Artificial Intelligence Course

Advance your career with this AI and Machine Learning course and master in-demand skills like ML, deep learning, NLP, computer vision, reinforcement learning, generative AI, prompt engineering, and ChatGPT among others.

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Price : 1000 USD $499

Nvidia CEO: To ensure job security in a rapidly evolving market, 
mastering AI tools and integrating them into your workflow isessential.

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3 to 4 weeks of program (Monday & Friday from 6:30PM to 9:30PM PST)

Introduction to Artificial Intelligence Course

AI will change many fields and redefine the knowledge economy. AI will create a 15 trillion contribution to the world economy by 2030. AI will take away many jobs but at the same time create new opportunities. This course is designed to help you have basic fundamental understanding of AI using the latest technologies from Microsoft Azure AI- Machine Learning platform.

In this topic you will learn from scratch how AI is changing the world- Siri, Alexa, etc.,
  • Business case for AI.
  • Difference between AI and ML.
  • How AI is transforming the world.
  • ChatGPT and OpenAI- Microsoft.
  • How future will look like with AI.
At the end of this topic you will have an understanding of the AI world at a high level.
In this topic you will learn about AI as an industry and where the money is coming from and going into- this will give you an idea on future opportunities:
  • Who are the major players in AI space?
  • What are the most popular technologies coming up?
  • How investments are moving into AI space- VC funding etc?
  • Where major jobs can be found and how?
  • Certifications and knowledge creation- industry and academia - MIT, Cornell, Microsoft,etc.,
The session will conclude with knowledge and understanding of AI as an industry.
In this lesson we'll learn:
  • Microsoft's cloud-based solutions for AI and Machine Learning.
  • The organization of an AI and ML Team and various stakeholders that take part in AI and ML initiatives.
  • A brief history of AI.
  • The prerequisites for the rest of the course.
  • When to use AI and ML, and when not?
By the end of this lesson, you'll be ready and prepared for the rest of the course.
This topic will cover the following components:
  • The relationship between AI and ML.
  • The five workloads for AI and ML and have an understanding of the common use cases.
  • Responsible AI and the application of ethics to the topic of AI.
  • Responsible ML and the ethical responsibilities of researchers, data scientists, and employees at organizations performing machine learning tasks.
By the end of this lesson, you will have a good idea of the main fundamental concepts we need to be able to start using AI and ML tools in Microsoft Azure.
  • Key Machine Learning Concepts to craft a foundation for following lessons.
  • Different approaches to ML, such as Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning.
  • Core tasks in building AI and ML solutions including Automated ML and Azure ML.
  • An overview of Azure ML around Azure ML Designer and ML Pipelines.
  • By the end of this lesson, you will have created three separate machine learning models using Azure Machine Learning and deployed two of them to production.
As a part of this topic, we will switch gears and focus on specialized AI services for specific AI and ML workloads. We'll learn:
  • Object Detection and Classification with Azure Computer Vision.
  • Image Classification with Azure Custom Vision.
  • Facial Recognition with Azure Face service.
  • Read text (OCR) with Azure Computer Vision.
  • Extracting information from forms with Azure Form Recognizer.
By the end of this lesson, you will be ready to implement various capabilities of Azure Computer vision into your applications and learn to apply it in real world scenarios.
We will build understanding of AI workloads that require Natural Human Language Understanding. We will cover following-
  • Key Phrase and Entity extraction with Text Analytics to get insights about documents.
  • Intent extraction through Language Understanding to figure out a sentence's goal is.
  • Speech recognition and synthesis of speech from text.
  • Text and Speech Translation.
At the end of this lesson, you will be ready to implement various NLP capabilities of Azure Cognitive Services into your applications. Some of these capabilities will be used in the next lesson when building conversational AI systems on MS Azure AI.
How humans engage in conversations with AI, experiences between users and computers. We will learn:
  • What Conversational AI is and how it works.
  • Working to create a knowledge base with Azure QnA Maker.
  • Actions to Deploy an automated bot to Azure Bot Service.
  • Learning to Use the Azure Bot Service channels.
At the conclusion of this lesson, you will build a chatbot backed by a knowledge base from start to finish to be able to apply to a project.
  • How tough is the exam.
  • How many questions.
  • Pricing and time taken.
  • Exam content and some practice questions.
  • Getting ready exam tips and tricks, register for exam 99$.
  • Other certifications that you can pursue from Google, Amazon, MIT, Cornell, etc.
  • At the end of this topic you will be able to answer what will it take for you to get certified in Microsoft AI 900 exam and pass it with fling colors. It will also give you an idea on other certifications in the space.
This topic will be the last topic of the course and prepare you for applying knowledge and certifications gained to find a suitable role
  • Data Analyst, Data Engineer, Data Scientist- can start from Data Analyst.
  • Project Manager and AI- ML, CPMAI.
  • Product Manager in AI- ML.
  • Resume, mocks, and placement assistance.
The session will conclude with next steps for finding a job in the area of AI-ML.

Road Map To Artificial Intelligence Certification

Course Syllabus – Artificial Intelligence

In the AI space- Microsoft, Amazon, and Google are at the forefront. Microsoft invested $1 billion in OpenAI that owns ChaptGPT.

This course can help you get AI 900 certification from Microsoft on Azure Cloud.

Module 1

What is AI and benefits of AI?

Module 2

Major players in AI?

Module 3

Introduction to AI Fundamentals- Microsoft Azure

Module 4

AI and ML Core Concepts- Azure AI - Machine Learning Studio

Module 5

Machine Learning- Microsoft Azure

Module 6

Computer Vision- Azure

Module 7

Natural Language Processing- Microsoft Azure Cognitive

Module 8

Conversational AI- Microsoft AI Azure QnA-Bot

What You'll Earn

A practical grounding in artificial intelligence (AI) and its business applications, equipping you with the knowledge and confidence you need to transform your organization into an innovative, efficient, and sustainable company of the future.

The ability to lead informed, strategic decision-making and augment business performance by integrating key AI management and leadership insights into the way your organization operates.

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Frequently Asked Questions

You do not need to be a developer or know coding to take this course.
We cover the basics and fundamentals of AI as per undermentioned curriculum.
20-25 hours.
2-2.5 hours per class- 10 classes- total 25 hours- students will also work on Microsoft AI platform- 1 month long- weekends/weekdays- will depend on demand- sales- I am open to both.
Strategism AI Certification - For Microsoft Azure AI 900 Certification- Preparatoy Course.
No coding or technical knowledge is required.

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