A non-technical introduction to AI and its buzz words

A non-technical introduction to AI and its buzz words, available at $19.99, has an average rating of 3.94, with 20 lectures, based on 8 reviews, and has 25 subscribers.

You will learn about Understand AI and its buzz words – Data Science, Machine Learning, Deep Learning, NLP, Computer Vision, etc. Understand different steps of model training like data collection, choosing model, training a model and deploying the model to the production environment, etc Get equipped to work with an AI team coming from a non-technical background. eg: HR, Product Manager, CEO, etc Understand AI jargon and be ready to learn on the go. This course is ideal for individuals who are Non-technical audience who want to understand AI and its various components. It is particularly useful for Non-technical audience who want to understand AI and its various components.

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Summary

Title: A non-technical introduction to AI and its buzz words

Price: $19.99

Average Rating: 3.94

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understand AI and its buzz words – Data Science, Machine Learning, Deep Learning, NLP, Computer Vision, etc.

Understand different steps of model training like data collection, choosing model, training a model and deploying the model to the production environment, etc

Get equipped to work with an AI team coming from a non-technical background. eg: HR, Product Manager, CEO, etc

Understand AI jargon and be ready to learn on the go.

Who Should Attend

Non-technical audience who want to understand AI and its various components.

Target Audiences

Non-technical audience who want to understand AI and its various components.

This short course focuses on introducing artificial intelligence and all its buzz words to the audience in a non-technical manner.

This is the first of its kind online course taught by realistic AI avatars !!!

As an HR, Product Manager, or CEO you might interact with AI teams and AI terms on a day-to-day basis.

This course demystifies all the buzz words and explains them in layman terms.

You will feel confident to work with AI teams and understand the AI jargon.

There are no prerequisites to take this course. Just bring in your enthusiasm to learn.

The course outline is shown below :

? What is Artificial Intelligence (AI) and its various applications?

? What is data science and what are the different components of it?

? Machine learning (ML) and its components like supervised learning, unsupervised learning, and reinforcement learning.

? Deep learning (DL) and the special focus of it inside Machine learning.

? What is Computer vision (CV)and its various applications?

? What is natural language processing (NLP)and its various applications?

? Model trainingand model deployment.

? Different steps of model training like data collection, data preparation, choosing a model, training a model, evaluating a model, tuning the hyperparameters of a model, and deploying the model to the production environment, etc.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Introduction and Outline

Chapter 2: AI and its applications

Lecture 1: Artificial Intelligence and its applications

Chapter 3: Components of AI

Lecture 1: What is Data Science?

Lecture 2: AI and its various components

Lecture 3: Components of Machine Learning

Lecture 4: Supervised Learning – Components of ML

Lecture 5: Unsupervised Learning – Components of ML

Lecture 6: Reinforcement Learning – Components of ML

Lecture 7: Deep Learning – Special Focus

Lecture 8: Computer Vision and its applications

Lecture 9: Natural Language Processing and its applications

Chapter 4: Model training and deployment

Lecture 1: Introduction to model development and deployment

Lecture 2: Data Collection and Cleaning

Lecture 3: Choosing a AI model

Lecture 4: Training an AI model

Lecture 5: Evaluation of an AI model

Lecture 6: Parameter Tuning of an AI model

Lecture 7: Model deployment

Lecture 8: Transfer Learning and Fine Tuning in AI

Chapter 5: Bias in AI and ways to mitigate it

Lecture 1: Bias in AI and countering it

Instructors

Ramsri Golla
Lead Data Scientist (NLP & CV)

Rating Distribution

1 stars: 1 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 2 votes

5 stars: 3 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!