on Azure 
  • Describe features of conversational AI workloads on Azure 

Course outline 

Module 1: Introduction to AI 

In this module, you’ll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You’ll then explore considerations and principles for responsible AI development. 

Lessons 

  • Artificial Intelligence in Azure 
  • Responsible AI 

After completing this module you will be able to: 

  • Describe Artificial Intelligence workloads and considerations 

 

Module 2: Machine Learning 

Machine learning is the foundation for modern AI solutions. In this module, you’ll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models. 

Lessons 

  • Introduction to Machine Learning 
  • Azure Machine Learning 

After completing this module you will be able to: 

  • Describe fundamental principles of machine learning on Azure 

Module 3: Computer Vision 

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you’ll explore multiple computer vision techniques and services. 

Lessons 

  • Computer Vision Concepts 
  • Computer Vision in Azure 

After completing this module you will be able to: 

  • Describe features of computer vision workloads on Azure 

Module 4: Natural Language Processing 

This module describes scenarios for AI solutions that can process written and spoken language. You’ll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands. 

After completing this module you will be able to: 

  • Describe features of Natural Language Processing (NLP) workloads on Azure 

Module 5: Conversational AI 

Conversational AI enables users to engage in a dialog with an AI agent, or bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions. 

Lessons 

  • Conversational AI Concepts 
  • Conversational AI in Azure 

After completing this module you will be able to: 

  • Describe features of conversational AI workloads on Azure 

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