Developing Generative AI Applications on Azure

Developing Generative AI Applications on Azure, available at $27.99, with 161 lectures, and has 4 subscribers.

You will learn about Master Azure OpenAI Service: Learn to deploy and manage Generative AI applications using Azure OpenAI Service Hands-on Linux and Python: Gain practical skills in Linux and Python essential for AI development. Build AI Models: Acquire the expertise to design and build generative AI models from scratch. Master Machine Learning Concepts: Learn the core concepts and techniques of machine learning, including supervised and unsupervised learning, model evaluation, Develop Generative AI Applications: Acquire skills to build and deploy generative AI models on aws bedrock, leveraging advanced techniques and tools. This course is ideal for individuals who are This course is ideal for anyone interested in entering the field of AI, including beginners with no prior coding experience. It is also suitable for professionals looking to expand their knowledge in Linux, Python, Machine Learning, and Generative AI. Whether you are a student, an aspiring data scientist, or a tech enthusiast, this comprehensive pathway will equip you with the necessary skills to excel in the AI domain. or This course is a zero-to-hero program designed to take you from a beginner to an expert. It is particularly useful for This course is ideal for anyone interested in entering the field of AI, including beginners with no prior coding experience. It is also suitable for professionals looking to expand their knowledge in Linux, Python, Machine Learning, and Generative AI. Whether you are a student, an aspiring data scientist, or a tech enthusiast, this comprehensive pathway will equip you with the necessary skills to excel in the AI domain. or This course is a zero-to-hero program designed to take you from a beginner to an expert.

Enroll now: Developing Generative AI Applications on Azure

Summary

Title: Developing Generative AI Applications on Azure

Price: $27.99

Number of Lectures: 161

Number of Published Lectures: 161

Number of Curriculum Items: 161

Number of Published Curriculum Objects: 161

Original Price: ?1,299

Quality Status: approved

Status: Live

What You Will Learn

Master Azure OpenAI Service: Learn to deploy and manage Generative AI applications using Azure OpenAI Service

Hands-on Linux and Python: Gain practical skills in Linux and Python essential for AI development.

Build AI Models: Acquire the expertise to design and build generative AI models from scratch.

Master Machine Learning Concepts: Learn the core concepts and techniques of machine learning, including supervised and unsupervised learning, model evaluation,

Develop Generative AI Applications: Acquire skills to build and deploy generative AI models on aws bedrock, leveraging advanced techniques and tools.

Who Should Attend

This course is ideal for anyone interested in entering the field of AI, including beginners with no prior coding experience. It is also suitable for professionals looking to expand their knowledge in Linux, Python, Machine Learning, and Generative AI. Whether you are a student, an aspiring data scientist, or a tech enthusiast, this comprehensive pathway will equip you with the necessary skills to excel in the AI domain.

This course is a zero-to-hero program designed to take you from a beginner to an expert.

Target Audiences

This course is ideal for anyone interested in entering the field of AI, including beginners with no prior coding experience. It is also suitable for professionals looking to expand their knowledge in Linux, Python, Machine Learning, and Generative AI. Whether you are a student, an aspiring data scientist, or a tech enthusiast, this comprehensive pathway will equip you with the necessary skills to excel in the AI domain.

This course is a zero-to-hero program designed to take you from a beginner to an expert.

What You’ll Learn:

The “Zero to Hero Program” is designed to guide you through a comprehensive learning journey, starting from the very basics and progressing to advanced topics that are essential before diving into Generative AI on Azure cloud. This program is structured to be accessible to everyone, including those who do not have a development background but have experience in IT. The aim is to ensure that even non-developers can gain the necessary knowledge and skills to effectively work with Generative AI on Azure’s platform.

15% Theory and 85% Hands-on Lab Sessions

Understand Linux and Python:
Gain foundational knowledge of Linux and Python, essential for developing and deploying AI applications.

Master Machine Learning Concepts:
Learn core concepts and techniques of machine learning, including supervised and unsupervised learning, model evaluation, and optimization.

Develop Generative AI Applications:
Gain hands-on knowledge on NLP, Hugging Face, LangChain, prompt engineering, and fine-tuning LLM models.

Implement AI Safeguards:
Learn how to apply responsible AI policies, including filtering harmful content and redacting sensitive information, to ensure ethical AI application deployment.

Why Enroll:

Expert Instruction:
Benefit from the expertise of Anil Bidari, a seasoned professional with over 18 years of experience in cloud computing, DevOps, and Generative AI.

Hands-On Learning:
We have 80% practical demo videos and source guide provided.

Comprehensive Curriculum:
Covering everything from foundational knowledge to advanced deployment techniques.

Join this course to become proficient in developing Generative AI applications on Azure AI, ensuring you stay ahead in the rapidly evolving field of AI.

Course Curriculum

Chapter 1: Linux Foundation

Lecture 1: Learn Linux Concepts Part -1

Lecture 2: linux concepts part-2

Lecture 3: Choose Linux Cloud Environment

Lecture 4: Demo: Create Linux Vm on AWS Cloud

Lecture 5: Demo: Create Linux Vm on Azure Cloud

Lecture 6: Demo: Create Linux Vm on Google Cloud

Lecture 7: Demo: Linux Directories

Lecture 8: Demo: Linux Packages Part-1

Lecture 9: Demo: Linux Packages Part-2

Lecture 10: Demo: Linux Essential Commands

Chapter 2: Python Foundation

Lecture 1: Python Concepts part -1

Lecture 2: Python Concepts part -2

Lecture 3: Python Concepts part -3

Lecture 4: Python Concepts part -4

Lecture 5: Demo: Python Operators Part-1

Lecture 6: Demo: Python Operators Part-2

Lecture 7: Demo: Python Operators Assignment Answers

Lecture 8: Demo: Python Data Types Part -1

Lecture 9: Demo: Python Data Types Part -2

Lecture 10: Demo: Python Data Types Assignment Answers

Lecture 11: Demo: Python List Part-1

Lecture 12: Demo: Python List Part-2

Lecture 13: Demo: Python List Assignment Answers

Lecture 14: Demo: Python Tuples Part -1

Lecture 15: Demo: Python Tuples Part -2

Lecture 16: Demo: Python Dictionary Part-1

Lecture 17: Demo: Python Dictionary Part-2

Lecture 18: Demo: Python Dictionary Assignment Answers

Lecture 19: Demo: Python File Handling Part-1

Lecture 20: Demo: Python File Handling Part-2

Lecture 21: Demo: Python Functions Part-1

Lecture 22: Demo: Python Functions Part-2

Lecture 23: Demo: Python Variables Part-1

Lecture 24: Demo: Python Variables Part-2

Lecture 25: Demo: Python Variables Assignment Answers

Chapter 3: Machine Learning Concepts

Lecture 1: Define Machine Learning Part-1

Lecture 2: Define Machine Learning Part-2

Lecture 3: Supervised and Unsupervised Learning Part-1

Lecture 4: Supervised and Unsupervised Learning Part-2

Lecture 5: Reinforcement Learning

Lecture 6: Difference between ML Types

Lecture 7: Neural Networks

Lecture 8: Applications of Deep Learning

Lecture 9: ML Algorithms Decision Trees

Lecture 10: ML Algorithms Linear Regression

Lecture 11: ML Algorithms CNN

Lecture 12: ML Algorithms RNN

Lecture 13: Summary of ML Algorithms

Lecture 14: Data Prep and Cleaning

Lecture 15: Evaluating Machine Learning Models

Lecture 16: Ethics in Machine Learning

Lecture 17: Future of Machine Learning

Chapter 4: Machine Learning Hands-on

Lecture 1: Demo: Numpy Labs

Lecture 2: Demo: Pandas

Lecture 3: Demo: Numpy and Pandas

Lecture 4: Demo: Supervised Learning Part-1

Lecture 5: Demo: Supervised Learning Part-2

Lecture 6: Demo: Supervised Learning Part-3

Lecture 7: Demo: Supervised Learning Part-4

Lecture 8: Demo: Unsupervised Learning Part-1

Lecture 9: Demo: Unsupervised Learning Part-2

Lecture 10: Demo: Linear Regression Single Variable

Lecture 11: Demo: Linear Regression Multi Variable

Chapter 5: GenAI for Developers

Lecture 1: GenAI course Overview

Lecture 2: Define GenAI

Lecture 3: Demo: Generate Image and music in single prompt

Lecture 4: Applications of GenAI

Lecture 5: Demo: Generate Videos in Single Prompt

Lecture 6: Technologies Behind GenAI

Lecture 7: Ethics and Legal in AI

Lecture 8: Demo: Generate ppt in 30 secs

Lecture 9: Managing GenAI Projects

Lecture 10: Security in GenAI

Lecture 11: Future of Ai

Lecture 12: Demo: Generate AI Voice in Single Prompt

Lecture 13: GenAI in Finance

Lecture 14: GenAI in Sales and Marketing

Lecture 15: GenAI in HR Management

Lecture 16: Demo: Generate AI Avatar Videos

Lecture 17: GenAI in Healthcare

Chapter 6: Prompt Engineering

Lecture 1: Define Prompt Engineering

Lecture 2: Prompting Technique

Lecture 3: Behind the Scenes Prompt to Output

Lecture 4: Demo: Prompt with ChatGPT – 3.5

Lecture 5: Demo: Prompt with ChatGPT – 4.0

Lecture 6: Demo: Prompt with Anthropic Claude

Lecture 7: Demo: Prompt with Google Gemini

Chapter 7: NLP foundation

Lecture 1: Introduction to NLP

Lecture 2: Applications of NLP

Lecture 3: Evolution of NLP Part-1

Lecture 4: Evolution of NLP Part-2

Lecture 5: Challenges in NLP

Lecture 6: NLP Tasks Part-1

Instructors

Anil Bidari
AWS Authorised Instructor, Generative AI consultant

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 0 votes

4 stars: 0 votes

5 stars: 0 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!