Top 10 Free AI Training Courses from LinkedIn and Microsoft
Top 10 Free AI Training Courses from LinkedIn and Microsoft
Introduction
Artificial intelligence (AI) is transforming businesses and our daily lives. As AI becomes more prevalent, there is a growing need for people with AI skills and knowledge. Fortunately, there are now many free AI courses available online to help you get started with learning about AI.
Microsoft and LinkedIn are two of the top providers of free online AI courses. They offer beginner-level courses to teach the fundamentals as well as more advanced courses on topics like machine learning and neural networks. Their courses are taught by AI experts and require no specialized knowledge to get started.
In this article, we provide an overview of the top 10 free AI courses from Microsoft and LinkedIn. For each course, we provide a brief description, key topics covered, who the course is best suited for, and the time commitment. Whether you’re new to AI or looking to expand your skills, these free courses offer an excellent way to build your AI knowledge.
Microsoft AI Courses:
1. AI For Beginners
Offered by: Microsoft
Duration: 2 hours
Description: This introductory course provides an overview of AI concepts, terminology, and applications. It’s designed for absolute beginners with no prior knowledge of AI.
Key topics:
– Defining artificial intelligence (AI)
– AI vs. machine learning vs. deep learning
– Common AI applications like computer vision, NLP, robotics
– AI ethics and bias
Best for: Those new to AI who want a high-level overview of what it is and how it’s used.
Get Access to AI for beginners here
2. Introduction to Machine Learning
Offered by: Microsoft
Duration: 8 hours
Description: This course offers an introduction to machine learning, one of the key capabilities of AI. It covers machine learning basics, terminology, algorithms, and applications. Some coding is required.
Key topics:
– Supervised, unsupervised, and reinforcement learning
– Training models, overfitting, and underfitting
– Regression, classification, and clustering algorithms
– Libraries like Scikit-learn for implementing machine learning
Best for: Beginners with some Python coding experience who want an introduction to machine learning concepts and basic implementation.
3. Natural Language Processing (NLP) Fundamentals
Offered by: Microsoft
Duration: 3 hours
Description: This course covers the basics of NLP, which enables AI systems to process, analyze, and generate human language. It provides an overview of key NLP applications and methods.
Key topics:
– Text processing, tokenization, and stemming
– NLP applications like sentiment analysis, chatbots
– Bag of words, TF-IDF, and word embeddings
– Libraries like NLTK and SpaCy for NLP
Best for: Those new to NLP looking for an introductory overview. Some Python experience is helpful.
4. Neural Networks Fundamentals
Offered by: Microsoft
Duration: 3 hours
Description: This course explains the fundamentals of neural networks, which are key to deep learning algorithms. It covers neural network architecture, activation functions, forward propagation, and backpropagation.
Key topics:
– Neural networks vs. traditional programming
– Neural network components and topology
– Forward and backpropagation passes
– Gradient descent optimization
– Common activation functions
Best for: Beginners who want to understand the basics of how neural networks work behind the scenes in deep learning. Assumes basic knowledge of Python.
5. Microsoft Azure AI Fundamentals
Offered by: Microsoft
Duration: 2 hours
Description: This course provides an introduction to AI services on Microsoft Azure. It covers pre-built APIs for vision, speech, language, knowledge, and machine learning.
Key topics:
– Azure Cognitive Services for vision, speech, language, etc.
– Azure Bot Service for building intelligent chatbots
– Azure Machine Learning for training, deploying, and managing models
– Responsible AI principles and practices
Best for: Those interested in applied AI development with Microsoft Azure. Some general programming experience is useful.
LinkedIn AI Courses
6. Artificial Intelligence Foundations: Thinking Machines
Offered by: LinkedIn Learning
Duration: 2 hours
Description: This LinkedIn Learning course gives a non-technical overview of AI concepts, applications, and implications. It’s designed for learners without a tech background.
Key topics:
– History of AI
– AI vs. machine learning vs. deep learning
– AI applications in vision, speech, robotics, and more
– AI risks and ethical concerns
Best for: Beginners seeking an understanding of AI concepts and applications without coding.
Search for the course on LinkedIn here
7. Artificial Intelligence Foundations: Learning Agents
Offered by: LinkedIn Learning
Duration: 1 hour
Description: The second installment in LinkedIn Learning’s AI Foundations series, this course covers various machine learning algorithms and methods.
Key topics:
– Supervised, unsupervised, semi-supervised, and reinforcement learning
– Linear and logistic regression
– Decision trees, neural networks, and support vector machines
– Clustering and dimension reduction techniques
Best for: Beginners looking to understand key machine learning algorithms and how they work.
8. Practical Deep Learning in PyTorch
Offered by: LinkedIn Learning
Duration: 5 hours
Description: This hands-on course teaches the fundamentals of deep learning by implementing neural networks in PyTorch. It covers data preparation, network architecture, loss functions, and more.
Key topics:
– Deep neural networks architecture
– Stochastic gradient descent
– Building CNNs, RNNs, and GANs in PyTorch
– Transfer learning
– Debugging and optimizing neural networks
Best for: Beginner to intermediate learners who want hands-on deep learning implementation experience with PyTorch. Requires Python and math skills.
9. Natural Language Processing with Deep Learning in PyTorch
Offered by: LinkedIn Learning
Duration: 3.5 hours
Description: This course focuses on NLP techniques using deep learning and PyTorch. It teaches how to implement models like RNNs, LSTMs, and Transformers for NLP tasks.
Key topics:
– Word embeddings and tokenization
– Sequence models like RNNs and LSTMs
– Implementing Transformer networks
– Sentiment analysis, text generation, and translation
– Pretrained models like BERT and GPT-2
Best for: Intermediate learners familiar with Python and deep learning basics who want to apply deep learning specifically to NLP.
10. Generative Adversarial Networks (GANs) for Image Generation
Offered by: LinkedIn Learning
Duration: 2 hours
Description: This course covers generative adversarial networks (GANs) — an advanced deep-learning technique for generating synthetic data. It teaches how to implement and train GANs.
Key topics:
– Understanding GAN architecture
– Training and stabilizing GANs
– Improving GAN output
– Conditional GANs
– Applications for image generation, image-to-image translation, and more
Best for: Intermediate learners already familiar with convolutional neural networks and deep learning basics. Requires proficiency in Python and PyTorch.
Wrapping UP
This covers our overview of the top 10 free AI courses from Microsoft and LinkedIn. Both providers offer a range of courses for learners at different levels, from AI and machine learning fundamentals to more advanced techniques and applications.
Their hands-on courses in PyTorch allow you to get practical experience implementing models like CNNs, RNNs, and GANs. And their intro courses provide a solid base of AI knowledge even for total beginners.
These free courses are a great way to start building AI skills and experience. They can prepare you for more advanced study or help boost your career opportunities in this high-demand field. Whether you want to learn the basics or expand your applied AI skills, they are a valuable free resource.