10+ Best AI Courses with Certificates (Free and Paid) in 2024

Dive into the best AI courses of 2024! Get certified, boost your skills, and discover job opportunities tailored for you.

Right now, the demand for AI skills is at an all-time high. It is changing the job market across various industries. The Zdnet report says 66% of leaders will not hire someone without AI skills and 71% of executives said they would hire candidates with AI expertise over those with actual experience. This clearly shows that AI is becoming essential for career growth.

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Certifications as a whole serve as an important asset for growth. They validate the expertise and also signal the employers a commitment to professional development. With many candidates with similar backgrounds, having certification can set them apart, obviously leading to better opportunities.

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When considering educational roadmaps in AI, students often face the choice between courses, free or paid, certificates, etc.

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Free: It can help you with foundational knowledge and is ideal for beginners.

Paid: Are for more comprehensive training and recognized credentials.

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In this blog post, we will take a look at some top AI courses that also provide certification.

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Let’s dive in.

1. AI For Everyone: Coursera

Instructor & Platform: Andrew Ng, Coursera

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A simple yet beginner-friendly introduction to AI. The course gives a picture of AI, including its societal impact, business applications, and how to navigate AI projects without needing a technical background.

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It's crafted for absolute beginners, including those in non-technical roles who are curious about AI's potential.

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Pros & Cons: The course's greatest strength is its simplicity. Andrew Ng delivers content that's easy to grasp, making it an ideal starting point.

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However, for those looking to dive deep into the technical aspects, "AI for Everyone" might feel too basic. It’s a course about understanding AI and not building it.

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Pricing: Some Coursera’s courses are free to audit, but to obtain a certification you may need to pay some fee.

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2. Deep Learning Specialization

Instructor and Platform: Andrew Ng, Younes Bensouda Mourri, and Kian Katanforoosh. Coursera.

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It is not an entry-level AI course; this specialization is for those who have a basic understanding of programming and are ready to go deep into neural networks and projects related to them. Anyone who enjoys a project-based learning style, this is a perfect course, as you will work through some real world projects using Python and TensorFlow.

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Pros & Cons: One of the biggest advantages is the specialization's comprehensiveness. The course provides a solid foundation in deep learning, supported by practical exercises and real-world projects.

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However, it’s demanding; the time and effort required can be significant, making it less suitable for casual learners.

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Best for: Those serious about mastering deep learning and pursuing a technical AI career path.

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Must Read: A Step-by-Step Guide to land a job in AI without a degree in 2024

3. Elements of AI

Instructor: University of Helsinki

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"Elements of AI" is a unique course that gives a small introduction to the world of AI. This course aims to make AI education accessible to everyone, regardless of technical background. This is somewhat similar to "AI for everyone" but the ways concepts are shared are engaging.

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Pros & Cons: The course is free and self-paced, making it an excellent option for those who want to learn at their own rhythm.

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However, the content is more conceptual, so it may not fully satisfy those seeking deep technical skills.

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Highlights: The interactive exercises, quizzes, and straightforward explanations are the highlights. The course also awards a certificate upon completion, which adds credibility to your AI knowledge.

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Pricing: entirely free, including certification.

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4. AI Programming with Python

Platform: Udacity

Prerequisites: Elementary algebra and Basic Python

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This course takes a deep dive into the technical aspects of AI and focusing on building and programming AI models using Python. It covers crucial AI topics such as machine learning, neural networks, and the use of popular frameworks like PyTorch and NumPy.

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Pros & Cons: One of the major pros is the course's hands-on approach with industry projects and mentors guiding you throughout.

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On the downside, it requires a solid time commitment, not for those with limited availability.

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Who Is It For? Ideal for intermediate learners who have foundational knowledge of programming and want to delve deeper into AI development.

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Pricing: Paid, with flexible payment options and scholarship opportunities.

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5. AI for Business (Wharton Online)

Platform: Wharton Online

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This course is tailored for business professionals. It explores AI's impact on business strategy and operations. It helps learners understand how AI can drive value in various business contexts.

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Pros & Cons: The content is concise and highly relevant for executives, but those looking for technical depth might find it lacking.

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Who Is It For? Business leaders, executives, and managers who want to integrate AI into their strategies.

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Pricing: Paid-$599, with various enrollment options and certificates covered in this 4-week course.

6. Google AI’s Machine Learning Crash Course

Platform: Google AI

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This free crash course by Google AI is a quick and practical introduction to ML. It covers core ML concepts, including supervised learning, neural networks, and loss functions, with hands-on TensorFlow exercises.

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Pros & Cons: The biggest advantage is its focus on practical ML skills through exercises. However, it assumes a basic understanding of programming and math.

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Who Is It For? Developers, data enthusiasts, and tech professionals looking to get a quick start in machine learning.

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Highlights: Practical exercises, TensorFlow tutorials, and Google's industry insights make this course stand out.

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Pricing: Completely free.

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7. Professional Certificate in Computer Science for AI

Platform: Harvard Online

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This certificate program gives a computer science foundation and focuses on AI fundamentals. It’s designed for those who want an academic-level understanding of AI while gaining a credible Harvard certificate.

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Pros & Cons: It’s thorough and prestigious, but the academic depth may be demanding for some.

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Who Is It For? Aspiring AI professionals, computer science students, and those who want a respected certificate in AI.

Pricing: Paid-$518, with a premium cost reflective of Harvard’s reputation.

8. Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT

Platform: Udemy

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This Udemy course provides a hands-on journey into AI by guiding learners through building 7 unique AI projects, including those focused on LLMs and ChatGPT. It’s a practical course designed to engage learners from the get-go.

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Pros & Cons: The practical project-based approach is a highlight, but it may feel fast-paced for beginners.

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Who Is It For? Beginners to intermediate learners interested in a project-driven AI course.

Pricing: affordable, with frequent discounts available.

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9. Introduction to TensorFlow for Artificial Intelligence

Instructor and Platform: Laurence Moroney. Coursera

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This course is a specific introduction to Tensorflow, which is one of the most popular AI frameworks. It's geared towards those who want to understand the basics of AI model-building using TensorFlow.

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Pros & Cons: The course is concise and to the point, perfect for TensorFlow beginners. However, it doesn’t dive deep into advanced AI topics.

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Who Is It For? Beginner to intermediate learners wanting a focused introduction to TensorFlow.

Pricing: Free to audit, with a paid certificate option.

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10. IBM AI Developer Professional Certificate

Platform: Coursera

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This professional certificate by IBM covers essential AI topics, including machine learning, deep learning, and data visualization using IBM’s Watson.

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Pros & Cons: A comprehensive program with hands-on labs. Some may find the focus on IBM tools limiting if they prefer more generalized platforms.

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Who Is It For? Aspiring AI developers and those interested in IBM’s AI ecosystem.

Pricing: Paid, but financial aid options are available.

11. Introduction to Generative AI Learning Path

Platform: Google Cloud Skills Boost

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A beginner’s pathway to understanding generative AI. This course from Google covers the basics of AI models and focuses particularly on generative applications like image and text generation.

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Pros & Cons: Short and focused, it’s ideal for beginners, but advanced learners may find it lacking depth.

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Who Is It For? For beginners curious about generative AI’s capabilities.

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Highlights: Tutorials on image and text generation, practical tasks, and Google Cloud insights.

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Pricing: Free.

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13. Professional Certificate Program in Machine Learning & Artificial Intelligence (MIT)

Platform: MIT Professional Education

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This professional certificate is a prestigious program that dives deep into machine learning and AI, blending theory and application. It’s designed for professionals aiming to advance their careers with MIT-level knowledge. It is best for serious learners only who want to advance in AI.

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Pros & Cons: Top-tier content and recognized certification, but it's a significant investment in terms of time and cost.

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Who Is It For? Professionals in technical fields who are looking for a deep dive into machine learning and AI.

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Pricing: Premium pricing due to its professional nature. Can range from $10k - $20K excluding the certificate costs.

Final Thoughts

So here we are. This is just a small list of some good AI-related certificate courses you can do. But remember that lifelong learning is the only way to stay relevant in this industry. With AI evolving at an insane rate, it is very important to keep yourself updated on the latest trends and technologies.

We encourage you to explore free trials or introductory modules offered by many platforms. This will help you check the quality of content in the course before making any financial commitments.

Unlock your potential in AI! Sign up on DataTeams.ai today to connect with top employers and access tailored job opportunities.

Happy learning.

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