Best FREE AI Courses for Beginners in 13 Minutes 🔥| Become an AI Engineer in 2024

Introduction

This tutorial provides a comprehensive guide to the best free AI courses available for beginners, as outlined in the video by Ishan Sharma. With the growing demand for generative AI skills in 2024, this guide will help you upskill from the comfort of your home. Whether you're a student, freelancer, or professional looking to transition into AI, these resources will equip you with the foundational knowledge you need.

Step 1: Learn Basic Mathematics

A solid understanding of mathematics is crucial for AI. Start with these resources:

• 3Blue1Brown: Offers intuitive explanations of mathematical concepts.
• FreeCodeCamp: Provides a comprehensive introduction to essential math skills.

Step 2: Master Python Programming

Python is a fundamental language for AI development. Explore these courses to build your Python skills:

• FreeCodeCamp's Data Analysis with Python Course: A hands-on approach to learning Python for data analysis.
• Harvard's CS50 Introduction to Python: A more structured and rigorous Python course.

Step 3: Understand Data Analysis

Data analysis is vital in AI. Enhance your skills with these resources:

• FreeCodeCamp: Offers in-depth tutorials on data analysis techniques and tools.

Step 4: Study Convolutional Neural Networks (CNN)

CNNs are essential for image processing and understanding. Use the following resources:

• Stanford's CS231n Course: A renowned course that covers CNNs and their applications.

Step 5: Dive into Natural Language Processing

Natural Language Processing (NLP) is crucial for AI applications involving language. Recommended courses include:

• Stanford's NLP Specialization: Comprehensive coverage of NLP techniques.
• DeepLearning.ai's NLP Specialization: A structured approach to learning NLP.

Step 6: Explore Generative AI Basics

Familiarize yourself with the fundamentals of generative AI through these courses:

• DeepLearning.ai's ChatGPT Prompt Engineering for Developers: Learn how to create effective prompts for generative models.

Step 7: Get Introduced to Large Language Models

Understanding large language models is essential. Check out:

• YouTube Video on Large Language Models: A beginner-friendly introduction to the concepts.

Step 8: Learn Python AI Techniques

To apply your Python skills to AI, consider:

• FreeCodeCamp's Mastering RAG from Scratch: A tutorial focused on Retrieval-Augmented Generation (RAG).

Step 9: Understand Career Essentials in Generative AI

Prepare for a career in AI with these relevant resources:

• LinkedIn Learning: Career essentials in generative AI by Microsoft and LinkedIn.

Step 10: Study Ethics in Generative AI

Ethics is a critical aspect of AI development. Explore these resources:

• LinkedIn Learning's Course on Generative AI Ethics: Understand the ethical implications and urgency in the field.

Step 11: Take Google Generative AI Courses

Google offers structured learning paths for generative AI:

• Beginner Course: Google Generative AI Beginner Course
• Intermediate Course: Google Generative AI Intermediate Course
• Advanced Course: Google Generative AI Advanced Course

Conclusion

With these free resources, you can build a strong foundation in AI and prepare for a successful career in this dynamic field. Start with the basics of mathematics and programming, then gradually advance to specialized topics like NLP and generative AI. By taking advantage of these courses, you'll be well-equipped to navigate the rapidly evolving landscape of AI technologies. Happy learning!