AI Courses by Coursera
Browse AI Courses by Coursera:
Coursera
AI for Everyone
This course is designed for everyone in your organization, especially non-technical colleagues, to enhance their understanding of AI. Participants will learn key AI concepts, realistic capabilities and limitations of AI, how to identify opportunities for AI application, and the basics of building machine learning projects. Additionally, the course covers collaboration with AI teams, developing an AI strategy, and navigating ethical considerations. Engineers are also welcome to gain insights into the business aspects of AI.
Introduction to Artificial Intelligence (AI)
This course provides a comprehensive introduction to Artificial Intelligence (AI), covering essential concepts such as deep learning, machine learning, and neural networks. You will explore generative AI models, their applications in natural language processing, computer vision, and robotics, and understand AI’s transformative impact on businesses and career opportunities. The course includes hands-on labs, a project, and insights from industry experts on AI capabilities, applications, and ethical considerations, making it suitable for professionals, enthusiasts, and students alike.
Generative AI for Everyone
Instructed by AI pioneer Andrew Ng, Generative AI for Everyone provides a practical understanding of generative AI, covering its capabilities and limitations. The course includes hands-on exercises for using generative AI in daily tasks, effective prompt engineering, and advanced applications. Participants will explore real-world use cases and gain insights into the impact of generative AI on business and society, ensuring that everyone can engage with our AI-powered future.
Deep Learning Specialization
Instructed by AI pioneer Andrew Ng, Generative AI for Everyone provides a practical understanding of generative AI, covering its capabilities and limitations. The course includes hands-on exercises for using generative AI in daily tasks, effective prompt engineering, and advanced applications. Participants will explore real-world use cases and gain insights into the impact of generative AI on business and society, ensuring that everyone can engage with our AI-powered future.
Machine Learning Specialization
The Machine Learning Specialization is a foundational online program developed by DeepLearning.AI and Stanford Online, designed for beginners to learn the essentials of machine learning and apply these techniques to real-world AI applications. Taught by AI expert Andrew Ng, this updated 3-course specialization covers topics such as supervised and unsupervised learning, along with best practices for AI and machine learning innovation. By completing the program, you will gain practical skills to effectively tackle real-world challenges in the field of AI and machine learning.
IBM AI Engineering Professional Certificate
In this program, you will learn to build, train, and deploy various deep learning architectures, including convolutional neural networks, recurrent networks, autoencoders, and generative AI models like large language models (LLMs). You will gain a solid understanding of machine learning concepts, applying Python and popular libraries such as SciPy, ScikitLearn, Keras, PyTorch, and TensorFlow to real-world problems in areas like computer vision, text analytics, and recommender systems. Through hands-on labs and projects, you will develop practical skills in deep learning frameworks, preparing you for in-demand roles in the field. Enroll today to enhance your resume and portfolio with job-ready skills.
Generative AI: Introduction and Applications
This course is tailored for professionals, executives, students, and enthusiasts eager to understand and apply generative AI in various contexts. You will learn the fundamentals and applications of generative AI across text, image, audio, video, and more, while exploring popular models and tools like GPT, DALL-E, and ChatGPT. Hands-on labs will allow you to engage with these technologies, and insights from practitioners will enhance your understanding of their capabilities and uses.
AI in Education: Leveraging ChatGPT for Teaching
In this short course, educators will learn to effectively integrate AI into their classrooms alongside Ethan and Lilach Mollick. Participants will gain essential knowledge about AI tools like ChatGPT, enabling them to create AI-driven assignments and prompts that align with their educational goals. The course addresses common challenges, such as academic integrity and ethical concerns, while demonstrating how to leverage AI to save time, personalize learning, and enhance student engagement.
AI For Business
This specialization equips learners with the essentials of Big Data, Artificial Intelligence, and Machine Learning, focusing on their application in business. You will explore AI ethics, governance frameworks, and fair HR practices, along with effective marketing strategies through data analytics. By the end, you’ll be prepared to implement ethical AI in people management and understand how these technologies can transform business operations.
IBM AI Developer Professional Certificate
The IBM AI Developer Professional Certificate program prepares you for a career in AI by teaching you essential skills in building AI-powered chatbots and applications, with no prior experience required. Over six months, you will learn software engineering fundamentals, AI concepts, and programming languages like HTML, JavaScript, and Python through hands-on labs and projects. Upon completion, you’ll receive a Professional Certificate from Coursera and a digital badge from IBM, along with access to career assistance and job preparation resources. Enroll now to enhance your career opportunities in AI.
IBM AI Product Manager Professional Certificate
Prepare for a career in the growing technology sector with this program, where you’ll acquire essential skills in product management, prompt engineering, and artificial intelligence in three months or less, with no prior experience needed. You’ll learn the fundamentals of product management, including the entire product lifecycle, while gaining insights into generative AI concepts and completing hands-on projects. Upon completion, you’ll have a portfolio and a Professional Certificate from IBM to demonstrate your expertise.
Generative AI with Large Language Models
In the Generative AI with Large Language Models (LLMs) course, you’ll explore the fundamentals of generative AI and its real-world applications. You’ll gain a comprehensive understanding of the LLM lifecycle, the transformer architecture, and optimization techniques, while applying advanced training and deployment methods. This intermediate course is designed for those with a foundational knowledge of Python and basic machine learning concepts, making it ideal for learners ready to deepen their expertise in generative AI.
DeepLearning.AI TensorFlow Developer
The DeepLearning.AI TensorFlow Developer Professional Certificate program equips you with applied machine learning skills using TensorFlow, one of the leading open-source deep learning frameworks. Through a hands-on, four-course structure, you will learn to build scalable AI applications and apply your skills to various projects. Completing this program will also prepare you for the Google TensorFlow Certificate exam.
Google AI Essentials
Google AI Essentials is a self-paced course designed for individuals across various roles and industries to acquire essential AI skills, requiring no prior experience. In under 10 hours, you’ll learn to effectively use AI tools for tasks like generating ideas, organizing events, and managing email responses, while also understanding how to write effective prompts and recognize AI biases. Upon completion, you will receive a certificate from Google to showcase your skills to potential employers.
Generative AI and ChatGPT for K-12 Educators
This hands-on specialization is designed for K-12 educators eager to leverage generative AI tools like ChatGPT to enhance lesson planning and engage students creatively. Participants will learn to create tailored lesson plans, interactive games, AI-powered activities, and personalized quizzes, all adaptable to various subjects and student levels. By fostering innovative thinking, this course prepares educators to integrate AI into their teaching while promoting critical thinking skills. No prior experience with AI or prompt engineering is required.
Introduction to Deep Learning & Neural Networks with Keras
This course provides an introduction to deep learning, covering essential concepts such as the differences between neural networks and deep learning models. Learners will explore various deep learning models, including unsupervised models like autoencoders and supervised models like convolutional and recurrent networks, while gaining hands-on experience building their first deep learning model using the Keras library. By the end of the course, participants will have a solid understanding of deep learning fundamentals and practical skills in model development.
This course covers two key areas of Machine Learning: Deep Learning and Reinforcement Learning. You will learn the theory behind Neural Networks and modern Deep Learning architectures, followed by practical applications of Reinforcement Learning. By the end, you will have a solid understanding of Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning, along with the ability to explain clustering challenges and apply relevant algorithms. Prior knowledge of Python programming and foundational concepts in data analysis, calculus, linear algebra, probability, and statistics is recommended.
The updated 2024 course, Mathematics for Machine Learning and Data Science, is an online program by DeepLearning.AI, taught by Luis Serrano. This specialization emphasizes applying mathematical concepts through Python programming in hands-on labs, requiring basic to intermediate Python skills. It covers essential topics such as vector and matrix operations, linear transformations, eigenvalues and eigenvectors, optimization techniques, and statistical methods, equipping learners to analyze data and quantify uncertainty in machine learning models. Familiarity with high school-level mathematics and programming concepts is recommended for success in the course.
The IBM Generative AI Engineering Professional Certificate equips aspiring AI engineers, developers, and data scientists with essential skills in generative AI, large language models, and natural language processing. Participants will gain hands-on experience in generating text and images, applying prompt engineering, and developing AI applications using Python and frameworks like Flask. The program includes practical projects, such as creating an NLP data loader and fine-tuning models, preparing graduates for in-demand roles in the rapidly growing generative AI market. Enroll today to enhance your career opportunities in under six months.
Google Prompting Essentials is a self-paced course designed to help you effectively use generative AI tools through clear and specific instructions, known as prompting. In under 10 hours, you will learn to save time, uncover insights, tackle complex projects, and use AI responsibly, all while building a library of reusable prompts. No prior experience is needed, and upon completion, you will receive a certificate from Google to share with your network and employer.