Advance tools and application of AI in Microsoft Azure#400924

• Analyse the impact of future trends on the development and application of advanced AI tools within Microsoft Azure.
• Identify key challenges and opportunities within your industry, considering how advanced Azure AI tools can be used for problem-solving and innovation.
• Develop a strategic vision for leveraging advanced AI services on Azure to address specific business needs within your organization.
• Explore the latest AI tools and services offered by Microsoft Azure, including:
• Cognitive Services: Pre-trained AI models for tasks like computer vision, language understanding, and speech recognition.
• Machine Learning Services: Tools for building, training, and deploying custom machine learning models at scale.
• Azure Databricks: A managed Apache Spark platform for large-scale data analytics and AI workloads.
• Azure IoT & AI for Edge Computing: Building intelligent applications that process data at the edge of the network.
• Gain hands-on experience building and deploying AI solutions on Azure using real-world datasets and scenarios.
• Understand the potential risks and limitations of advanced AI tools, and consider ethical considerations in AI development and deployment.
• Develop a personalized action plan outlining steps to explore and implement advanced AI solutions within your specific role or project.

• Developers and data scientists interested in building and deploying AI solutions using Microsoft Azure services.
• IT professionals responsible for managing and deploying AI infrastructure on Azure.
• Architects and decision-makers looking to understand the potential of advanced AI tools for business transformation.
• Anyone interested in exploring the future applications of AI on the Azure platform and its impact on various industries.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: The Future of AI & Microsoft Azure
• Welcome and program overview.
• AI on Azure: A Powerful Platform for Innovation: Exploring the potential of Microsoft Azure for building and deploying cutting-edge AI solutions across various industries.
• Future Studies for AI Developers: Learning how to incorporate future studies methodologies like scenario planning to anticipate potential disruptions and opportunities related to AI advancements on Azure.
• Azure AI Services Overview: Introducing the core AI services offered on Azure, exploring their functionalities and potential applications.
• Guest Speaker: A Microsoft Azure AI expert or a developer who successfully built an innovative AI solution on Azure can be invited to share their insights and answer participant questions.

Day 2: Deep Dive into Cognitive Services
• Computer Vision with Azure Cognitive Services: Exploring pre-trained models for image recognition, object detection, optical character recognition (OCR), and more. Participants will gain hands-on experience using APIs to analyse images and extract insights.
• Natural Language Processing (NLP) with Azure Cognitive Services: Learning how to utilize AI models for tasks like sentiment analysis, text analytics, and language translation. Participants will build practical applications using NLP APIs.
• Speech Recognition & Text-to-Speech with Azure Cognitive Services: Exploring tools for converting speech to text and vice versa, with applications for chatbots, voice assistants, and accessibility features. Participants will experiment with these services through hands-on labs.
Day 3: Building & Deploying Machine Learning Models
• Introduction to Machine Learning Services (MLS) on Azure: Understanding the core functionalities of Azure MLS, including data preparation, model training, deployment, and management.
• Hands-on Lab: Building a Machine Learning Model with Azure MLS: Participants will work on a real-world scenario using Azure services to build, train, and deploy a simple machine learning model on a provided dataset.
• Responsible AI on Azure: Discussing ethical considerations in developing and deploying AI models, focusing on topics like bias mitigation, fairness, and explainability tools within Azure.
• Case Study: analysing a real-world example of a company that successfully built and deployed a machine learning model on Azure, addressing the challenges and benefits encountered.
Day 4: Big Data & AI with Azure Databricks
• Introduction to Azure Databricks: Understanding the benefits and functionalities of Azure Databricks, a managed Apache Spark platform for large-scale data processing and AI applications.
• Hands-on Lab: Data Processing & AI with Databricks: Participants will gain practical experience using Databricks for data manipulation, feature engineering, and building machine learning pipelines.
• The Future of AI & Big Data: Exploring future trends in big data analytics and their impact on AI development and application within various industries.
• Guest Speaker: A data scientist or engineer who utilizes Databricks for advanced AI projects can be invited to share their expertise and showcase potential future applications.

Day 5: AI for Edge Computing & The Future
• Azure IoT & Intelligent Edge Solutions: Learning how to integrate AI with Azure IoT services to develop intelligent applications that process data at the edge of the network, closer to sensors and devices.
• The Future of AI & Azure: Discussing potential future advancements in AI on Azure, such as explainable AI, responsible AI frameworks, and the increasing role of quantum computing.
• Developing Your AI Action Plan: Participants will create personalized action plans outlining steps to explore and implement advanced AI solutions within their specific roles or projects. This may include:
o Identifying specific business challenges where advanced Azure AI tools could be beneficial.
o Researching the most relevant Azure services for their needs and exploring pricing models.
o Building a proof-of-concept application using Azure tools and their skills learned in the program.
o Advocating for the adoption of advanced AI solutions within their organization, considering ethical considerations.
• Course Wrap-Up & Ongoing Learning: Reviewing key takeaways from the program, addressing any remaining questions, and discussing ongoing learning resources for staying informed about advancements in AI and Azure AI services.
• Networking & Innovation Showcase: Participants engage in a facilitated discussion to share their AI action plans and explore potential collaborations on future projects using advanced AI tools on Microsoft Azure. They can also showcase their ideas for innovative AI solutions within their fields.