Generative AI:Beginner to Pro with OpenAI & Azure OpenAI from Udemy

Generative AI refers to a type of artificial intelligence technology that can generate new content based on the data it has been trained on. This includes text, images, music, video, and other forms of media. The AI learns from a large dataset to recognize patterns, styles, or features and then uses this understanding to create new, original content that mimics the input it has studied.

The course will present you with a foundational understanding of AI. The course has several modules where you will be explained basic concepts around AI, Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs) , ChatGPT , Azure Open AI

The Topics that will be covered are as follows:

AI Concepts & Workloads
What is AI ?Benefits of Artificial Intelligence (AI)Types of AI WorkloadsAI vs ML vs DLQuiz TimeAI Concepts Quiz
Machine Learning Machine Learning - Real World ExampleMachine Learning - Key TerminologiesWhat is Machine Learning ?Types of Machine LearningWhat is Supervised Machine Learning ?What is Classification in SML ?What is Regression in SML ?What is Unsupervised Machine Learning ?What is Re-inforcement Machine LearningWhat is a Jupyter NotebookDemo: Understanding the IRIS DatasetDemo: Creating & Training your ML Model

Deep Learning
What is Deep Learning ?
What is a Neural Network ?Deep Learning ModelsWhat is a Transformer Model?Demo: GANs - Deep Fake VideoDemo- Creating & Training Deep Learning Model
Generative AI
What is Generative AI ?Predictive AI vs Generative AIWhat is GPT ?GPT-3 vs GPT-4What is LLM ?
What is Embedding?
What is a Vector Database
Relationship between Embedding vs Vector DatabaseWhat is Prompt Engineering ?
AI Infrastructure
What is a GPU ?Demo: CPU Vs GPUWhat is High Performance ComputeWhat is RDMA Cluster Network
OpenAI

What is OpenAI ?

What is ChatGPT

Demo on chatgpt

Time to reach 100M users

Get an understanding of Various ChatGPT Models

GPT-3 vs GPT-4

What are tokens ?

Pricing Model for ChatGPT

Demo: How to make API Calls with

Demo: Image generation using DALL·E in the API

Demo: Convert Speech to Text

Azure OpenAI

What is Azure OpenAI

History behind Azure OpenAI

Models available with Azure OpenAI (regions)

Limits & Quotas

How Pricing works in Azure OpenAI

What is Azure OpenAI Studio ?

Chats Playground

Completions Playground

Creating Images using DALL-E

Bring your own Data - RAG with Azure AI Search

What is Azure AI Search

How Vector Search Works with Azure AI Search

Understanding the ACAS Data (Your Private Data)

Pre-reqs for RAG with Azure AI Search

Create a Storage Account

Create an Embedding Deployment

Create a chats deployment

Create Azure AI Search Resource

Uploads Documents to Chats Deployment

Perform Queries - Using your Own Data

Azure Open AI Fine Tuning
What is Fine Tuning ?
Understanding of Fine Tuning Regions & Models
Use Cases of Fine Tuning
Demo: Create Azure OpenAI Service in US East2
Demo: Prepare & Upload data
Demo: Create a Fine Tuning Job
Demo: Evaluate Fine Tuning Model
Demo: Deploy the Fine Tuned Model
Demo: Query the Fine Tuned Model-Part1
Demo: Query Fine Tuned Model - Part 2

Azure Open AI Content Filtering

What is Content Filtering ?

Categories Covered

Jailbreak / Prompt Shield

Demo: Impact of Content Filtering

What's inside

Learning objectives

Ai concepts & workloads
Machine learning foundations
Types of machine learning
Demo lab on machine learning
Deep learning foundations
Types of deep learning
Demo lab on deep learning
Generative ai foundations
Embeddings vs vector databases
Ai infrastructure

Openai / chatgpt / apis
Azure openai
Bring your own data - rag with azure ai search
Azure openai fine tuning
Azure openai content filtering
Azure openai - iam / rbac model
Azure openai - making api calls (python codes)
Assistants api
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Ai concepts & workloads
Machine learning foundations
Types of machine learning
Demo lab on machine learning
Deep learning foundations
Types of deep learning
Demo lab on deep learning
Generative ai foundations
Embeddings vs vector databases
Ai infrastructure
Openai / chatgpt / apis
Azure openai
Bring your own data - rag with azure ai search
Azure openai fine tuning
Azure openai content filtering
Azure openai - iam / rbac model
Azure openai - making api calls (python codes)
Assistants api
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Show less

Syllabus

What is AI ?

What is Classification in SML ?

AI Concepts & Workloads- Title

History of AI

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Examines ChatGPT, Azure OpenAI, and their various models

Ideal for those interested in industry-relevant skills in AI, machine learning, and natural language processing

Appeals to individuals curious about the potential of generative AI in various domains

Suitable for both beginners seeking a comprehensive grounding and professionals looking to enhance their AI knowledge

Offers a combination of theoretical foundations, practical demonstrations, and hands-on labs to enhance learning

Prepares learners for real-world applications of AI and its advancements, including ChatGPT, in various industries

Reviews summary

Practical generative ai with azure openai

According to learners, this course offers a largely positive experience for those aiming to master Generative AI, particularly with a strong focus on OpenAI and Azure OpenAI services. Students frequently highlight the clear explanations and practical, hands-on demos that make complex concepts like Retrieval Augmented Generation (RAG) and fine-tuning accessible. While it aims for a "Beginner to Pro" journey, some reviewers suggest a prior technical or IT background is beneficial for the faster-paced sections, especially those involving Azure deployments. The course is consistently praised for its up-to-date content, including recent models like GPT-4o, and its direct applicability for professional implementation, making it a valuable resource for developers and data scientists.

Instructor clarifies complex topics effectively.

"The instructor's explanations are concise and he provides good real-world examples."

"The instructor explains complex topics in an easy-to-understand manner."

"I found the instructor explained everything clearly, making even difficult concepts approachable."

Content is current and highly relevant for professional use.

"The content is up-to-date, even mentioning GPT-4o, which shows the instructor is keeping pace."

"The continuous updates, like mentioning GPT-4o, are a huge plus."

"The content is relevant and timely."

Well-structured progression from basics to advanced Gen AI concepts.

"The progression from basic AI concepts to advanced Azure OpenAI features is well-structured."

"A very comprehensive course. The coverage of LLMs, embeddings, vector databases, and RAG architectures was top-notch."

"A very good introduction to Generative AI, especially the sections on OpenAI and Azure OpenAI. I appreciated the structured approach..."

Provides clear, hands-on demonstrations for practical application.

"Absolutely fantastic! ... The demos are incredibly clear and hands-on, making complex concepts easy to grasp."

"The practical labs are the highlight."

"The detailed walkthroughs of Azure OpenAI Studio and API calls in Python are exactly what I needed for my work projects."

"I appreciated the focus on Azure OpenAI... The instructor provided clear explanations and practical examples."

Some learners desired more independent exercises beyond demos.

"I wished there were more exercises or assignments beyond just following the demos, to truly solidify the concepts."

"I would suggest adding more complex scenarios or troubleshooting tips for the Azure deployments, as real-world issues often arise."

Best suited for those with some prior technical or IT background.

"Some sections, particularly on fundamental ML/DL, felt a bit rushed if you're truly a 'beginner' with no prior background..."

"I came into this course as a complete beginner with no tech background... I found myself struggling with the prerequisites implicitly assumed."

"The 'Beginner to Pro' title might be a bit ambitious for complete novices."

"For those with some technical background, it's a good starting point for Azure OpenAI, but don't expect to be a 'pro' without further self-study."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI:Beginner to Pro with OpenAI & Azure OpenAI with these activities:

Review basic SQL commands

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Start the course with a refreshed understanding of the fundamental commands and structures of the SQL language.

Browse courses on SQL

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Review online documentation or tutorials on basic SQL commands, such as SELECT, WHERE, and JOIN.
Practice writing SQL queries to retrieve and filter data from a sample database.

Participate in SQL discussion forums and communities

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Engage with other SQL learners and practitioners to share knowledge, discuss best practices, and get support when needed.

Browse courses on SQL

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Identify online forums or communities dedicated to SQL discussions, such as Stack Overflow or Reddit.
Actively participate in discussions, ask questions, provide answers, and share your own experiences.

Explore advanced SQL features and techniques

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Expand your knowledge of SQL by delving into advanced features and techniques that can enhance your data manipulation and analysis capabilities.

Browse courses on SQL

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Identify specific advanced SQL features or techniques that you want to learn, such as window functions, stored procedures, or triggers.
Find online tutorials or courses that provide comprehensive explanations and examples of these advanced concepts.
Follow the tutorials, practice writing code, and experiment with the features in a development environment.

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Solve SQL coding challenges

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Enhance your problem-solving skills and reinforce your understanding of SQL syntax by tackling coding challenges.

Browse courses on SQL

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Find online platforms or resources that offer SQL coding challenges.
Attempt to solve the challenges independently, focusing on optimizing your queries and code efficiency.
Review solutions and explanations to gain insights into alternative approaches and best practices.

Mentor junior SQL learners or enthusiasts

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Share your knowledge and experience to support the growth of aspiring SQL learners and contribute to the community.

Browse courses on Mentoring

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Identify platforms or organizations where you can connect with junior SQL learners who need guidance.
Offer your support, answer questions, provide feedback, and encourage their learning journey.

Contribute to open-source SQL projects or libraries

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Make meaningful contributions to the SQL community by participating in open-source projects and extending the capabilities of existing libraries.

Browse courses on Open Source

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Identify open-source SQL projects or libraries that align with your interests and skills.
Review the project documentation and codebase to understand its purpose and architecture.
Identify areas where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
Submit pull requests with clear explanations and well-tested code.

Develop a data visualization dashboard

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Demonstrate your proficiency in data analysis and presentation by creating an interactive dashboard that visualizes key insights from a dataset.

Browse courses on Data Visualization

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Select a dataset and identify the key metrics and insights you want to convey.
Choose a data visualization tool and learn its features for creating interactive dashboards.
Design and develop the dashboard, ensuring it is visually appealing, user-friendly, and effectively communicates the data insights.
Test the dashboard and make necessary adjustments to improve its functionality and usability.

Develop a data-driven solution to a real-world problem

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Apply your SQL skills to a practical problem and demonstrate your ability to extract insights, make informed decisions, and create value from data.

Browse courses on Data Analysis

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Identify a real-world problem or challenge that can be addressed using data analysis and SQL.
Gather and preprocess the necessary data from relevant sources.
Analyze the data using SQL, identify patterns, and draw meaningful conclusions.
Develop a data-driven solution or recommendation based on your analysis.
Present your findings and solution in a clear and compelling manner.

Career center

Learners who complete Generative AI:Beginner to Pro with OpenAI & Azure OpenAI will develop knowledge and skills that may be useful to these careers:

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Generative AI

Beginner to Pro with OpenAI & Azure OpenAI

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Syllabus

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Reviews summary

Practical generative ai with azure openai

Activities

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