In today's fast-paced digital era, the demand for skills in Artificial Intelligence (AI) and Machine Learning (ML) is soaring high. These cutting-edge technologies are transforming industries, from healthcare to finance and beyond. But where do you start on your journey to mastering AI? That's where we come in!
AI, or Artificial Intelligence, is the overarching concept that aims to create machines or systems that can mimic human intelligence. The goal of AI is to make machines capable of reasoning, problem-solving, and decision-making, much like humans.
Now, let's clear up a common confusion: What's the difference between AI and Machine Learning? Machine Learning is a subset of AI. It's the part where machines learn from data and improve their performance over time without being explicitly programmed. In simple terms, ML is like teaching a computer to recognize patterns and make predictions based on data.
So, if you're ready to dive into the exciting world of AI and Machine Learning, we've got you covered. In this guide, we'll walk you through the 10 best courses to help you grasp these technologies for free, even if you're starting from scratch. Whether you're aiming to break into the tech industry, enhance your career, or simply satisfy your curiosity, these courses will be your compass on this incredible journey. Let's get started on your path to AI mastery!
1. AI For Everyone By Coursera.
In this course, you will learn:
- Gain a clear understanding of common AI terms like neural networks, machine learning, deep learning, and data science.
- Distinguish what AI can realistically achieve and its limitations.
- Learn how to Identify opportunities to implement AI solutions within your organisation.
- You will get experience for the process of developing machine learning and data science projects.
- Learn how to collaborate with an AI team and formulate an AI strategy for your company.
- You will learn how to navigate the ethical and societal aspects related to AI discussions.
While this course primarily focuses on non-technical aspects, it's also beneficial for engineers looking to grasp the business dimensions of AI.
About The Course
- Course Name: AI For Everyone
- Platform: Coursera
- Level: Beginner
- Course Duration: 10 hours (Approx)
- Taught By: Andrew Ng
- Offered By: Deep Learning AI
- Enrollment Fees: Free
- Certificate: Free
- Rating: 4.8 | 5
What You'll Learn
- What is AI?
- Building AI Projects
- Building AI In your company
- AI and Society
2. IBM: AI for Everyone: Master the Basics
Explore the world of AI with our "AI for Everyone" course! Whether you're tech-savvy or a newbie, this course breaks down AI into easy-to-understand concepts.
Discover how AI impacts our daily lives, from machine learning to neural networks. Dive into real-world applications and tackle concerns like ethics and bias. Plus, glimpse the future of AI and get career advice. No coding or tech experience needed! And to top it off, you'll even try your hand at a mini AI project. Uncover the power of AI – join us on this exciting journey.
About The Course
- Institution: IBM
- Platform: edX
- Subject: Computer Science
- Level: Introductory
- Prerequisites: None
- Course Duration: 4 Week (1-2 Hours per week)
- Language: English
- Video Transcript: English
- Associated programs:
- Professional Certificate in Foundations of AI
- Professional Certificate in Essential Technologies for Business
- Professional Certificate in Applied AI
- Associated skills: Deep Learning, Artificial Intelligence, Artificial Neural Networks, Machine Learning, Computer Science
- Enrollment Free: Free
What You'll Learn
- Understand what is AI, its applications and use cases and how it is transforming our lives
- Explain terms like Machine Learning, Deep Learning, and Neural Networks
- Describe several issues and ethical concerns surrounding AI
- Articulate advice from experts about learning and starting a career in AI
3. Intro to Artificial Intelligence by Udacity
This course will introduce you to the basics of AI. Topics include machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
Learn from the best in the industry! Our course is led by experts like Peter Norvig, the Research Director at Google and co-author of the renowned textbook "Artificial Intelligence: A Modern Approach." Sebastian Thrun, Founder and Executive Chairman of Udacity, brings his expertise in democratizing education and leading groundbreaking projects like the Self-Driving Car and Google Glass through Google X.
With their guidance, you'll gain invaluable insights into the world of AI and its limitless possibilities. Join us and embark on an educational journey curated by these visionary leaders.
About The Course
- Course Name: Intro to Artificial Intelligence
- Platform: Udacity
- Enrollment Fees: Free
- Prerequisites: No experience required
- Taught By: Peter Norvig (Research Director, Google), Sebastian Thrun (Founder and Executive Chairman, Udacity)
- Total No. Of Lesson: 31
- No. Of Topics: 22
What You'll Learn
- Basic Introduction of A.I, Probability in AI, Probabilistic Inference, Problem Solving.
- Machine Learning, Unsupervised Learning
- Representation with Logic, Planning under Uncertainty, Reinforcement Learning.
- HMMs and Filters, MDP Review
- Games, Game Theory.
- Advance Planning, Computer Vision
- Robotics
- Neural Language Processing.
- Total 8 Problem Sets For Practice.
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4. IBM AI Engineering Professional Certificate
AI is transforming industries by harnessing data for smarter decision-making. To stay competitive, organizations need skilled AI engineers proficient in cutting-edge techniques like machine learning and deep learning. This 6-course Professional Certificate empowers you to excel as an AI or ML engineer.
1. Master machine learning and deep learning fundamentals, including supervised and unsupervised learning, using Python.
2. Apply popular libraries like SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow to tackle real-world challenges in areas like computer vision, NLP, and recommender systems.
3. Gain hands-on experience scaling machine learning on big data using Apache Spark.
4. Build, train, and deploy various deep architectures, including CNNs, RNNs, and autoencoders.
5. Receive a Professional Certificate from Coursera and a digital badge from IBM, validating your AI engineering expertise.
Applied Learning:
Throughout the program, you'll create a portfolio of practical projects showcasing your proficiency with ML libraries and deep learning frameworks. This includes a Capstone Project where you'll apply your skills to solve a real-world problem and effectively communicate your project's outcomes.
About The Course
- Course: IBM AI Engineering Professional Certification
- Instructors: Romeo Kienzier, Joseph Santarcangelo, Alex Akison
- Platform: Coursera
- Offered By: IBM
- Level: Intermediate [Professional Course]
- Language: English and 21+
- Duration: 2 months at 10 hours a week
- Certificate: Available For Free
What You'll Learn
- Machine Learning with Python
- Introduction to Deep Learning & Neural Networks with Keras
- Introduction to Computer Vision and Image Processing
- Deep Neural Networks with PyTorch
- Building Deep Learning Models with TensorFlow
- AI Capstone Project with Deep Learning
5. Microsoft AI Fundamentals
If you want to kickstart your career and explore exciting AI opportunities, mastering the basics is the way to go. AI isn't just science fiction anymore; it's a game-changer in fields like healthcare, finance, and the environment.
Consider getting the Microsoft Certified: Azure AI Fundamentals certification. It proves you have the AI skills to make a difference. This certification lays the foundation for your career and shows you understand AI and Azure services.
You don't need extensive programming experience, but it's helpful. Plus, this certification can prep you for other Azure roles like Data Scientist, AI Engineer, or Developer—no prerequisites required. Start your journey into AI and open doors to endless possibilities.
About The Course
- Course Name: Microsoft Certified: Azure AI Fundamentals certification
- Platform: Microsoft Learn
- Job Role: Student, Developer, AI Engineering, Data Scientist.
- Language: English
What You'll Learn
- Microsoft Azure AI Fundamentals: Get started with artificial intelligence
- Explore visual tools for machine learning
- Explore computer vision
- Explore natural language processing
- Explore decision support
- Explore knowledge mining
6. Introduction to Artificial Intelligence
In AI, computer scientists are just a small part of the picture. Most AI professionals are project managers, product managers, directors, and executives – just like you. This course is tailored to help you understand AI's essential concepts and how it can benefit your career and daily life.
Despite AI's long history, the core ideas in machine learning and neural networks remain understandable.
Designed for project managers, product managers, directors, executives, and students entering the AI field, this course provides a high-level overview of key AI tools.
You'll explore what "intelligence" means for a system, delve into machine learning algorithms and artificial neural networks, and simplify AI, making it seem more like exciting technology rather than magic.
About The Course
- Course Name: Introduction to Artificial Intelligence
- Platform: LinkedIn Learning
- Duration: 1 Hour 34 Minutes
- Released: 13 May, 2023
- Skill Level: Beginner
- Course Certificate: Available For Free
What You'll Learn
- What is Artificial Intelligence
- The Rise of Machine Learning
- Common AI Systems
- Learn From Data
- Identify Patterns
- Machine Learning Algorithms
- Artificial Neural Networks
7. Introduction To Machine Learning
Welcome to "Introduction to Machine Learning"! This course is your gateway to the world of machine learning (ML). Here, you won't dive into implementing ML or handling data; instead, you'll grasp the fundamental ML ideas.
In just a short 20-minute course, you'll achieve three key goals.
Firstly, you'll explore the various types of machine learning, gaining a clear picture of its diverse applications.
Secondly, you'll delve into the essentials of supervised machine learning, a crucial ML branch.
Lastly, you'll discover how ML problem-solving differs from traditional approaches, giving you valuable insights into the future of problem-solving. Get ready to embark on your ML journey!
About The Course
- Course: Introduction to Machine Learning
- Platform: Google for Developer
- Duration: 20 minutes
- Format: Article, Text
- Course Fees: Available for Free
What You'll Learn
- Understand the different types of machine learning.
- Understand the key concepts of supervised machine learning.
- Learn how solving problems with ML is different from traditional approaches.
8. Intro To Machine Learning
You'll dive into the inner workings of machine learning models, learn essential data exploration techniques, and create your very first machine learning model. Discover how to validate models, tackle underfitting and overfitting, and harness the power of Random Forests.
Plus, get hands-on experience with machine learning competitions through tutorials and exercises for each topic. By the end, you'll be well-prepared for the worlds of ML explainability, intermediate ML, and even intro to deep learning.
Earn your certificate and step confidently into the realm of machine learning!
About The Course
- Course: Intro to Machine Learning
- Platform: Kaggle
- Course Duration: 3 Hours
- Builds On: Python
- Course Fees: Free
- Instructor: Dan Becker
- Preparation for: Machine Learning Explainability, Intermediate Machine Learning, Intro to Deep Learning
- Certificate: Available
What You'll Learn
- How Models Work
- Basic Data Exploration
- Your First Machine Learning Model
- Model Validation
- Underfitting and Overfitting
- Random Forests
- Machine Learning Competitions
- Including Tutorial and Exercise For each of the above topics
9. Machine Learning with Python
In this "Machine Learning with Python" course, we'll make machine learning easy to understand, using a familiar programming language. You'll discover the difference between Supervised and Unsupervised Learning and see how Statistical Modeling connects to Machine Learning. Plus, we'll show you real-life examples of how machine learning impacts society in unexpected ways!
You'll dive into various algorithms and models, like popular ones for Classification, Regression, Clustering, and Dimensional Reduction. We'll also cover essential concepts like Train/Test Split, Root Mean Squared Error, and Random Forests. Be prepared to learn a lot, even more than your machine can handle! Join us on this exciting journey into the world of machine learning with Python.
About The Course
- Course: Machine Learning with Python
- Platform: cognitive class
- Offered By: IBM
- Level: Beginner
- Course Duration: 3 Hours
- Language: English
- Instructors: Joseph Santarcangelo (Senior Data Scientist in IBM)
- Prerequisites: Python for data science
- Course Module: 5
- Enrollment Fees: Free [Login to Enroll]
What You'll Learn
- Supervised vs Unsupervised Learning
- Supervised Learning I and II
- Unsupervised Learning
- Dimensionality Reduction & Collaborative Filtering
10. Deep Learning Crash Course - Learn the Key Concepts and Terms
Are you new to deep learning and worried about courses diving into complex code too quickly? Here is the another free course for you The Deep Learning Crash Course which is available on YouTube Channel of freeCodeCamp's.
This course, designed by Jason Dsouza, is perfect for absolute beginners, even if you've never programmed before. You won't be overwhelmed with code; instead, you'll explore deep learning's fundamental concepts using easy-to-understand diagrams.
Discover topics like Neural Networks, types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning), and various Neural Network architectures. It's a gentle, code-free introduction to the exciting world of deep learning, tailored just for you.
What You'll Learn
- What is Deep Learning
- Introduction to Neural Networks
- How do Neural Networks LEARN?
- Core terminologies used in Deep Learning
- Activation Functions
- Loss Functions
- Optimizers
- Parameters vs Hyperparameters
- Epochs, Batches & Iterations
- Conclusion to Terminologies
- Introduction to Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Regularization
- Introduction to Neural Network Architectures
- Fully-Connected Feedforward Neural Nets
- Recurrent Neural Nets
- Convolutional Neural Nets
- 5 Steps to EVERY Deep Learning Model
Conclusion
In a world increasingly shaped by artificial intelligence, the quest for knowledge in AI has never been more critical. Fortunately, there's a wealth of free AI courses tailored for beginners.
These 10 courses provide a solid foundation in AI and machine learning without any fees and you will earn a free certificate after completion of the course.
From Coursera's "AI For Everyone" to IBM's "AI Engineering Professional Certificate," these courses offer diverse learning experiences. You'll grasp AI concepts, understand its real-world applications, and even delve into ethical considerations.
Udacity's "Intro to Artificial Intelligence" led by industry experts like Peter Norvig and Sebastian Thrun provides invaluable insights. Additionally, Microsoft's "Azure AI Fundamentals" opens doors to exciting opportunities.
Whether you're an absolute beginner or a curious mind, these courses offer the keys to unlock the world of AI. Start your journey today, equip yourself with AI knowledge, and embrace the future with confidence. The best part? It won't cost you a penny!