Learning artificial intelligence (AI) is becoming increasingly important for both technical and non-technical professionals as it has the potential to revolutionize various industries and provide innovative solutions to complex problems. has become Free AI courses and online certifications equip individuals with the knowledge and skills they need to remain relevant in today’s rapidly evolving job market.
Machine Learning Specialization by DeepLearning.AI and Stanford Online
Machine Learning Specialization by DeepLearning.AI and Stanford Online is a foundational online program that provides a broad introduction to the latest in machine learning. This three-course specialization is an AI visionary who has led significant research at Stanford University and conducted groundbreaking research at Google Brain, Baidu, and Landing.AI to advance his AI field. Taught by Andrew Ng.
Other notable instructors include Eddy Shyu, Curriculum Product Manager at DeepLearning.AI. Curriculum Engineer Aarti Bagul. Another one he is DeepLearning.AI’s head of his instructor, Geoff Ladwig.
The first course in the specialization is Supervised Machine Learning: Regression and Classification. This course builds machine learning models in Python using the popular machine learning libraries NumPy and scikit-learn to build and train supervised machine learning models for prediction and binary classification tasks. , including linear and logistic regression.
The second course is Advanced Learning Algorithms. In this course, you will use TensorFlow to build and train neural networks, perform multiclass classification, and apply machine learning development best practices to ensure your models generalize to real-world data and tasks. , describes its construction and use. Decision trees and tree ensemble methods, including random forests and boosting trees.
The third and final course is Unsupervised Learning, Recommenders, and Reinforcement Learning. This course teaches you how to use unsupervised learning techniques for unsupervised learning. This includes building recommendation systems using clustering and anomaly detection, collaborative filtering approaches and content-based deep learning techniques. Building deep reinforcement learning models.
By the end of this specialization, you’ll have mastered key concepts and the practical know-how to quickly and powerfully apply machine learning to difficult real-world problems. If you’re looking to get into AI or build a career in machine learning, the Machine Learning Specialization is a great place to start.
Introduction to Artificial Intelligence in Python for CS50 by Harvard University
Harvard’s CS50 Introduction to Artificial Intelligence in Python is an introductory course that explores the latest artificial intelligence concepts and algorithms. Courses are free on his edX, but students can purchase verified certificates for an additional fee. The instructor for this course is Gordon McKay, Professor of Practice in Computer Science at Harvard University. Brian Yu, Senior Instructor in Computer Science at Harvard University. and David Mullan.
Students dive into the ideas that give rise to technologies such as gameplay engines, handwriting recognition, and machine translation. This course teaches students how to incorporate machine learning concepts and algorithms into Python programs through a series of hands-on projects.
Related: A Brief History of Artificial Intelligence
Students will be exposed to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning. By the end of the course, students will have experience with libraries for machine learning and knowledge of artificial intelligence principles that will enable the design of their own intelligent her systems.
AI For Everyone by Coursera in collaboration with DeepLearning.AI
AI for Everyone is an online course offered by Coursera in collaboration with DeepLearning.AI. This course is designed for non-technical learners who want to understand AI concepts and their practical applications. Provides an overview of AI and its impact on the world, covering key concepts in machine learning, deep learning, and neural networks.
The course is taught by noted AI expert and founder of DeepLearning.AI, Andrew Ng. He is also the co-founder of his Coursera, where he previously taught popular online courses on Machine Learning, Neural Networks and Deep Learning. The course consists of his four modules, each covering a different aspect of his AI. these are:
- What is AI
- Building an AI project
- Build AI in-house
- AI and society
The course is self-paced and takes approximately 10 hours to complete. This includes video lectures, quizzes, and case studies that enable students to apply the concepts they learn using popular programming languages such as Python.
Courses can be audited for free on Coursera, and financial aid is available for those who can’t afford the fees. A certificate of completion will also be issued for a fee.
Machine Learning Crash Course with the TensorFlow API by Google
Machine Learning Crash Course with TensorFlow API is a free online course from Google. Designed for beginners who want to learn about machine learning and how to use TensorFlow, a popular open source library for building and deploying machine learning models.
This course covers the following topics:
- Introduction to machine learning and TensorFlow
- linear regression
- classification
- neural network
- regularization
- Training and validation
- convolutional neural network
- natural language processing
- sequence model
Throughout the course, you’ll learn about various machine learning techniques and how to build and train models using the TensorFlow application programming interface (API). The course also includes hands-on exercises and coding assignments to help you gain hands-on experience building and deploying machine learning models.
This course is available for free on Google’s website and is self-paced so you can learn at your own pace. Upon completion, you will receive a certificate of completion from Google.
Related: 5 New Trends in Deep Learning and Artificial Intelligence
Introducing AI with Intel
The Intel® AI Fundamentals Course is an introductory level course that teaches the fundamentals of artificial intelligence and its applications. It covers topics such as machine learning, deep learning, computer vision, and natural language processing. Free self-paced courses contain modules that can be completed in any order.
The 8-week program includes lectures and exercises. Each week, students are expected to spend 90 minutes completing coursework. The exercises are implemented in Python, so prior knowledge of the language is recommended, but students can learn it along the way.
No certificate of completion is issued for this course, but students earn badges for completing each module. This course is designed for software developers, data scientists, and others interested in learning about AI.
Ready to join the AI revolution?
By leveraging the resources above, individuals can become part of the growing AI industry and help shape its future. Additionally, the ChatGPT Prompt Engineering for Developers course, jointly developed with OpenAI, develops opportunities to learn how to use Large Language Models (LLM) to build powerful applications in a cost-effective and efficient manner. provided to those The course is taught by two of his well-known experts in the field of AI, Isa Fulford and Andrew Ng.
Whether the learner is a beginner or an advanced machine learning engineer, this course provides an up-to-date understanding of prompt engineering and best practices for using prompts in modern LLM models. Hands-on experience will teach you how to use her LLM API for a variety of tasks, including summarization, reasoning, text transformation and augmentation, and building custom chatbots. This course is free for a limited time, so don’t miss your chance to join the AI revolution.
