Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
17 Hour(s) 15 Minute(s)
Language
English
Taught by
Anand George
Rating
Course Overview
NEW 2025 UPDATED-OpenAI, Agents, LLM, AI Foundry,Computer Vision,NLP, Search,Real Exam simulation,250+ Practice Question
In Chapter 1, we cover the fundamentals of artificial intelligence, focusing on:
Introduction to Artificial Intelligence (AI) and its importance.
Core concepts: Neural Networks and Large Language Models (LLMs).
How to download and run LLMs locally.
Chapter 2 is all about Azure AI services, offering hands-on guidance for deploying and using Azure AI Services:
Azure AI Vision - Image Analysis, OCR, Video Analysis, Face Service
Azure AI Content Safety - detects harmful user-generated and AI-generated content in applications and services.
Azure AI Language - Understanding and analyzing text, Conversational Language Analysis, Custom Question Answering
Azure AI Speech - Provides speech to text and text to speech capabilities
Azure AI Translator - Multi-language solutions
Azure AI Document Intelligence - Document processing solutions
Azure AI Search - Search-as-a-service solution offering full-text search, vector similarity search
Azure OpenAI Models: ChatGPT, DALL·E, embeddings for LLMs, and image generation.
Building custom AI models and containerizing services for on-premises/edge deployment.
MLOps & CI/CD: Automating deployment and lifecycle management of AI solutions.
Fine tuning OpenAI Models
Bringing your own data to Models
Manage, monitor, and secure an Azure AI service
Each lesson is followed by a QUIZ to help you consolidate your learning.
Chapter 3 contains new updated topics based on 2025 Updates:
Agentic AI Solutions and Azure AI Foundry.
Sematic Kernel and AutoGen frameworks.
Azure AI Foundry features: Evaluation, Tracing, Prompt Templates, Prompt Flow, Model Catalog.
RAG pattern by grounding a model in your data
MCP (Model Context Protocol)
Each lesson is followed by a QUIZ to help reinforce what you've learned.
Finally, Chapter 4 is dedicated to Azure AI 102 exam preparation:
Focused on Azure AI Associate Certification objectives.
Includes study guides and practice questions for exam readiness.
Proper explanation for all answers and other options along with reference link to Microsoft Documentation.
Exam Simulation.
Course Content
- 4 section(s)
- 53 lecture(s)
- Section 1 Introduction to AI
- Section 2 Azure AI Services
- Section 3 NEW UPDATES 2025 - Azure AI Foundry, Agentic Solution & GenAI
- Section 4 Azure AI 102 Certification Tips and Practice Tests
What You’ll Learn
- Deploy and Manage Azure AI Services - Vision, Content Safety, Language, Speech, Translator, Document Intelligence, Search, OpenAI
- Basic knowledge on neural networks and LLM
- Microsoft Certified: Azure AI Engineer Associate Azure AI 102
- Build generative AI solutions with Azure AI Foundry
- Use Semantic Kernel and AutoGen Frameworks to deploy agents
- Model Context Protocol (MCP)
- Deploy custom azure AI models and MLOps/CICD pipeline.
- Container solutions for Azure AI Services
- Build Agents
- RAG by grounding a model in your data
- Deploy Azure AI services using REST APIs, SDK and Python.
Skills covered in this course
Reviews
-
SSiddhartha Sekhar
Very hands on and code centric approach, which I prefer for learning any solution, from the bottom up. Anand is deep into the subject and can really cut through the noise to focus on the essentials without overwhelming his audience ( Code Overwhelm with SDK class names and function names is a real thing) . Anand also has an unique and impressive delivery cadence which demands and holds your attention. BUY THIS COURSE, IF YOU WANT TO BUILD AI-APPLICATIONS USING AZURE AI AND NOT JUST ACHIEVE A CERTIFICATION . For the Certification centric: The last 2 mocks at the end of the course will provide you with enough exposure to pass the exam ( provided you review the questions and understand why one option is correct and the others are not)
-
AAnuroop S
Course is good. Pros: 1. Gives good understanding of AI and azure AI services Cons: 1. Videos are long . 2. Coding resources links missing. had difficult in finding where the python code was from. 3. Need improvement code explanation and allowing students to code. Suggestions: 1. Split into small videos of max 15 min 2. Please add where the code was from and attach as resource in lectures to download directly. 3. For code explanations it will be really good if you follow this method -> Ex: https://www.udemy.com/course/the-complete-guide-to-angular-2
-
LLudwig Reinhard
Perfect especially for me who just gets started with this topic and does not have a tech background
-
PPhilip
Best Azure AI-102 video I have ever bought. I have only gone through 60% of the vidoes and it's been very interesting and well-simplified
