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Beginner Guide to Artificial Intelligence & Machine Learning
Rating: 4.4 out of 5(7 ratings)
50 students

Beginner Guide to Artificial Intelligence & Machine Learning

An Insight and comprehensive overview of the concepts of AI and ML
Created byPhani Avagaddi
Last updated 11/2024
English

What you'll learn

  • Introduction to Artificial Intelligence
  • Introduction to Machine Learning
  • Understanding the Roles available in AI career path
  • Planning your career building path in AI and ML specific to the roles
  • Build a portfolio of work to have on your resume
  • Supervised and Unsupervised Learning
  • Learn which Machine Learning model to choose for each type of problem
  • Learn how to program in Python using the latest Python 3
  • Learn to pre process data, clean data, and analyze large data

Course content

4 sections • 8 lectures • 16h 14m total length

  • Introduction2:03:54
  • What is Artificial Intelligence and Machine Learning?1:54:32

    Explore the fundamentals of artificial intelligence and machine learning, including supervised, unsupervised, and reinforcement learning, deep learning, neural networks, transfer learning, and key ethical and privacy considerations.

Requirements

  • Beginners from IT or Non IT any one can watch these videos
  • AI Enthusiasts who wants to enter into the AI world
  • Career shifting people who want to know AI and ML
  • Whoever wants to understand the foundational concepts can watch these sessions

Description

Implement Machine Learning algorithms

How to improve your Machine Learning Models

Build a portfolio of work to have on your resume

Supervised and Unsupervised Learning

Explore large datasets using data visualization tools like Matplotlib

Learn NumPy and how it is used in Machine Learning

Learn to use the popular library Scikit-learn in your projects

Learn to perform Classification and Regression modelling

Master Machine Learning and use it on the job

Learn which Machine Learning model to choose for each type of problem

Learn best practices when it comes to Data Science Workflow

Learn how to program in Python using the latest Python 3

Learn to pre process data, clean data, and analyze large data.

Developer Environment setup for Data Science and Machine Learning

A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided

Real life case studies and projects to understand how things are done in the real world

Guidance to choose your career path based on your background and build the path in next 6 months

Comprehensive understanding on foundational concepts like Neurons, Perceptron, Multilayer Perceptron, Transformers.

Good overview on Convolution Neural Networks and Recurrent Neural Networks

Who this course is for:

  • Fresh Graduates, IT professionals shifting their career to AI path, Non IT domain experties

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