Bonus Material: Free AI Skill-Mastery Prompts
AI isn’t the future anymore.
It’s here, changing industries from healthcare to marketing and to education and even the way we work.
Guess what?
Some of the world’s leading companies and universities, including NVIDIA, Google, META, MIT and IBM, are offering free AI courses online, giving you direct access to expert knowledge without spending a dime.
This isn’t just basic stuff.
We’ve pulled together 50 free AI courses that cover everything from deep learning to AI in marketing and data science and analytics.
Download My Free AI Skill-Mastery Prompts
Also check: How to Make Money With AI in 2024: (20+ Proven Ways)
Beginner Level: Best Free AI Courses
1. Building A Brain in 10 Minutes (NVIDIA)
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- Duration: 10 minutes
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- Price: Free
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- Subject: Deep Learning
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- Link: Course Detail | NVIDIA
- Link: Course Detail | NVIDIA
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- Why Take This Course: This course offers a quick, hands-on introduction to deep learning in just 10 minutes, making it ideal for beginners who want to understand the basics of neural networks.
2. Generative AI Explained (NVIDIA)
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- Duration: 2 hours
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- Price: Free
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- Subject: Generative AI/LLM
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- Link: Course Detail | NVIDIA
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- Why Take This Course: This is a beginner-friendly introduction to generative AI and large language models (LLM), perfect for those looking to explore the foundational concepts of AI technology.
3. Augment your LLM Using Retrieval Augmented Generation (NVIDIA)
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- Duration: 1 hour
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- Price: Free
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- Subject: Generative AI/LLM
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- Link: Course Detail | NVIDIA
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- Why Take This Course: This course delves into how to enhance large language models using Retrieval Augmented Generation (RAG), offering practical insights into improving AI models’ accuracy.
4. Introduction to AI in the Data Center (Coursera)
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- Duration: 5 hours
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- Price: Free
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- Subject: Data Engineering
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- Why Take This Course: Learn about AI infrastructure and data engineering in this comprehensive course. It’s perfect for beginners interested in how AI powers data centers and large-scale systems.
5. Accelerate Data Science Workflows with Zero Code Changes (NVIDIA)
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- Duration: 1 hour
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- Price: Free
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- Subject: Data Science
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- Link: Course Detail | NVIDIA
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- Why Take This Course: This course teaches how to optimize data science workflows without writing new code. It’s an excellent starting point for beginners looking to streamline data analysis processes.
6. An Even Easier Introduction to CUDA (NVIDIA)
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- Duration: 1 hour
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- Price: Free
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- Subject: Accelerated Computing
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- Link: Course Detail | NVIDIA
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- Why Take This Course: Explore the basics of CUDA, NVIDIA’s parallel computing architecture. This course is a great fit for anyone new to accelerated computing who wants to understand how GPUs drive AI applications.
7. Introduction to Networking (Coursera/NVIDIA)
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- Duration: 1 hour
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- Price: Free
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- Subject: Computer Networking
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- Why Take This Course: Learn the fundamentals of computer networking, offering a solid foundation for understanding how data flows across networks and the internet, a key aspect of AI systems.
8. Introduction to Physics-informed Machine Learning with Modulus (NVIDIA)
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- Duration: 4 hours
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- Price: Free
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- Subject: Deep Learning
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- Link: Course Detail | NVIDIA
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- Why Take This Course: This course focuses on integrating deep learning with physics-based simulations, a unique area of AI that is gaining attention in scientific computing.
9. AI 101 (MIT OCW)
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- Duration: Not specified
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- Price: Free
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- Subject: Artificial Intelligence basics
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- Why Take This Course: MIT’s AI 101 provides a foundational understanding of artificial intelligence concepts, making it an ideal starting point for anyone new to the field.
10. Introduction to Computational Thinking and Data Science (edX/MIT)
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- Subject: Computational Thinking and Data Science
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- Language: Python
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- Why Take This Course: This course teaches Python programming and computational thinking for data science. It’s perfect for beginners interested in building a strong foundation in data analysis.
11. Elements of AI (University of Helsinki)
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- Duration: Not specified
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- Price: Free
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- Subject: AI basics (no maths required)
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- Why Take This Course: One of the most popular AI courses, Elements of AI offers a beginner-friendly introduction to artificial intelligence without the need for advanced math or programming skills.
12. AI for Everyone: Master the Basics (IBM/edX)
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- Subject: AI fundamentals and career advice
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- Why Take This Course: This course from IBM provides an accessible introduction to AI concepts, helping beginners understand how AI can enhance their career prospects.
13. Introduction to Generative AI (Google/Coursera)
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- Duration: 1 hour
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- Subject: Generative AI basics
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- Why Take This Course: This quick course by Google offers a clear overview of generative AI, making it ideal for beginners who want to explore this emerging technology.
14. Introduction to Large Language Models (Google/Coursera)
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- Duration: 1 hour
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- Subject: Large Language Models
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- Why Take This Course: Learn the fundamentals of large language models, the technology behind modern AI applications like GPT-3, in this accessible course for beginners.
15. Introduction to Image Generation (Google/Coursera)
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- Duration: 1 hour
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- Subject: Image Generation models
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- Why Take This Course: Discover how AI generates realistic images in this course, ideal for beginners interested in creative applications of AI technology.
16. Google AI Essentials (Coursera)
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- Duration: 9 hours
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- Subject: Essential AI skills for real-world application
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- Why Take This Course: A comprehensive introduction to the key concepts in AI, this course offers practical examples and skills for applying AI in real-world scenarios.
17. Generative AI Essentials: Overview and Impacts (University of Michigan)
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- Subject: AI basics, ethics, and regulations
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- Why Take This Course: This course offers a balanced overview of generative AI and explores its ethical and regulatory considerations, making it ideal for those interested in understanding the broader impact of AI.
18. Introduction to AI for Business (Udemy)
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- Subject: AI algorithms in enterprise
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- Why Take This Course: This course covers how AI is transforming business operations, from automating tasks to making data-driven decisions, perfect for professionals in the business world.
19. AI for Everyday Life (Coursera)
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- Duration: Approximately 10 hours
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- Subject: Practical AI applications in daily life
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- Why Take This Course: Explore how AI is embedded in the tools and services we use daily. This course offers an approachable way to understand the practical applications of AI in everyday life.
Intermediate Level: Best Free AI Courses for Learners with Experience
1. Building RAG Agents with LLMs (NVIDIA)
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- Duration: 8 hours
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- Price: Free
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- Subject: Generative AI/LLM
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- Link: Course Detail | NVIDIA
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- Why Take This Course: Learn to build Retrieval Augmented Generation (RAG) agents using large language models (LLMs). This intermediate course is ideal for those with some AI background looking to enhance their knowledge of advanced generative AI techniques.
2. Artificial Intelligence (MIT OCW)
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- Duration: Not specified
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- Price: Free
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- Subject: Fundamental AI problems and techniques
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- Why Take This Course: This course provides an in-depth exploration of AI’s core problems and techniques, making it a must for intermediate learners interested in advancing their understanding of AI algorithms.
3. Introduction to Algorithms (MIT OCW)
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- Duration: Not specified
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- Price: Free
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- Subject: Efficient algorithms and data structures
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- Why Take This Course: Master efficient algorithms and data structures, crucial skills for anyone advancing in the AI field. This course offers a strong foundation for tackling more complex AI challenges.
4. Introduction to Machine Learning (MIT Open Learning Library)
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- Duration: Not specified
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- Price: Free
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- Subject: Machine Learning fundamentals
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- Why Take This Course: Ideal for learners with a basic understanding of AI, this course dives into machine learning fundamentals, covering key concepts like supervised learning, unsupervised learning, and neural networks.
5. Machine Learning with Python: From Linear Models to Deep Learning (edX/MIT)
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- Duration: Not specified
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- Price: Free
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- Subject: Comprehensive machine learning
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- Language: Python
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- Why Take This Course: This course covers everything from linear models to deep learning using Python. It’s a great next step for intermediate learners familiar with machine learning and programming in Python.
6. CS50’s Introduction to Artificial Intelligence with Python (HarvardX/edX)
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- Duration: Not specified
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- Price: Free
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- Subject: Core AI concepts and Python implementation
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- Why Take This Course: This Harvard course takes you through core AI concepts like search algorithms and optimization, with hands-on Python coding. It’s designed for learners with some prior experience in programming and AI.
7. Artificial Intelligence Projects (Great Learning)
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- Duration: Not specified
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- Price: Free
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- Subject: Hands-on AI projects
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- Why Take This Course: If you’re looking for a practical way to apply what you’ve learned, this course offers real-world AI projects to work on, perfect for intermediate learners wanting hands-on experience.
8. Fine Tuning Large Language Models (DeepLearning.AI)
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- Duration: Not specified
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- Price: Free
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- Subject: LLM fine-tuning techniques
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- Why Take This Course: Dive deep into fine-tuning large language models with this course. It’s a great choice for learners with an understanding of generative AI who want to specialize in improving the performance of LLMs.
9. Generative AI with Large Language Models (Coursera)
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- Duration: Not specified
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- Price: Free
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- Subject: Fundamentals of generative AI and LLMs
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- Why Take This Course: This course provides a solid foundation in generative AI using large language models. It’s perfect for intermediate learners who want to understand how LLMs like GPT work and how to build with them.
Advanced Level: Best Free Advanced AI Courses Online
1. Databases: Advanced Topics in SQL (Stanford Online)
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- Duration: Not specified
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- Price: Free
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- Subject: Advanced SQL concepts
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- Why Take This Course: This advanced course from Stanford covers complex SQL concepts, perfect for AI professionals needing a strong database background to work with large datasets and AI systems.
2. Mining Massive Data Sets (Stanford Online)
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- Duration: Not specified
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- Price: Free
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- Subject: Data mining and machine learning for large datasets
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- Why Take This Course: Learn about data mining techniques and machine learning algorithms used for processing massive datasets. This advanced course is perfect for learners dealing with large-scale AI and data science projects.
3. Machine Vision (MIT OCW)
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- Duration: Not specified
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- Price: Free
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- Subject: Image processing and computer vision techniques
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- Why Take This Course: Dive deep into the world of computer vision with this advanced course, which covers the techniques and algorithms used to extract information from visual data—ideal for anyone specializing in AI-powered image recognition systems.
Great! Now, let’s move on to the Specialized Courses section.
Specialized Courses: Top Free AI Courses in Specific Fields
1. ChatGPT Prompt Engineering for Developers (DeepLearning.AI)
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- Duration: Not specified
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- Price: Free
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- Subject: Prompt engineering for app development
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- Why Take This Course: Learn how to leverage ChatGPT for building AI-powered applications with optimized prompts. This course is perfect for developers looking to integrate generative AI tools into their apps.
2. ChatGPT for Excel (Great Learning)
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- Duration: Not specified
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- Price: Free
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- Subject: AI-enhanced Excel skills for finance professionals
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- Why Take This Course: This course is ideal for finance professionals and analysts who want to improve their data-handling skills using ChatGPT to automate tasks within Excel.
3. ChatGPT for HR (Great Learning)
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- Duration: Not specified
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- Price: Free
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- Subject: AI applications in human resources
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- Why Take This Course: Learn how ChatGPT is revolutionizing HR workflows, from talent acquisition to employee engagement, making this course ideal for HR professionals looking to adopt AI technologies.
4. ChatGPT for Digital Marketing (Great Learning)
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- Duration: Not specified
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- Price: Free
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- Subject: AI in marketing strategies and campaigns
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- Why Take This Course: Explore how ChatGPT can transform digital marketing strategies by automating content creation, customer engagement, and campaign management.
5. ChatGPT, Midjourney, Firefly, Bard, DALL-E, AI Crash Course (Udemy)
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- Duration: Not specified
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- Price: Free
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- Subject: Comprehensive AI tools for content and art creation
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- Link: AI Crash Course | Udemy
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- Why Take This Course: This crash course covers a range of AI tools, including ChatGPT, DALL-E, and Midjourney, making it ideal for creative professionals looking to explore AI’s role in content and art generation.
6. The Economics of AI (Coursera)
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- Duration: Approximately 13 hours
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- Price: Free
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- Subject: Economic implications of AI
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- Why Take This Course: Gain insights into how AI is impacting global economics, and learn about its potential to reshape industries. This course is perfect for those interested in the macroeconomic aspects of AI.
7. Building Trustworthy Generative AI Applications (Coursera)
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- Duration: Approximately 7 hours
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- Price: Free
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- Subject: Ethical AI application development
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- Why Take This Course: Explore the ethics and trust issues surrounding generative AI systems, making this course a must for developers working on AI-powered applications that prioritize ethical considerations.
8. GPT-Powered Applications with Vision (Coursera)
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- Duration: Approximately 8 hours
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- Price: Free
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- Subject: Combining language and vision in AI applications
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- Why Take This Course: Learn how to combine GPT models with visual data for next-gen AI applications. This course is perfect for AI professionals looking to create multimodal systems that integrate language and vision.
9. Artificial Creativity (Coursera)
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- Duration: Approximately 10 hours
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- Price: Free
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- Subject: AI’s role in creative processes
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- Why Take This Course: This course focuses on AI’s application in creative industries, exploring how algorithms like DALL-E and Midjourney can assist with design, music, and content creation.
10. AI Concepts and Strategy (Coursera)
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- Duration: Approximately 11 hours
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- Price: Free
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- Subject: AI implementation in business contexts
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- Why Take This Course: Designed for business professionals, this course covers AI strategy, implementation, and decision-making processes, making it an essential resource for those looking to integrate AI into their organizations.
11. Application of AI, InsurTech, and Real Estate Technology (Coursera)
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- Duration: Approximately 13 hours
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- Price: Free
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- Subject: AI applications in insurance and real estate
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- Why Take This Course: Explore how AI is being applied in specialized sectors like insurance and real estate, providing valuable insights for professionals in these fields looking to embrace AI-driven transformation.
12. Artificial Intelligence in Marketing (Coursera)
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- Duration: Approximately 10 hours
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- Price: Free
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- Subject: AI in digital marketing transformation
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- Why Take This Course: Learn how AI is reshaping digital marketing strategies, from automation to personalized customer experiences, in this course designed for marketers keen to leverage AI for growth.
Data Science and Analytics Courses: Best Free AI Courses in Data Science
1. Introduction to Data Analytics (META/Coursera)
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- Duration: 14 hours
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- Price: Free
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- Subject: Basic analytics tasks
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- Why Take This Course: This course from META offers a comprehensive introduction to data analytics, covering basic tasks and concepts essential for beginners looking to dive into the world of data science.
2. Marketing Analytics Foundation (META/Coursera)
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- Duration: 11 hours
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- Price: Free
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- Subject: Data analysis in digital marketing
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- Why Take This Course: Perfect for marketers, this course focuses on how data analytics can optimize marketing campaigns, from tracking customer behavior to personalizing outreach strategies.
3. Data Analytics Methods for Marketing (META/Coursera)
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- Duration: 12 hours
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- Price: Free
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- Subject: Analytics methods for marketers
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- Why Take This Course: This course provides actionable insights into the data analytics methods used in marketing, helping learners understand how to harness data for better marketing performance.
4. Ask Questions to Make Data-Driven Decisions (Google/Coursera)
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- Duration: 21 hours
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- Price: Free
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- Subject: Data-driven decision making
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- Why Take This Course: Learn how to ask the right questions and make informed decisions based on data. This course is ideal for beginners looking to enhance their ability to interpret data in business contexts.
5. Analyze Data to Answer Questions (Google/Coursera)
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- Duration: 32 hours
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- Price: Free
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- Subject: Data analysis fundamentals
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- Why Take This Course: This course covers the basics of data analysis, from collecting and cleaning data to generating insights. It’s a perfect fit for those who want to strengthen their data science skills.
6. Share Data Through the Art of Visualization (Google/Coursera)
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- Duration: 25 hours
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- Price: Free
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- Subject: Data visualization techniques
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- Why Take This Course: Learn how to create compelling visualizations that make data easy to understand. This course is great for professionals who want to communicate data insights more effectively.
7. Preparing Data for Analysis with Microsoft Excel (Microsoft/Coursera)
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- Duration: 18 hours
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- Price: Free
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- Subject: Excel for business data analysis
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- Why Take This Course: This course helps learners master Microsoft Excel for data preparation and analysis, a crucial skill for anyone working in business analytics or data-driven roles.
8. Harnessing the Power of Data with Power BI (Microsoft/Coursera)
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- Duration: 16 hours
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- Price: Free
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- Subject: Data analysis using Microsoft Power BI
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- Why Take This Course: Learn how to use Power BI for data analytics and visualization in this course, which is perfect for learners looking to enhance their data analysis capabilities with Microsoft’s powerful BI tools.
9. Extract, Transform, and Load Data in Power BI (Microsoft/Coursera)
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- Duration: 20 hours
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- Price: Free
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- Subject: ETL processes in Power BI
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- Why Take This Course: This course provides detailed insights into the ETL (Extract, Transform, Load) process using Power BI, an essential skill for anyone working with large datasets in business analytics.
10. Data Science: Machine Learning (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Core machine learning concepts
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- Why Take This Course: This course offers a deep dive into machine learning, covering the essential algorithms and techniques. It’s ideal for intermediate learners looking to expand their knowledge in AI and data science.
11. Data Science: Probability (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Probability theory for data science
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- Why Take This Course: Learn probability theory in the context of data science, a critical foundation for understanding how AI models work with uncertainty and randomness in data.
12. Data Science: Linear Regression (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Linear regression for prediction and inference
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- Why Take This Course: Master linear regression techniques, a cornerstone of predictive analytics, in this course designed for data science learners seeking to improve their predictive modeling skills.
13. Data Science: R Basics (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: R programming fundamentals
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- Why Take This Course: Learn the basics of R programming, one of the most popular languages used in data science, in this beginner-friendly course from Harvard.
14. Data Science: Visualization (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Principles of data visualization
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- Why Take This Course: This course covers the essential principles of data visualization, helping learners understand how to effectively present data-driven insights.
15. Introduction to Data Science with Python (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Python for data science
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- Why Take This Course: Learn Python programming for data science in this beginner-friendly course. Ideal for those looking to start their journey into data science with one of the most widely used programming languages.
16. Data Science: Capstone (Harvard)
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- Duration: Not specified
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- Price: Free
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- Subject: Real-world data science project
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- Why Take This Course: This capstone course allows learners to apply their data science knowledge to a real-world project, helping them solidify their skills and showcase their abilities to potential employers.
17. R Programming Fundamentals (Stanford Online)
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- Duration: Not specified
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- Price: Free
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- Subject: R for statistical computing and data analysis
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- Why Take This Course: This course is perfect for learners interested in statistical computing and data analysis using R, offering a strong foundation for anyone working in AI or data science.
18. Statistical Learning with R (Stanford Online)
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- Duration: Not specified
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- Price: Free
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- Subject: Supervised learning using R
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- Why Take This Course: Learn the principles of supervised learning using R, with a focus on real-world applications. This course is perfect for advanced learners interested in machine learning techniques for AI and data science.
Frequently Asked Questions (FAQ)
1. Can I learn AI for free online?
Yes, you can absolutely learn AI for free online. Many leading companies like NVIDIA, Google, and IBM offer free AI courses online, covering everything from beginner topics to advanced AI applications.
2. Is Google’s AI course free?
Yes, Google offers a range of free AI courses online through platforms like Coursera. These include topics such as Generative AI, Machine Learning, and AI for beginners.
3. Which is the best AI course for beginners?
Some of the best AI courses for beginners include:
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- Elements of AI (University of Helsinki)
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- AI for Everyone (IBM)
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- Introduction to Generative AI (Google/Coursera) These courses provide a solid foundation for anyone starting their AI journey.
4. Can I self-teach AI?
Yes, many learners successfully self-teach AI through a combination of free AI courses online, tutorials, and hands-on practice with projects. Platforms like Coursera, edX, and YouTube provide excellent resources for self-paced learning.
5. How to start learning AI for beginners?
Start by taking beginner-friendly courses like:
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- AI for Everyone (IBM)
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- Introduction to AI for Business (Udemy)
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- Google AI Essentials (Coursera) These courses explain core AI concepts and help you get started without requiring prior knowledge.
6. Is AI certification worth it?
An AI certification can be very valuable, especially if you want to pursue a career in AI, data science, or machine learning. Certifications from platforms like Coursera and edX, especially those in collaboration with companies like Google or universities like Harvard, are highly regarded.
7. Does AI require coding?
Yes, in most cases, learning AI requires some level of coding knowledge. Popular programming languages for AI include Python, R, and Java. However, some courses, like AI for Everyone and Elements of AI, focus on AI concepts without requiring coding.
8. Can I learn AI without coding?
While many AI courses involve coding, there are several beginner-friendly courses that don’t require any coding knowledge, such as:
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- AI for Everyone (IBM)
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- Elements of AI (University of Helsinki) These courses provide a strong understanding of AI principles without diving into programming.
9. What coding language is used for AI?
Python is the most widely used programming language for AI due to its simplicity and extensive libraries like TensorFlow and PyTorch. Other languages used in AI include R, Java, and C++.
10. Where can I train AI for free?
You can train AI for free through platforms like Google’s TensorFlow, Kaggle, and NVIDIA‘s learning portal. These platforms offer tools, datasets, and free AI courses online to help you build and train your own AI models.
11. What is the best AI course for non-technical people?
For non-technical learners, courses like AI for Everyone (IBM) and Elements of AI (University of Helsinki) are excellent choices. These courses focus on the impact and applications of AI without requiring technical knowledge.
12. Can I learn AI on my own?
Yes, many people learn AI independently using free AI courses online, tutorials, and community resources. With platforms like Coursera, edX, and YouTube, you can structure your own learning path at your own pace.
13. Does AI require math?
Yes, AI involves math, especially in areas like linear algebra, calculus, and statistics. However, many beginner courses introduce AI concepts without diving too deeply into the math, making it accessible for learners from various backgrounds.
14. How to learn AI from scratch?
To learn AI from scratch, start with beginner courses such as:
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- AI for Everyone (IBM)
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- Introduction to Machine Learning (MIT Open Learning)
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- Elements of AI (University of Helsinki) These courses provide foundational knowledge, and you can gradually move on to more advanced topics.
15. What software is used for AI?
Popular software tools for AI include:
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- TensorFlow (Google)
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- PyTorch (Facebook)
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- Scikit-learn
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- Power BI for data analysis
- NVIDIA’s CUDA for accelerated computing
Now that you’ve found the best free AI courses, learn how to turn those skills into income with our detailed guide on how to make money with ai realistically in 2024.