
HP course.
π§© Part 1: Introduction to Artificial Intelligence
What is AI?
Types of AI: Narrow vs. General
What AI is not: Clearing up misconceptions
The Role of Data in AI
Importance of Data
AI in Everyday Life
AI Applications Across Industries
Fundamentals of Machine Learning
AI in Action: A Cautionary Tale About Bias
Machine Learning Tools for Professional Development
π Part 3: Diving Into Deep Learning
What is Deep Learning?
Introduction to Generative AI?
What is generative AI?
Large Language Models (LLMs) and their function
Practical Deep Learning and Generative AI Applications
AI in Action: Expert Systems in Healthcare
π οΈIntegrations and Applications
π οΈ Part 4: Using AI Tools to Grow Personally and Professionally.
1. AI Tools Overview
2. Introduction to ChatGPT, Gemini, and other LLMs
3. Features and use cases
βοΈ Part 5:
Ethical Considerations and Future Trends.
1. Ethics in AI
2. Privacy concerns
3. Bias and fairness
4. Regulatory and legal considerations
5. The Future of A
Conclusion
Course recap and summary.
An intro
πΉ Elements of AI online course! {Reading, No Videos}
Our goal is to demystify AI. The Elements of AI is a series of online courses created by MinnaLearn and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and canβt) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
Part 1
Introduction to AI
An Introduction to AI is an online course for everyone interested in learning what AI is.
1. What is AI?
2. AI Problem Solving.
3. Real World AI.
4 Machine Learning.
5. Neural Networks.
6. Implications.
Part 2
Building AI {Advanced AI}
Building AI is an online course where youβll learn about the actual algorithms that make creating AI methods possible. Some basic Python programming skills are recommended, but not necessary, to get the most out of the course.
1. Getting started with AI
2. Chapter. Dealing with uncertainty.
3 Chap. more Machine Learning.
4 Chap. More Neural Networks.
5 Chap. Conclusion.
π Generative AI & Business Applications
AI Training Courses for Generative AI
Here, weβve compiled a list of the best free AI training courses that focus on generative AI and how you can harness it, as well as foundational concepts in artificial intelligence. A lot of these courses are designed to be introductory sessions and geared toward beginners.
1. Generative AI Learning Path (5 Courses)
2. Transform Your Business With AI Course
3. Machine Learning Foundational Course
4. Career Essentials In Generative AI Training Course
5. Fundamentals of ChatGPT Training Course
6. Phil AI Crash Course
5. The Future of AI
π§βπ» Advanced AI for Programmers & Developers
Advanced AI Training Courses for Programmers, Developers & Tech Experts.
Up next, we have more advanced courses geared towards AI programming and development.
1. Introduction to Artificial Intelligence with Python
2. Intro to TensorFlow for Machine Learning
3. Georgia Techβs Reinforcement Learning
4. Become an AI-Powered Engineer: ChatGPT
5. ChatGPT for Beginners training course
Introduction to AI (Artificial intelligence) with Python.
Introduction to Programming with Python for AI.
An introduction to programming using Python, a popular language for general-purpose programming, data science, web programming, and more..
Introduction
Functions, Variables
Conditionals
Loops,
Exceptions
Libraries
Unit Tests
File I/O
Regular Expressions
Object-Oriented Programming
Set a weekly learning goal
Setting a goal motivates you to finish the course. You can always change it later.
SOFT AI Academy is a great platform that offers interactive courses specifically tailored for aspiring AI learners. The courses range from beginner to advanced levels and are designed with hands-on exercises. Here are some of the best AI-related courses.
1. Understanding AI Course
2. AI Fundamentals skill track
3. Python Fundamentals
4. Data Manipulation with Python
5. Machine Learning Fundamentals with Python
6. Machine Learning Scientist with Python
7. Introduction to Deep Learning with PyTorch.