Azure AI for Business Leaders

This course provides business leaders with a foundational understanding of Artificial Intelligence (AI) and its practical implications, enabling them to identify opportunities, make informed decisions, and lead AI initiatives within their organizations.

Enroll Now

📅 New batch starts every Monday!

Duration (Total 6 Hours)

Weekdays

Monday to Friday · 1 Hour per Day

+ 1 Bonus hour on Friday

Weekends

Saturday & Sunday · 3 Hours per Day

Training Agenda

Module 1: Introduction to AI and Business Considerations

Understanding AI Workloads: Explore common AI applications relevant to business, including:
- Computer Vision (e.g., image analysis for quality control, facial recognition for security)
- Natural Language Processing (NLP) (e.g., sentiment analysis for customer feedback, chatbots for support)
- Document Processing (e.g., extracting information from invoices, automating data entry)
- Generative AI (e.g., content creation, personalized marketing)
Responsible AI Principles: Learn about the ethical considerations and best practices for implementing AI, covering:
- Fairness and Inclusiveness
- Reliability and Safety
- Privacy and Security
- Transparency and Accountability

Module 2: Fundamental Principles of Machine Learning for Business

Core Machine Learning Concepts: Understand the basic principles behind machine learning, including:
- Features and Labels: What data is used and what is being predicted.
- Training, Validation, and Test Datasets: How models learn and are evaluated.
Common Machine Learning Techniques (Business Context): Overview of how different ML techniques solve business problems:
- Regression: Predicting continuous values (e.g., sales forecasting).
- Classification: Categorizing data (e.g., customer churn prediction).
- Clustering: Grouping similar data (e.g., customer segmentation).
Deep Learning and Transformer Architecture: A high-level introduction to advanced techniques driving modern AI.
Leveraging Cloud AI Services: Understand how cloud platforms (like Azure) offer managed AI services that simplify development and deployment, focusing on capabilities like automated machine learning and model management.

Module 3: Leveraging Computer Vision in Business

Applications of Computer Vision Solutions: Identify business scenarios where computer vision can add value, such as:
- Image Classification: Categorizing products, identifying defects.
- Object Detection: Inventory management, security surveillance.
- Optical Character Recognition (OCR): Automating data extraction from documents.
- Facial Detection and Analysis: Access control, customer demographics (with ethical considerations).
Overview of Computer Vision Tools: A high-level look at readily available AI services that enable computer vision without extensive coding (e.g., Azure AI Vision).

Module 4: Harnessing Natural Language Processing (NLP) for Business

Key NLP Scenarios for Business: Explore how NLP can transform business operations:
- Key Phrase Extraction: Summarizing documents, identifying critical information.
- Entity Recognition: Extracting names, locations, and organizations from text.
- Sentiment Analysis: Understanding customer opinions from reviews and social media.
- Language Modeling: Enhancing search, enabling intelligent text completion.
- Speech Recognition and Synthesis: Voice assistants, transcription services.
- Translation: Global communication, expanding market reach.
Overview of NLP Tools: Introduction to services that provide pre-built NLP capabilities (e.g., Azure AI Language, Azure AI Speech service).

Module 5: Exploring Generative AI for Business Innovation

Understanding Generative AI Capabilities: Grasp the potential of AI models that can create new content, including:
- Text Generation: Creating marketing copy, drafting emails.
- Image Generation: Designing visuals, generating product mock-ups.
- Code Generation: Assisting developers, automating repetitive coding tasks.
Common Generative AI Scenarios: Identify how businesses can leverage generative AI for:
- Content Creation and Curation
- Personalization at Scale
- Customer Interaction Enhancement
Responsible AI in Generative AI: Emphasize the unique ethical considerations and guardrails for generative AI, such as bias, misinformation, and intellectual property.
Azure Services for Generative AI: A brief overview of platforms and models available (e.g., Azure AI Foundry, Azure OpenAI Service).

Ready to Get Started?

Join our training and learn how to strategically integrate AI into your business operations and drive innovation with Azure AI.

$149

$499

for a limited time

Your Instructor

Meet Your Instructor

Stephen Simon

Stephen SIMON, is a cloud and AI expert with hands-on experience in building and scaling developer communities. He has organized over 50 virtual conferences, hosted 600+ guests in his developer shows, and led 30+ national hackathons through HackIndia — India's largest Web3 and AI hackathon initiative. He works with technologies like Azure, Gemini, LangChain, Python, React, GitHub, and VS Code, and frequently speaks on topics such as cloud architecture, AI in real-world development, and emerging tech trends. His global speaking engagements include Experts Live Europe and WOW Summit Hong Kong, and he is the host of "Azure for Sure" and "A Dash of .NET."

5k+

Students taught

4k+

Students placed

10+

Years of experience

Frequently Asked Questions

Is this training for me?

Yes, if you're a business leader or decision-maker looking to understand and leverage AI for your organization. No prior technical background required.

Do I need to know how to code?

Not at all! This course is designed for non-coders and focuses on using AI tools and services without writing any code.

What will I be able to do after this?

You'll be able to identify AI opportunities, lead AI initiatives, and make informed decisions about integrating AI into your business.

What if I miss a class?

No problem. Every class is recorded, and you'll get lifetime access to all recordings to watch anytime.

Back to Trainings