AI & ML Starter Course with No-Code AI Projects [2024]

Learn Artificial Intelligence & Machine Learning with No-Code AI Hands-On Projects

Ratings: 3.93 / 5.00




Description

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!


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.