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Artificial intelligence (AI) is a branch of computer science that enables machines to mimic human-like intelligence to perform various activities. Unlike other technologies, AI innovations integrate into our everyday lives.
Today, AI significantly impacts people and processes within commercial setups and standard day-to-day solutions. As a result, AI is practically everywhere, be it smart lighting solutions for homes, virtual assistants, or to add intelligent solutions to transform businesses and science and innovations.
What is the Best Way to Learn AI?
Recent trends highlight the continuous growth of the AI industry in the past few years, with AI software revenue forecasts of a staggering $62.5 billion in 2022, with an increase of 21.3% from 2021.
Notably, AI has moved beyond the hype with proven capabilities with fascinating technologies like Google Brain and the wide adoption of AI innovations across industries. While industry leaders pave the way for AI solutions to drive businesses and gain competitive advantages, researchers implement AI to solve various complex problems.
Likewise, almost every industry is on the lookout for new talent and tech veterans in the AI space; thus, it is evident that AI industry prospects are promising, with ample opportunities in the job market.
Nowadays, every online platform claims to offer the best artificial intelligence courses. While artificial intelligence courses are plenty, selecting the right specialization is challenging—with several online platforms offering different curricula and course material requiring different levels of experience and technical know-how.
The best AI course will teach you the right balance of theoretical and technical skills for AI programming. To help you pick, we compiled the top 15 online courses taught by industry experts. This list includes courses with a comprehensive curriculum and industry-recognized certificates to help you stand out in the AI field.
Disclosure: Some of the links in this article may be affiliate links, which can provide compensation to us at no cost to you if you decide to purchase a paid plan. This site is not intended to provide financial advice and is for entertainment only. You can read the affiliate disclosure in our privacy policy.
What Are the Best AI Courses Online?
Here are our picks for the best artificial intelligence courses to learn AI this year.
1. Machine Learning Specialization – Coursera
This specialization is among the best online AI courses offered by DeepLearning.AI and Stanford on Coursera. Taught by the AI visionary Andrew Ng, this beginner-friendly course focuses on introducing the fundamental AI concepts and building the learners’ practical machine learning (ML) skills.
You will learn to build and train ML models and implement them for problems such as prediction, binary classification, etc. As a beginner-level course, it doesn’t require a vast experience with programming languages; however, some prerequisites exist, such as basic coding experience and an understanding of linear algebra is essential.
This machine learning course helps students master supervised and unsupervised learning techniques and apply best practices for ML development. Likewise, you will become familiar with training neural networks using TensorFlow for various multi-class classification problems.
Additionally, you will delve into concepts of decision trees, recommender systems, and content-based deep learning methods and work on deep reinforcement learning models.
By the end of this AI course, you will master key concepts of AI and machine learning, including practical skills to create robust AI solutions for challenging real-world problems.
If you aspire to enter the world of AI, we highly recommend this specialization to begin your journey. However, like most AI courses, you must complete all the hands-on projects under each module to achieve your certification.
Key Highlights
- Arguably the best artificial intelligence course, taught by the pioneers of the AI industry
- Learn artificial intelligence and gain a comprehensive overview of machine learning algorithms such as artificial neural networks
- Learning programming with Python and popular ML libraries such as NumPy and scikit-learn to build machine learning models
- Building and training neural networks using TensorFlow
- Applying best practices in machine learning development such that the models generalize to data and tasks to solve real problems
- In-depth understanding of decision trees, random forests, and boosted trees
- Unsupervised learning techniques such as clustering and anomaly detection
- Building recommender systems and implementing deep reinforcement learning models for industry problems
Course Modules
There are three modules in the specialization which are:
- Supervised machine learning: regression and classification
- Advanced learning algorithms
- Unsupervised learning, recommenders, and reinforcement learning
Course Details
Instructors: Andrew Ng, Aarti Bagul, Eddy Shyu, and Geoff Ladwig
Duration: 3 months approx.
Level: Beginner
User Rating: 4.9/5
Price: Free Enrollment (Fees applicable to obtain certificate)
2. Deep Learning Specialization – Coursera
This specialization aims to develop deep learning skills for intermediate learners. As it comes highly rated, this is one of the best among several AI courses to learn deep learning under the guidance of Andrew Ng.
As the program focuses on intermediate learners, there are prerequisites for the course, such as basic programming knowledge, understanding of loops, if/else statements, data structures, and machine learning.
During the course, you will learn to build and train deep neural networks, identify architecture parameters and implement vectorized neural networks.
Similarly, hands-on sessions allow you to cover various concepts on convolutional neural networks (CNNs) and their application for detection and recognition tasks. At the same time, you will analyze variance for deep learning applications and implement the standard technique and optimization algorithms.
The final modules cover advanced concepts of building recurrent neural networks (RNNs) for natural language processing (NLP) problems and word embeddings and learning to use HuggingFace tokenizers to perform NER and question-answering using NLP models.
Key Highlights
- Learn to build and train deep neural networks and apply them to various applications
- Understand the best practices and develop test sets and analyze bias and variance when building deep learning applications
- Explore different strategies to reduce errors in complex machine-learning settings
- Learn to apply end-to-end transfer learning to solve real-world problems
- Implement CNN for visual detection and use image and video analysis algorithms
- Understand various variants of RNN and modeling for NLP problems
Course Modules
- Neural networks and deep learning
- Improving deep neural networks: hyperparameter tuning, regularization, and optimization
- Structuring machine learning projects
- CNNs for various applications such as autonomous driving, face recognition, radiology image, and more
- Sequence models for speech recognition, music synthesis, chatbots, and machine translation
Course Details
Instructors: Andrew Ng, Kian Katanforoosh, and Younes Bensouda Mourri
Duration: 5 months
Level: Intermediate
User Rating: 4.9/5
Price: Free Enrollment (Fees applicable to obtain certificate)
3. IBM Applied AI Professional Certificate – Coursera
IBM is a tech giant known to develop some of the best courses to learn artificial intelligence. IBM offers this comprehensive artificial intelligence course on Coursera, which doubles as a professional certificate program. You can kickstart your career with this beginner-friendly course that covers all the technical aspects of AI concepts taught by industry professionals.
Students will cover the definition of AI and its applications and indulge in various use cases to gain clarity over terms like machine learning, deep learning, and neural networks. You will become familiar with multiple tools of AI to perform various tasks associated with image classification, image processing, natural language processing, IBM Watson AI, OpenCV, and APIs.
Even if you lack programming skills, this course is suitable for beginners as there is a wide range of hands-on learning projects, with experts teaching Python programming to help design, build and deploy AI applications.
An exciting aspect of this course is the provision for applying pre-built AI to your products and solutions. Often beginners in the field tend to create complex AI algorithms, a problem that the course will address.
You will learn to use the IBM Watson AI service to create intelligent solutions with minimal coding requirements. You will also work on projects to build your own AI chatbot, work with Python to solve data science problems, build custom image classifiers, and create and deploy a computer vision web application to the cloud.
At the end of the course, learners are also offered valuable digital badges from IBM that demonstrate AI programming proficiency in building intelligent solutions.
Key Highlights
- In-depth understanding of AI concepts and applications using use cases
- Comprehensive understanding of various ethical issues surrounding AI and bias
- Artificial intelligence with Python
- Familiarity with IBM Watson AI services with real-life client examples and implementation to build intelligent applications
- Leveraging IBM Watson for creating and deploying NLP solutions such as chatbots/ virtual assistants
- Working on industry-level projects and learning to build, run tests and package the application for distribution
- Creating AI applications using Watson APIs
Course Modules
- Introduction to artificial intelligence
- Getting started with AI using IBM Watson
- Building AI-powered chatbots without programming
- Python for data science, AI, and development
- Python project for AI and application development
- Creating AI applications with Watson APIs
Course Details
Instructors: Rav Ahuja, Antonio Cangiano, Joesph Santarcangelo, Ramesh Sannareddy, and Tanmay Bakshi
Duration: 6 months
Level: Beginner
User Rating: 4.6/5
Price: Free Enrollment (Fees applicable to obtain certificate)
4. AI for Everyone – Coursera
AI is the latest buzzword, and engineers play a pivotal role in helping organizations leverage AI to gain a competitive edge over their competitors. However, if organizations want to maximize AI’s impact, the non-technical workforce should have some fundamental knowledge of AI.
This is where this artificial intelligence online course is most effective. There are various artificial intelligence courses, but very few begin from scratch. In this course, you will understand common terminologies such as neural networks, machine learning and deep learning, and AI implementations for data science.
This course targets non-technical audiences, so there are no prerequisites. Next, the critical strategies to implement AI in the organization for real-world applications are covered comprehensively, and the ethical and societal factors are also discussed in detail.
Finally, you will explore the workflow of machine learning projects, understand what AI can realistically achieve, and identify opportunities to implement AI in organizations.
Key Highlights
- Basic AI terminologies
- Understanding various opportunities and how how to implement AI to solve them
- Creating an AI strategy for your company
- Machine learning and data science workflow
Course Modules
- What is AI?
- Building AI projects
- Implementing AI in your company
- AI and society
Course Details
Instructors: Andrew Ng
Duration: 11 hours
Level: Beginner
User Rating: 4.8/5
Price: Free Enrollment (Fees applicable to obtain certificate)
5. Expand Your Knowledge of Artificial Intelligence – Udacity
Udacity offers this artificial intelligence course. The nanodegree programs are standard specialization programs but differ in course levels.
It is created by the co-founder of Udacity, Sebastian Thrun, a renowned AI expert, and Peter Norvig. Mainly, this course is best suited for beginner and intermediate learners with essential programming experience. Some of the key concepts include optimization, planning, and pattern recognition.
Not only the foundational concepts, but you can gain hands-on experience and learn to write classical AI algorithms such as Bayes Networks, Hidden Markov Models, and much more.
The prerequisite for the course includes knowledge of linear algebra and calculus, some experience with Python and object-oriented programming, and the ability to run programs using a command line terminal.
Key Highlights
- Master the theoretical concepts and classical AI algorithms
- Learn programming with Python
- Best practices for AI model optimization
- Understanding agent-based models and optimization problems
- Peer review from industry experts
- Technical mentorship support
Course Modules
The course has six modules, each focusing on teaching new concepts and algorithms and emphasizing hands-on experience:
- Introduction to artificial intelligence: The first module introduces the fundamentals of AI with concepts covering the configuration of the programming environment to working on beginner-level AI problems using Python.
- Classical search: Under the second module, you will learn about the classical graph search algorithm and understand various associated techniques, such as breadth-first search and depth-first search, respectively. Next, you will explore how these techniques have become the core of planning, optimization, and problem-solving and learn to implement them for complex domains.
- Automated planning: In this module, you will learn to solve real problems using logic and find optimal plans to achieve agent-based goals. Additionally, you will explore how planning and scheduling systems can be automated using AI and its impact in various industries such as logistic operations, aerospace applications, Hubble telescope, and more. Finally, the practical sessions focus on enabling learners to build a forward planning agent model.
- Optimization problems: The fourth module focuses on concepts associated with iterative improvement optimization problems. These are one of the classical algorithms that are gradient-free problem-solving methods. Again, there are various classroom exercises where you will learn to compare different algorithms and their performance for multiple problems.
- Adversarial search: In this module, you will explore the multi-agent environment that has become of primary interest in the modern AI industry. Aside from that, you will cover the concepts of the minimax theorem and learn to build an agent-based model that can play games better than humans.
- Fundamentals of probabilistic graphical models: The final module introduces the concepts of Bayes Nets and understands how to use these algorithms for sampling probability distributions. Next, you will dive deep into the process of building an algorithm where you train and test your model to predict and evaluate the outcomes for pattern recognition problems accurately. There are also essential concepts on gesture recognition, gene sequence identification, speech generation, and speech tagging and learning to build the models for various scenarios.
Course Details
Instructors: Sebastian Thrun, Peter Norvig, and Thad Starner
Duration: 3 months, 12-15 hours/week
Level: Beginner/Intermediate
User Rating: 4.5/5
Price: $286/month or $729 for 3-month access
6. Artificial Intelligence A-Z: Learn How to Build An AI – Udemy
This is a unique online course among various artificial intelligence courses. Not only are you starting from the beginner level, but with each module, you move your way toward the intermediate and advanced levels throughout the course. However, the basic requirements of the course include knowledge of high-school-level mathematics concepts like linear algebra and basic programming with Python.
You will begin with the fundamental AI concepts covering areas like how to build AI, merge AI with OpenAIGym, and learn to optimize AI to maximize its potential for real-world problems. Another reason to opt for this artificial intelligence course is its high enrollment rate of over 186,000 students with significantly higher ratings.
Every tutorial enables you to write codes to build AI from scratch for different problems. There is also a provision for downloadable Python code templates for the learners and build a deeper understanding of every concept, with an approach of “learn by doing.”
Likewise, every module has a varying structure with increasing difficulty levels so that you can adapt to different real-world scenarios and build AI, test and deploy them as the scenario demands.
Some of the critical projects include learning to develop AI-enabled technologies for self-driving cars, developing AI-to-beat games, and building deep Q-learning models.
Key Highlights
- Understanding the theory behind AI
- Building AI models for a wide range of tasks, including data science
- Q-Learning
- Deep convolutional Q-learning
- Making AI models beat games
- Project on self-driving cars
- A3C algorithms
Course Modules
- Fundamentals of reinforcement learning
- Q-learning intuition
- Q-learning visualization
- Deep Q- learning intuition
- Deep Q- learning implementation
- Deep Q-learning visualization
- Deep convolutional Q-learning: from intuition to visualization
- A3C intuition
- A3C implementation
- A3C visualization
- Annex 1: Artificial neural network
- Annex 2: Convolutional neural networks
- Bonus lectures
Course Details
Instructors: Hadelin de Ponteves, Kirill Eremenko, Luka Anicin, Jordan Sauchuk, and Ligency Team
Duration: 16 hours
Level: Beginner-Advanced
User Rating: 4.4/5
Price: $43
7. Professional Certificate in Foundations of AI – edX
This program is meant for learners with little or no prior experience in AI, computer science, or programming skills. Each module of this artificial intelligence course is designed to better comprehend basic concepts, including multiple industrial use cases to improve AI skills.
In addition, you will become familiar with machine learning, deep learning, and natural language processing concepts. Throughout this program, you will also be introduced to IBM Watson AI services for building AI and deploying pre-built solutions for different problem areas.
At the same time, there are some complex topics where you will engage in developing and deploying AI applications from scratch. Similarly, there are various hands-on sessions within different AI environments and applications. You will learn to create intelligent solutions, such as virtual assistants, towards the end of the course.
Key Highlights
- Understanding AI and its applications in various business aspects and use cases
- Comprehensive understanding of all the key terminologies and AI techniques
- In-depth knowledge of ethical issues and concerns
- Fundamentals of IBM Watson machine learning
- Working with deep learning models
- Watson AI services on the IBM cloud
- Understanding chatbots and their uses
- Leveraging IBM Watson to enhance AI capabilities
- Fundamental principles of natural language processing for an effective chatbot design
- Creating a chatbot with minimal coding
- Deploying chatbot on WordPress website
- Building chatbots for customers
Course Modules
- AI for Everyone: Master the basics
- Introduction to WatsonAI
- AI chatbots without programming
Course Details
Instructors: Rav Ahuja and Antonio Cangiano
Duration: 4 months
Level: Beginner/Intermediate
User Rating: N/A
Price: $307
8. Master the Fundamentals of AI and Machine Learning – LinkedIn Learning
This program is the first of many artificial intelligence courses covering both the fundamentals of AI and machine learning.
Through a series of AI courses in this learning path, you will gain a basic understanding of the primary AI and machine learning concepts and their differences. Additionally, you will dive deep into how modern organizations implement various AI capabilities using machine learning, deep learning, and natural language processing models for different theoretical and technical aspects.
As much as the course emphasizes learning AI, a particular interest is shown in imparting knowledge for understanding issues of accountability, security, and explainability of AI solutions.
Key Highlights
- Introducing artificial intelligence and machine learning workflow
- Essentials for addressing AI-related issues such as transparency, explainability, accountability, and ethics in designing AI models and their execution and deployment
- Using machine learning to make better business decisions and identifying patterns from the data
- Key concepts of strong and weak AI and best practices for building AI-enhanced technologies
- Understanding the concepts of artificial neural networks and their uses in finding patterns from big data
- Discovering how neural networks work
- Learning about cognitive learning theory for AI and robotics
- Exploring AI algorithms for creating two-player games with turn-based gaming options during gaming
- Understanding AI from a business leader’s perspective. Q&A with a VP of artificial intelligence at LinkedIn
- Harnessing the power of AI to streamline workflows and gain a competitive advantage
- Understanding how explainable AI works and its uses for solving data science projects
- Leveraging artificial intelligence for solving complex problems such as cyber security
Course Modules
- AI accountability essential training
- Artificial intelligence foundations: machine learning
- Artificial intelligence foundations: thinking machines
- Artificial intelligence foundations: neural networks
- Cognitive technologies: the real opportunities for business
- Artificial intelligence algorithms for gaming
- AI the LinkedIn way: a conversation with Deepak Agarwal (VP)
- Artificial intelligence for project managers
- Learning XAI: explainable artificial intelligence
- Artificial intelligence for cybersecurity
Course Details
Instructors: Barton Poulson, Doug Rose, Deloitte Insights, Eduardo Corpeno, Deepak Agarwal, Oliver Yarbrough, Aki Ohashi, and Sam Sehgal
Duration: 14 hours
Level: Beginner
User Rating: N/A
Price: 1-month free trial (charge may apply after trial period)
9. Professional Certificate Program in AI and Machine Learning – Simplilearn
Learning AI has now become more straightforward with this online program among several artificial intelligence courses offered by Purdue University in collaboration with IBM on Simplilearn.
Several live sessions, practical labs, and hands-on projects prepare you with top skills focusing on current industry trends. You will also have access to “ask-me-anything” sessions with IBM experts to help navigate your career and enhance your skills.
In addition, there are three capstone projects from the industry from companies like Amazon, Walmart, Mercedes Benz, and Uber.
You can accelerate your career with this artificial intelligence course that provides an industry-relevant AI curriculum, including data science, machine learning, deep learning, NLP, and computer vision concepts.
There are also essential tools covered in this course, such as Python, TensorFlow, Keras, NLTK, scikit learn, matplotlib, OpenAI gym, Amazon Sagemaker, Django, and Kubernetes.
By the end of this course, you will be able to earn a professional certificate in AI and machine learning.
Key Highlights
- Fundamentals of statistics, artificial intelligence, machine learning, deep learning, neural networks, NLP, and reinforcement learning
- Python for data science problems, including libraries, writing scripts and using a Jupyter lab environment
- Data science and data analytics techniques using Python programming
- Mastering machine learning techniques with hands-on modeling
- Solid understanding of neural networks and deep learning using TensorFlow and Keras
- Introduction of computer vision concepts and hands-on experience in building real applications using generative adversarial networks (GANs)
- Understanding distributed parallel computing with GPUs and deploying deep learning models on the cloud
Course Modules
- Python for data science
- Applied data science with Python
- Machine learning
- Deep learning with TensorFlow and Keras
- Artificial intelligence and machine learning capstone project
Electives
- NLP and speech recognition
- Reinforcement learning
- Git and GitHub training
- Masterclass –Purdue University
- Industry masterclass
Course Details
Instructors: Simon Travasoli, Rocky Jagtiani, Nikhil Garg, and Nitin Gujral
Duration: 11 months
Level: Beginner/Intermediate
User Rating: 5/5
Price: $3568
10. DeepLearning. AI TensorFlow Developer Professional Certificate – Coursera
TensorFlow is among the most in-demand skills in the artificial intelligence industry. It is also a popular open-source framework used by many artificial intelligence experts. With this in mind, this is one of the best artificial intelligence courses for intermediate and advanced learners.
You will learn the best practices for TensorFlow and learn to use the deep learning framework to train neural networks for computer vision applications. Likewise, you will explore how you can build NLP systems using TensorFlow.
In this program, you will gain top practical skills with 16 hands-on training throughout the course. You will learn to handle real-world image data and explore techniques and strategies to address the issues of overfitting, augmentation, and dropout. Similarly, there are advanced concepts on RNNs, GRUs, and LSTMs for text repositories.
After finishing the program, you will also be equipped with the knowledge of various tools and concepts to prepare for the official Google TensorFlow certification exam to showcase your skills.
Key Highlights
- Learning to build and train neural networks using TensorFlow
- Enhancing the network’s performance with the help of convolutions for identifying real-world images
- Teaching your model to understand, analyze and respond to human speech using natural language processing algorithms
- Text processing, representing sentences as vectors using NLP systems
- Building scalable AI
Course Modules
- Introduction to TensorFlow for artificial intelligence, machine learning, and deep learning
- Convolutional neural networks in TensorFlow
- NLP in TensorFlow
- Sequences, time series, and prediction
Course Details
Instructors: Laurence Moroney
Duration: 4 months
Level: Intermediate/Advanced
User Rating: 4.7/5
Price: Free Enrollment (Fees applicable to obtain certificate)
11. Advanced and Applied AI on Microsoft Azure – Futurelearn
Many platforms offer advanced artificial intelligence courses, but only a few have the accreditation of industries. This AI course is provided by CloudSwyft and accredited by Microsoft.
You can now enhance your understanding of advanced machine learning and AI concepts and become familiar with Microsoft Azure and programming with python to help build AI algorithms for solving complex problems.
This artificial intelligence online course is also suitable for allowing you to prepare for industry-recognized certification exams such as Microsoft Azure AI Engineer Associate (AI-100) and Microsoft Azure AI Fundamentals (AI-900), respectively.
This expert track is a specialization program that helps develop in-demand practical skills with solid foundations in machine earning, AI, and data science concepts using AI. You will also have a detailed introduction to the core offerings of Microsoft Azure and learn advanced Azure AI functionalities.
With the help of Python programming, you will learn to build predictive AI models and use several machine-learning tools for different projects throughout the course. Finally, you will explore Azure cognitive services to create chatbots, gain basic knowledge of NLP programming, and implement language understanding (LUIS) to improve chatbot functionality.
There is also a provision for tutorial interactions and academic credit and feedback assessments. However, the course requires prior experience in Python basics, C#, Creative Studio, Excel, linear algebra, and databases.
Key Highlights
- Azure cloud portal administration
- Azure cognitive services
- Azure machine learning models
- Coding AI using advanced programming with Python
- Machine learning algorithms
- Statistics for artificial intelligence
- Mathematics for artificial intelligence
- Microsoft Bot Framework
- Chatbot development and LUIS integration
Course Modules
- Microsoft future ready: Using Python programming to explore the principles of machine learning
- Applied artificial intelligence: NLP
- Applied artificial intelligence: Computer vision and image analysis
Course Details
Instructors: CloudSwyft and Microsoft Professionals
Duration: 15 weeks
Level: Intermediate
User Rating: N/A
Price: Free 7-day trial and $11/month
12. Digital Skills: Artificial Intelligence – Futurelearn
This artificial intelligence course is best suited for gaining basic knowledge about pivotal moments and the history of AI and demystifying various facts and fiction to understand realistic AI capabilities.
You will then explore the benefits of AI and investigate multiple issues surrounding the ethics of AI. With this knowledge, you will delve into AI applications across industries, ranging from retail to agriculture, and work on numerous case studies to understand the impact of AI.
In addition, several exercises to help you identify the gaps in the AI landscape. In the course’s final weeks, you will work on assessing how AI-driven technologies might help solve real-world problems and develop strategies for evolving industries.
Besides the unique curriculum being developed by Accenture, the course is accredited by the CPD certification service.
Key Highlights
- Origins and advent of AI
- Understanding the relationship between AI and automation
- Knowledge representation and applications of AI
- Identifying the critical changes influenced by artificial intelligence in the organizations
- Impact of AI and the new roles and responsibilities
- Identifying the relationship between humans and AI
- Future skills influenced by artificial intelligence
- Action plan for adapting AI skills
Course Modules
- Introduction to artificial intelligence
- Artificial intelligence in the Industry
- Adapting your skills to work with artificial intelligence
Course Details
Duration: 3 weeks
Level: Beginner
User Rating: 4.7/5
Price: Free
13. Deep Learning and Python Programming for AI with Microsoft Azure – Futurelearn
This expert track is another top AI course offered by CloudSwyft in collaboration with Microsoft. It is best suited for advanced training in artificial intelligence and deep learning for professionals, students, and data scientists with prior experience in the field.
This online program is a clear choice for the best artificial intelligence course to clear the Microsoft Azure AI Engineer Associate exam through lectures and hands-on lab sessions. You will grow your knowledge about several latest AI programming solutions, including speech recognition and NLP systems.
This specialization program helps you to understand how to build and implement cutting-edge deep learning models and apply machine learning techniques to build predictive models for AI. You will also explore how various software driven by AI can process, analyze and extract meaning from natural language, including images and videos similar to humans.
While examining several real-world AI examples, you will also explore Microsoft Azure to build AI systems. You will learn to develop deep semantic similarity models, neural networks for machine translation, signal processing for speech recognition, acoustic modeling, and labeling. Likewise, you will investigate existing algorithms for language modeling.
Key Highlights
- Creating AI programs
- Advanced concepts of machine learning and deep learning
- Programming with Python
- Microsoft Azure
- Data Science
- Statistics and probability
- Python data structures
- Statistical modeling
- Neural networks
Course Modules
- Deep learning on Azure with Python: AI for beginners
- The basics of Python programming
- Introduction to machine learning
- Introduction to deep learning
- Reinforcement learning
Course Details
Duration: 21 weeks
Level: Intermediate
User Rating: N/A
Price: $11/month
14. AI for Healthcare Nanodegree Program – Udacity
Artificial intelligence has been at the forefront of transforming healthcare. This is among the best artificial intelligence courses if you are looking for a career as a researcher or an engineer in the healthcare industry.
As such, this is one of the most interesting artificial intelligence courses focusing on AI in healthcare and improving patient outcomes. You will learn how AI is implemented to enhance medical decisions with power AI and machine learning models, which are gradually emerging as the most promising technologies for the healthcare industry.
From learning to build, evaluate and integrate predictive models to developing AI algorithms to classify and segment 2D and 3D medical images, you will undergo rigorous training to help elevate your skillsets. You will also learn how to augment diagnosis and build AI models for patient outcomes using electronic health records to improve clinical trials and decisions.
Finally, you will also explore how to build algorithms that capture data from wearable devices to estimate information such as pulse rates due to the wearer’s motion. This online course is offered for intermediate learners; therefore, you must have prior coding experience in Python, building models, various Python libraries, and machine learning frameworks to perform data manipulation and cleaning data.
Key Highlights
- Fundamentals of 2D medical imaging data
- Learn to gain insights from data gathered from different medical images such as X-rays, mammography, and digital pathology
- Extracting 2D images from DICOM files
- Performing data analysis
- Implementing AI solutions for 2D images and positioning AI tools for regulatory approval
- Create powerful AI to work with 3D medical images in a clinical context
- Understanding data acquisition of medical images and storage
- Designing AI algorithms to solve challenging problems related to 3D medical images and integrating them into the clinical workflow
- Fundamentals of EHR data and building and evaluating AI models that comply with regulations
- Build interpretable AI and understand EHR data privacy and security issues
- Build robust and real-world applications using TensorFlow
- Foundations of sensors, and signals, including IMU, PPG, and ECG, that are commonly associated with wearable devices
- Building algorithms to process data collected by wearable devices in real-time
Course Modules
- Applying AI to 2D Medical Imaging Data
- Applying AI to 3D Medical Imaging Data
- Applying AI to EHR data
- Applying AI to Wearable device data
Course Details
Duration: 4 months
Level: Intermediate
User Rating: 4.6/5
Price: $286/month or $976/4-month access
15. Become a Machine Learning Engineer for Microsoft Azure – Udacity
This nanodegree program is a specialization on the Udacity platform, offered in collaboration with Microsoft. With this AI course, you can upskill with advanced machine learning skills and build practical applications using Azure machine learning.
You will be able to master the most in-demand programming skills with the help of artificial intelligence online lab sessions.
Some prerequisites include AI programming experience using Python, concepts of variables, loops, data types and functions, fundamentals of statistics, basic knowledge of machine learning concepts, and some understanding of the basics of Azure, such as Docker and Container.
In this program, you will also learn to build and deploy sophisticated machine-learning solutions using open-source tools and frameworks and gain ample practical experience using machine learning for complex tasks using the built-in Azure lab environment. However, students must complete a final capstone to attain the course completion certificate.
Key Highlights
- Machine learning configurations and AI programming
- Understanding machine learning pipelines in Azure
- Use cases for automated machine learning
- Using Azure ML SDK for designing, creating, and managing machine learning pipelines in the Azure environment
- Learning to select appropriate targets for model deployment
- Identifying problem areas in logs
- Understanding the process of moving machine learning models into the production phase
- Using Azure automated ML and HyperDrive to solve problem areas
- Deploying the ML model as a web service and testing the model endpoint
- Technical mentorship
- Peer review and GitHub review
Course Modules
- Using Azure machine learning
- Machine learning operations
- Capstone project
Course Details
Duration: 3 months
Level: Intermediate
User Rating: N/A
Price: $286/month or $729/3-month access
Summary
We spent a lot of time curating this list of the best online courses for artificial intelligence. When choosing a course, be sure to look into the modules and costs before making a decision.
Whether you’re a newbie to AI, or you’ve already got a few AI courses under your belt, there is always more to learn.
Moving forward with one of these online AI courses can earn you a professional certificate, teach you AI programming, and potentially even help you land a job on an AI team in an emerging company.
Disclosure: Some of the links in this article may be affiliate links, which can provide compensation to us at no cost to you if you decide to purchase a paid plan. This site is not intended to provide financial advice and is for entertainment only. You can read the affiliate disclosure in our privacy policy.
