Greetings from the AI Odyssey! The fifty AI courses in this collection from 2024 have been carefully chosen to guide you through the fascinating world of artificial intelligence. You can choose from a wide range of courses that are precisely matched to your interests and level of competence, covering everything from the most fundamental ideas to the most innovative applications. Join us on this journey to witness the cutting edge of AI research and innovation. Together, let’s explore the vast potential of artificial intelligence!
Overview of Google’s Generative AI through Coursera:
A kind of artificial intelligence called “generative AI” is devoted to producing fresh, original information. There are video presentations available in the Introduction to Generative AI course. Engage with Google, instructor Charles Isbell, and other course providers while watching engaging films that will keep you captivated and amused.
Coursera offers IBM’s Introduction to Artificial Intelligence: Upon successful completion of this extensive professional certificate program, the learner will have the ability to apply IBM Watson artificial intelligence technology and gain practical skills in artificial intelligence.
Coursera offers Andrew Ng’s course, Supervised Machine Learning: Regression and Classification.
Students will master the fundamentals of machine learning in this course, including how to use key models, ideas, and algorithms.
LinkedIn DALL·E and Generative AI: This provides an in-depth exploration of generative AI and OpenAI’s groundbreaking DALL·E. curated on LinkedIn by experts in the field.
TensorFlow 2.0 for Deep Learning via Udemy: Using TensorFlow 2.0, this course gives participants a thorough introduction of the most recent advances in deep learning research and development. The expert behind this video is Holly Grace.
CS50AI (Complete Review 2024): Top Course on Artificial Intelligence?
This course is regarded as the top artificial intelligence course for 2024 among all AI courses. It serves as an introduction to Python-based artificial intelligence.
The Artificial Intelligence Nanodegree program: The course offered by Udacity equips graduates with a strong foundation in probabilistic graphical models, planning and scheduling systems, and AI algorithms. Additionally, the curriculum teaches students how to apply this knowledge to solve real-world problems.
The AWS Generative AI Developer Kit: It is a paid course that covers the general ideas and techniques of generative AI as well as the tools and technologies associated with it.
The Professional Certificate in Computer Science for Artificial Intelligence from Harvard University: Basic AI-related topics are covered in the Harvard University Professional Certificate in Computer Science for Artificial Intelligence.
The MIT Professional Certificate Program in Artificial Intelligence and Machine Learning: With starting at $6,325; + 2,500 for optional requirements, this course covers advanced themes in machine learning.
The 16-week course on AI fundamentals and applications at Stanford University: This course covers topics such as computer vision, robotics, machine learning, and natural language processing among AI courses in 2024.
Elements of AI: This is a free online course that is intended for people of all ages who are curious about what artificial intelligence (AI) is, what it can do, what it cannot do, and how it operates. That also implies a lack of complex programming or mathematics.
Udacity’s Artificial Intelligence Nanodegree Program: Graduates of the curriculum are equipped with all the knowledge necessary to use AI algorithms, probabilistic graphical models, planning, and scheduling systems to solve problems in the real world.
AI for All by DeepLearning,AI: Coursera offers an AI course designed for individuals who are interested in learning about AI but lack background knowledge. It covers the fundamentals of artificial intelligence, machine learning, and deep learning as well as how to use this information to address practical issues.
IBM’s Fundamentals of Generative AI on Coursera: This three-week course introduces us to generative models for producing fresh data and evaluating the caliber of the generated data.
IBM on Coursera offers Generative AI for Data Scientists: Data scientists may learn how to create new data generations and generative models in this three-week course.
AI Fundamentals for All via IBM Coursera: This introductory course covers the fundamentals, applications, and ethics of artificial intelligence. Anyone who might be interested can use it.
Coursera offers IBM’s AI Foundations for Business course: The eight-hour training explores how artificial intelligence (AI) can be applied in business and is intended for business people.
With IBM’s AI Product Manager on Coursera: Product managers who complete the seven-hour training will gain knowledge on identifying suitable AI initiatives and creating and overseeing AI products.
IBM’s AI for Healthcare on Coursera: The six-hour training covers patient outcomes, the fundamentals of AI in healthcare, and the advantages of cutting costs for both patients and the healthcare system.
Coursera offers IBM AI for Manufacturing: This training gives manufacturing experts an introduction to AI fundamentals. IBM’s AI course is tailored for manufacturing professionals and teaches them how to use AI to build products, improve product quality, and lower manufacturing costs.
IBM created a course on Coursera called AI for Retail: For retail AI specialists, the training serves as a depiction of the fundamentals. Here, you may find out how to use AI in your retail business to enhance customer experience, increase sales income, and cut expenses.
Coursera offers Andrew Ng’s course, Supervised Machine Learning: Regression and Classification.
This is a general overview of machine learning, including some of the key ideas and uses.
Coursera’s IBM AI for Finance: Bankers are taught how to use AI practically in this course, which covers risk and investment management, asset selection and appraisal, and financial analysis.
IBM Applied AI: This course provides instruction on how to quickly use IBM Watson AI technology together with a professional artificial intelligence credential.
AI Product and Service Design and Development at MIT, Coursera: This offers an examination of the ideas and procedures involved in creating artificial intelligence-based goods.
Coursera offers Probabilistic Graphical Models from Stanford University: This course covers both accurate and approximate inference strategies using probabilistic graphical models.
Andrew Ng’s Deep Learning Specialization: It is available through Coursera and covers deep learning with an emphasis on practical topics including CNNs, RNNs, and deep learning frameworks.
Stanford University: Machine Learning: This course provides an introduction to machine learning, covering both supervised and unsupervised learning concepts and their practical applications.
Coursera is offering Andrew Ng’s book AI for Everyone: The course covers the fundamental terminologies used in artificial intelligence, including neural networks.
Coursera offers TensorFlow for Machine Learning, Deep Learning, and Artificial Intelligence: This introductory course is part of a four-course deeplearning.ai certificate program that teaches users how to create a simple neural network in TensorFlow and use an open-source machine learning framework.
Udacity’s Artificial Intelligence Nanodegree: This thorough beginning-to-intermediate course aims to give students a thorough understanding of both the theoretical underpinnings of artificial intelligence and the real-world applications of training one.
Professional Certificate in Artificial Intelligence through Computer Science from edX: This course, which is intended for beginners to intermediate specialists, delves deeply into the nuances of each design aspect to clearly understand the basic principles of artificial intelligence (AI) and provides masters with insights into the principles of AI and the tools that make those principles operate.
Coursera’s Natural Language Processing Specialization: This course, designed for beginners and intermediate learners, offers insights into natural language processing and the reasoning behind its application.
CourseWare’s Artificial Intelligence: Excellent knowledge of AI algorithms, machine learning, and probabilistic techniques is provided by this intermediate course.
Overview of Google’s Generative AI through Coursera: With an emphasis on producing fresh, original material, this intermediate course teaches how to develop generative AI and explains its purpose.
Coursera offers IBM’s Introduction to Artificial Intelligence: The learner will gain great practical knowledge of AI and IBM Watson AI from this intermediate course.
Coursera’s Deep Learning Specialization: This intermediate course first covers the deep learning network and learning framework, before going on to introduce RNN and CNN.
Self-driving Cars with Duckietown by edX: This intermediate course focuses mostly on hand-tested methods for self-driving cars.
AI A-Z 2023: Build 5 AI (including ChatGPT) available on Udemy by Alex Genadinik: With the help of this AI beginner course, participants will get sufficient insight into AI concepts and intuition to begin developing AI using Python without any prior coding experience.
DataCamp’s Understanding Artificial Intelligence: This quick course is helpful for developing the fundamentals of AI.
An Introduction to Generative AI Learning by Google Cloud: There are quizzes in this free course. The fundamentals of generative AI are covered.
Prompt Engineering Specialization: This course covers the efficient prompting of big language models among AI courses in 2024.
Mastering OpenAI Python APIs: It is a course that gives students a hands-on introduction to OpenAI’s APIs, particularly ChatGPT.
AI and Ethics in edX: This course, AI and Ethics in edX, examines the broad ethical issues surrounding the applications of AI technologies.
edX’s Machine Learning for Analytics and Data Science: This is an additional course. This data science course is focused on machine learning.
Robotics and artificial intelligence: Learn more about the integration of robotics and artificial intelligence in the construction of autonomous systems.
Python for Machine Learning: Learn the principles of machine learning with the most popular machine learning programming language.
AI for Social Good: Examples of AI and ML applications for people’s wellbeing that address global concerns are provided by AI for Social Good.
