This is a great time to be alive – a great time to learn and then, earn! So, in this piece – we shall talk about the free ones. The surge in AI tools like ChatGPT has sparked a growing interest in AI education, and luckily, there are plenty of free AI certification courses available. These top-notch programmes offer a fantastic opportunity to learn about generative AI, machine learning, and other cutting-edge technologies that are shaping our future. Let’s talk about some of the best AI courses for beginners and seasoned professionals alike.
Google AI for Everyone
IBM AI Foundations for Everyone
AWS Skill Builder AI Courses
DeepLearning.AI’s AI Specialisations
Harvard’s Introduction to AI with Python
Udacity’s AI Programming with Python
Coursera’s AI for Everyone by Andrew Ng
Microsoft’s AI Fundamentals
Intel’s AI Courses
Stanford University
Google AI for Everyone
Google’s AI for Everyone course offers a comprehensive introduction to artificial intelligence, cutting through the hype to deliver practical knowledge. These free AI certification programs are designed for individuals without a background in computer science or mathematics, making it accessible to anyone curious about AI and machine learning.
Key Topics Covered
The course delves into fundamental AI concepts, including neural networks, types of machine learning (supervised, unsupervised, and reinforcement), and real-world applications like recommender systems and computer vision. Participants gain hands-on experience with data, learning how to teach computers to recognise images and sounds.
Learning Outcomes
By the end of the course, learners will have a solid understanding of AI terminology, ethics, and fairness in AI applications. They’ll also gain insight into AI programming and its practical applications. This knowledge equips participants to engage in informed discussions about AI and machine learning in both personal and professional settings, providing a strong foundation for further exploration of these emerging technologies.
IBM AI Foundations for Everyone
This specialisation consists of three self-paced courses, each designed to be completed in about four weeks with 2-4 hours of study per week. The entire programme can be finished in 2-3 months at a relaxed pace or in just one month with more intensive study. The courses cover a range of topics, from AI basics to generative AI and chatbot creation, providing a comprehensive introduction to AI without requiring any coding skills.
Skills Gained
Participants will gain a solid understanding of AI fundamentals, including machine learning and neural networks. They’ll learn about generative AI, its real-world applications, and prompt engineering techniques. The course also teaches how to create AI-powered chatbots without programming, using IBM Watson’s Natural Language Processing capabilities. These skills are highly relevant in today’s job market, where AI literacy is becoming increasingly important across all industries.
Certification Details
Upon completing the specialisation, learners receive a verified digital credential from IBM, which can be shared on LinkedIn or added to a CV. This certification demonstrates expertise in AI fundamentals, generative AI applications, and chatbot development, providing a valuable asset for career advancement in the rapidly evolving field of artificial intelligence.
Subham Kumar
AWS Skill Builder AI Courses
AWS Skill Builder offers a robust range of AI courses, catering to various skill levels and interests. From introductory courses on generative AI to advanced topics like building language models, there’s something for everyone. The platform provides free and low-cost options, making it accessible to learners worldwide.
Learning Resources
Learners can access a wealth of resources, including interactive labs, video tutorials, and hands-on experiences. These tools are designed to help individuals build practical skills in AI and machine learning. The courses cover topics such as prompt engineering, low-code machine learning, and using AI-powered tools like Amazon CodeWhisperer.
Industry Recognition
AWS certifications are highly regarded in the tech industry. The platform offers exam preparation materials for AI-related certifications, including the AWS Certified AI Practitioner and AWS Certified Machine Learning Engineer – Associate. These credentials demonstrate expertise in AI fundamentals and applications, providing a valuable asset for career advancement in the rapidly evolving corridors of AI as we call it.
DeepLearning.AI’s AI Specialisations
DeepLearning.AI offers a range of top AI courses for beginners and professionals alike. Their Deep Learning Specialisation, led by AI pioneer Andrew Ng, has attracted over 1 million learners. This comprehensive programme covers neural networks, machine learning, and practical AI applications. The Machine Learning Specialisation provides a foundational understanding of AI concepts through an intuitive visual approach.
Instructor Expertise
The courses are taught by industry experts, including Andrew Ng, who co-founded Google Brain and Coursera. Their instructors bring real-world experience and cutting-edge knowledge to the programmes, ensuring learners gain practical skills in AI tools and generative AI.
Practical Applications
DeepLearning.AI’s courses focus on hands-on learning, allowing students to build and train neural networks, implement machine learning algorithms, and develop AI applications. Learners gain experience with popular frameworks like TensorFlow and explore areas such as computer vision and natural language processing.
Harvard’s Introduction to AI with Python
This course builds on CS50’s foundation, requiring basic programming knowledge. Familiarity with Python is beneficial, as is a grasp of statistics and probability concepts. The course is designed to accommodate learners with varying levels of experience in AI and machine learning.
Curriculum Highlights
The curriculum delves into core AI concepts, including graph search algorithms, classification, optimisation, and reinforcement learning. Students explore cutting-edge topics like game-playing engines, handwriting recognition, and machine translation. The course emphasises practical applications, enabling learners to incorporate AI principles into their own Python programmes.
Project-Based Learning
Hands-on projects form a crucial part of the learning experience. Students gain practical skills by working with machine learning libraries and designing intelligent systems. This approach allows learners to apply theoretical knowledge to real-world problems, preparing them for careers in AI and data science.
Ipsita Acharya
Udacity’s AI Programming with Python
This beginner-friendly programme offers a thorough exploration of Python AI programming. Learners gain hands-on experience with essential tools like NumPy, Pandas, Matplotlib, and PyTorch. The curriculum covers Python fundamentals, data structures, and object-oriented programming, providing a solid foundation for AI development.
Nanodegree Programme
The Nanodegree programme spans several months, offering in-depth learning through practical projects. Students apply their skills to real-world scenarios, such as creating image classifiers and working with neural networks. This approach ensures learners gain practical experience with AI tools and concepts, preparing them for careers in the field.
Career Support
Udacity provides robust career services to help students transition into AI careers. These include personalised project reviews, access to industry experts, and guidance on building a professional portfolio. The programme also offers insights into the latest AI trends, helping learners stay current in this ever-growing field.
Coursera’s AI for Everyone by Andrew Ng
This course aims to demystify AI for non-technical professionals, making it accessible to everyone. It provides a 360-degree overview of AI technologies, applications, and societal impact. Learners gain insights into AI’s potential and limitations, helping them identify opportunities within their own organisations.
Module Breakdown
The course covers AI fundamentals, machine learning concepts, and real-world applications. It explores topics such as data science workflows, AI project management, and the roles within AI teams. Learners also examine ethical considerations and potential pitfalls in AI implementation.
Real-World Examples
The course showcases practical Artificial Intelligence applications across various industries, including virtual assistants, self-driving cars, and healthcare. These examples illustrate how AI is transforming businesses and society, providing learners with a realistic view of AI’s capabilities and limitations.
Microsoft’s AI Fundamentals
Microsoft‘s AI Fundamentals course offers a special introduction to artificial intelligence concepts and Azure AI services. The programme is designed for both technical and non-technical learners, making it one of the best AI courses for beginners. It combines instructor-led training with online materials on the Microsoft Learn platform, providing a blended learning experience.
Azure AI Services
The course covers a range of Azure AI services, including Azure AI Vision, Azure AI Face detection, and Azure AI Language. Learners gain hands-on experience with these tools, exploring their capabilities in computer vision, natural language processing, and generative AI. This practical approach helps students understand how AI tools can be applied to real-world scenarios.
Certification Exam
Upon completing the course, learners can take the AI-900 Microsoft Azure AI Fundamentals exam. This certification verifies knowledge of AI concepts and Azure services, covering topics such as machine learning, computer vision, and natural language processing. The exam consists of 40-60 questions and has a passing score of 700 out of 1000, making it an achievable goal for those new to AI.
Nitin Konde
Intel’s AI Courses
Intel offers a range of AI courses, including Network Transformation and AI Fundamentals. These programmes cover topics such as SDN, NFV, and network acceleration technologies. The AI Essentials course provides a foundation for AI discovery conversations, making it one of the best AI courses for beginners.
Industry Applications
Intel’s courses explore AI applications across various sectors, including healthcare, transportation, and retail. Learners gain insights into how AI tools and generative AI are transforming industries. The courses also cover Intel’s network technology solutions for cloud, network, and edge applications.
Hands-on Labs
Practical experience is a key component of Intel’s AI courses. Students work with tools like the Intel Distribution of OpenVINO toolkit, learning to deploy computer vision capabilities in edge applications. The courses also include exercises on using Windows Machine Learning and optimising deep learning inference on edge devices.
Stanford University
The Stanford AI Graduate Certificate Program offers a structured learning experience with core and elective courses. Students start with a core course—either Artificial Intelligence: Principles and Techniques or Machine Learning—covering AI foundations, deep learning, and optimization. They can then choose electives like NLP with Deep Learning for chatbot and language models, Robotics for autonomous systems, Computer Vision for image recognition, and Deep Reinforcement Learning for AI-driven decision-making.
Real-World Examples
These courses have real-world applications in Google Translate, ChatGPT, Tesla’s self-driving cars, Boston Dynamics robots, facial recognition, medical imaging, and financial trading models. The program provides hands-on learning to apply AI in healthcare, finance, automation, and beyond.
End Note
The world of artificial intelligence is changing significantly, offering exciting opportunities for learning and growth. These free AI certification courses provide a solid foundation to understand and harness the power of AI technologies. So, there’s something for everyone looking to expand their knowledge in this field. These programmes not only equip learners with valuable skills but also have an influence on their career prospects in an increasingly AI-driven job market.
As you get onto your AI learning journey, remember that continuous learning is key in this field. To stay updated with the latest AI trends and insights, don’t forget to check out other AI-related articles at StartupTalky and follow the Instagram for quality content shared by the team. Finally, no matter who you are – a beginner or a seasoned professional, these courses offer a stepping stone to explore the fascinating world of artificial intelligence, helping you to stay ahead in an era where AI is causing a revolution in nearly every industry.
FAQ
How to get AI certified for free?
You can get AI certified for free by enrolling in online courses from platforms like :
- IBM
- AWS
- DeepLearning.AI
- Harvard
- Udacity
- Coursera
- Microsoft
- Intel’s
- Stanford
Is a certificate in AI worth it?
Yes, a certificate in AI can be worth it as it validates your skills, enhances your resume, and opens up opportunities in AI-driven fields. It can also increase your credibility and competitiveness in the job market.
Can I learn AI in 3 months?
Yes, you can complete AI certification courses in 3 months, as many programs are designed for short-term learning. However, achieving proficiency in AI may require ongoing practice beyond the course duration.
What are free AI courses with certificate?
Here are some free AI courses with certificates:
- AI For Everyone – Coursera (DeepLearning.AI)
- Machine Learning Crash Course – Google
- AI Fundamentals – IBM SkillsBuild
- AI For Beginners – Microsoft
- Generative AI Learning Path – Google Cloud
These courses cover AI basics, ML, NLP, and deep learning.
