AI ML Starter Course with No-Code AI Projects

AI & ML Starter Course with No-Code AI Projects, available at $49.99, has an average rating of 4.09, with 10 lectures, based on 281 reviews, and has 23970 subscribers.

You will learn about Basics of Human Brain & Artificial Neural Network – Biological Neurons & Artificial Neurons Difference between Artificial Intelligence, Machine Learning & Deep Learning 3 Machine Learning Techniques – Supervised Learning, Unsupervised Learning, Reinforcement Learning with examples Learn how to train, evaluate and optimize a Machine Learning model Day in a life of an AI/ML Engineer ML Model Evaluation Method – Confusion Matrix, Error, Recall, Precision, Accuracy ML Model Optimization Method – Learning Rate, Epoch, Batch Size ML Model Training – Using Open-Source Tools Hands-On Project 1 – Build a Machine Learning model using Healthcare Dataset Hands-On Project 2 – Build a Machine Learning model using Agriculture Dataset This course is ideal for individuals who are Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure. It is particularly useful for Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.

Enroll now: AI & ML Starter Course with No-Code AI Projects

Summary

Title: AI & ML Starter Course with No-Code AI Projects

Price: $49.99

Average Rating: 4.09

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Basics of Human Brain & Artificial Neural Network – Biological Neurons & Artificial Neurons

Difference between Artificial Intelligence, Machine Learning & Deep Learning

3 Machine Learning Techniques – Supervised Learning, Unsupervised Learning, Reinforcement Learning with examples

Learn how to train, evaluate and optimize a Machine Learning model

Day in a life of an AI/ML Engineer

ML Model Evaluation Method – Confusion Matrix, Error, Recall, Precision, Accuracy

ML Model Optimization Method – Learning Rate, Epoch, Batch Size

ML Model Training – Using Open-Source Tools

Hands-On Project 1 – Build a Machine Learning model using Healthcare Dataset

Hands-On Project 2 – Build a Machine Learning model using Agriculture Dataset

Who Should Attend

Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.

Target Audiences

Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.

Hi there!

This course aims to provide you with an overview of Artificial Intelligence (AI) & Machine Learning (ML) using simplified explanations and hands-on projects.

We will be covering the following topics in this course:

Introduction to Artificial Intelligence (AI) & Neural Networks

Difference between Artificial Intelligence, Machine Learning & Deep Learning

Standardized Architecture for AI & ML Systems

Machine Learning (ML) Algorithms – Supervised vs Unsupervised vs Reinforcement Learning

Day in a life of an AI & ML Engineer

Skills you will need for an AI & ML Engineer role

Methods to evaluate the performance of Machine Learning Models

Confusion Matrix, Accuracy, Precision, Recall

Epoch, Learning Rate, Batch Size

No-Code Hands-on AI & ML Projects with Open-Source Tools

Summary

This is the first version of this course and it will be updated as we continue to witness the evolution of Artificial Intelligence and Machine Learning. My goal is to ensure people from all over the world are able to access this course and are able to learn the fundamentals of AI & Machine Learning and apply the same in their journey.

You will benefit from this course if:

You want to learn the basics of AI & Machine Learning and you are looking for beginner-friendly hands-on exposure

You are contemplating switching your career to Artificial Intelligence & Machine Learning

You have a genuine interest in improving your understanding of AI & Machine Learning

You want to learn the standardized framework used to build and evaluate AI/ML Models

You are building a new startup and need to solidify your understanding of AI & ML concepts

Hope you will enjoy this course!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Human Brain & Artificial Neural Network

Lecture 1: Human Brain & Artificial Neural Network

Chapter 3: Artificial Intelligence (AI), Machine Learning (ML), & Deep Learning

Lecture 1: Artificial Intelligence (AI), Machine Learning (ML), & Deep Learning

Chapter 4: What is Machine Learning?

Lecture 1: What is Machine Learning?

Chapter 5: Machine Learning Algorithms

Lecture 1: Machine Learning Algorithms

Chapter 6: Day in a life of AI & Machine Learning Engineer

Lecture 1: Day in a life of AI & Machine Learning Engineer

Chapter 7: Machine Learning (ML) Model Performance Evaluation

Lecture 1: Machine Learning (ML) Model Performance Evaluation

Chapter 8: Project 1 – Pneumonia Detection Using Chest X-Ray & Ml

Lecture 1: Project 1 – Pneumonia Detection Using Chest X-Ray & Ml

Chapter 9: Project 2 – Fruit Classifier Using Image Dataset & ML

Lecture 1: Project 2 – Fruit Classifier Using Image Dataset & ML

Chapter 10: Summary

Lecture 1: Summary

Instructors

Prathamesh Khedekar
Sr. TPM | Ex – Motorola US & EU

Rating Distribution

1 stars: 7 votes

2 stars: 9 votes

3 stars: 61 votes

4 stars: 103 votes

5 stars: 101 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!