Top 20 AI certifications for beginners

Why Choose an AI Certification? – Step-by-Step Benefits

Artificial Intelligence (AI) is the field of computer science that focuses on creating systems capable of performing tasks that normally require human intelligence.Thesetasksinclude understanding naturallanguage, recognizing images, solving problems, making decisions, and learning from data.

AI is not limited to robots — it's embedded in everyday technologies like voice assistants, recommendation systems, chatbots, self-driving cars, and even fraud detection tools. Let's see the benefits of choosing AI Certifications as your first step.

1. Build a Strong Foundation ( Core Concepts)

• Gain a solid understanding of core AI concepts like machine learning, deep learning, neural networks, and natural language processing.

2. Get Industry-Recognized Validation

• Certifications from trusted platforms (like Microsoft, Google, or IBM) validate your expertise and boost your credibility in the job market.

3. Stand Out in the Job Market

• In a competitive space, certified professionals are more likely to catch the attention of recruiters and hiring managers.

4. Stay Current with Evolving Tech

• AI is constantly evolving. Certifications keep you up to date with the latest tools, frameworks, and best practices.

5. Hands-On Learning Experience

• Many certification programs include real-world projects and labs, helping you apply your knowledge practically.

6. Boost Career Opportunities & Salary

• Certified AI professionals often command higher salaries and qualify for specialized roles like AI Engineer, ML Specialist, or Data Scientist.

7. Smooth Career Transition

• For professionals from non-AI backgrounds (e.g., software development, data analysis), certifications offer a structured path to switch into AI.

8. Resume & LinkedIn boost:

• An AI certification from a trusted platform (like Coursera, edX, Google, IBM, or Microsoft) adds credibility to your profile and helps you stand out to employers.

9. Gain Confidence and Credibility

• Completing a certification boosts your confidence and helps establish your authority when working on AI projects or collaborating with teams.

10. Stand out in Interviews:

• With the AI field growing rapidly, certified individuals have better chances of: Getting interviews or a plus point while giving interviews, Earning higher salaries, Joining top companies or startups many more.

AI is Trending Everywhere

AI Trends:

1. Investments and Market Size

The global AI market is projected to reach 1.2 trillion dollars by the end of 2025.It is expected to grow annually at a rate of approximately 26 percent.By 2030, AI is expected to contribute around 16 trillion dollars to the global GDP.Leading tech companies such as Microsoft, Nvidia, Oracle, and Snowflake are heavily investing in AI infrastructure, including hardware and software.

2. Enterprise Adoption and Workforce Impact

3. Global Competitive Landscape

AI Statistics:

AI Certification Data:

1. Employability and Skill Alignment

2. Workforce Readiness and Training Gaps

Comparison: Top AI Certifications

Best AI Certifications to Start Your Career 

Whether you are new to AI or upgrading your skills, or want a career in AI, these are some free and paid AI certification courses offered by different platforms. Check them out :

1. AI For Everyone – Andrew Ng (Coursera)

• This course is ideal for business professionals, managers, team leaders, policy-makers, and curious beginners who want to understand how AI impacts the modern world.
• It is tailored for non-technical audiences who want to leverage AI strategically in their field or organization without needing to write code.

• A strong conceptual understanding of what AI is (and isn't)
• Ability to differentiate between AI hype and real capabilities
• Strategic thinking around how to integrate AI into business workflows

• Helps you lead or support AI-powered business initiatives and decision-making.
• Lead AI transformation projects within their department or organization

• No coding, math, or engineering background is required
• Designed for absolute beginners and non-technical professionals

• Free to audit the entire course content, including videos and discussions. To earn a shareable certificate, you need a Coursera Plus subscription (~$25/month)

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2. Elements of AI – University of Helsinki

• Anyone curious about AI across all disciplines—students, educators, business professionals, public servants, and anyone without a tech background.
• It's especially useful for policy-makers, HR professionals, journalists, marketers, and educators looking to responsibly navigate a world shaped by AI.

• Deep understanding of the fundamental concepts of AI such as machine learning, algorithms, and neural networks, real-world problem-solving, ethics, and neural networks.

• Provides a solid understanding of AI’s societal impact and professional relevance.
• Adds a credible, globally recognized credential to your LinkedIn or resume

• Absolutely no coding, math, or technical background required.
• Designed for first-time learners.

• Completely free, includes full access to course materials, assignments, and quizzes.

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3. Microsoft Certified Azure AI Engineer Fundamentals (AI-900)

• This certification is designed for students, early-career professionals, and anyone exploring the Microsoft AI ecosystem who wants a solid understanding of AI fundamentals.
• It’s perfect for people aiming to work with AI-enabled tools on the Azure cloud platform or those planning to enter technical roles

• Understanding of core AI workloads Machine learning, computer vision, NLP, and responsible AI.
• Insights into how AI models are built, trained, evaluated, and deployed.
• Familiarity with Microsoft Azure AI services

• Entry point for Microsoft’s AI certification pathway or cloud-based AI careers.
• Builds foundational knowledge for roles such as AI/ML Developer, Cloud Support Engineer, or Business Analyst

• No formal programming or data science background required

• Course content is free.
• Certification exam (AI-900) costs $99 USD (~₹8,200 INR).

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4. Google AI – Learn with Google AI

• This platform is ideal for students, aspiring AI developers, data analysts, educators, and anyone interested in machine learning (ML) and artificial intelligence.

• Fundamental understanding of AI/ML fundamentals.
• Hands-on application of TensorFlow.
• Proficiency in Google AI tools and APIs is useful for production-level AI deployment

• Builds strong foundational skills for roles like ML Engineer, AI Developer, or Data Scientist
• Equips you with practical coding experience to work on real AI/ML projects

• Some prior experience with Python programming is highly recommended
• Comfort with basic algebra and statistics is helpful

• All course materials and exercises are completely free.

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5. MIT Introduction to Deep Learning

• This course is for university students, engineering graduates, and self-taught programmers who already have a solid foundation in Python and mathematics.

• Deep understanding of neural networks, including CNNs, RNNs, and transformers.
• Hands-on experience using TensorFlow and PyTorch frameworks.
• Practical knowledge of computer vision, natural language processing (NLP), and robotics applications

• Great stepping stone toward ML research and AI engineering.
• Recognized globally due to MIT’s academic reputation and the course’s rigorous content

• Strong foundation in Python programming.
• Knowledge of linear algebra, calculus, and probability is expected.
• Best suited for learners with some exposure to machine learning concepts or prior coursework in CS

• Completely Free, includes all lecture videos, slides, labs, and assignments at no charge

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6. Jetson AI Courses & Certifications – NVIDIA Developer

• These certifications are intended for developers, engineers, students, and educators looking to specialize in AI at the edge using NVIDIA Jetson hardware.
• Ideal for those working on robotics, IoT, drones, smart cameras, and embedded AI devices.

• Building and deploying deep learning models on Jetson devices (Nano, Xavier, Orin, etc.
• Proficiency with TensorRT, CUDA, and NVIDIA JetPack SDK.
• Real-world Edge AI applications like object detection, gesture recognition, autonomous navigation, and computer vision.
• Integration of AI with IoT and robotics platforms.

• Prepares learners for roles in Edge AI development, robotics engineering, and embedded AI system.
• Opens opportunities in industries such as automotive, healthcare, smart surveillance, and industrial automation

• Intermediate knowledge of Python programming and Linux OS
• Basic understanding of AI concepts and neural networks
• Experience with Jetson boards

• Free

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7. Harvard CS50's Introduction to Artificial Intelligence

• This course is designed for programmers, computer science students, and tech enthusiasts who are already comfortable with Python and want a structured, academic dive into AI.

• Understanding of core AI techniques like Search algorithms, optimization, machine learning, deep learning, game-playing AI.
• Hands-on debugging, data modeling, and AI logic building

• Equips learners for positions like AI developer, ML engineer, data analyst, or academic researcher
• Recognized globally as part of Harvard’s prestigious CS50 series

• Prior experience with Python programming is required.
• Some familiarity with algorithms, recursion, and data structures is helpful.
• Best suited for intermediate-level learners.

• Free to audit all course content.
• To receive a verified certificate, you have to pay ~$199 USD (approx. ₹16,500).

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8. Semrush Academy – How to Become an AI-Powered Marketer

• Targeted at digital marketers, SEO professionals, entrepreneurs, content creators, and marketing managers who want to leverage AI tools.
• No prior programming, math, or tech background needed.

• AI Tools in Marketing: Learn to use ChatGPT, Jasper, and other GenAI tools for content creation
• Prompt Engineering Basics: Understand how to craft AI prompts for better output
• AI in SEO and Campaigns: Learn automation techniques for keyword research, email writing, and campaign optimization

• Equips marketing professionals to stay competitive in the AI-powered digital economy.
• Supports career growth in AI-driven content marketing, SEO automation, and performance marketing

• 100% Free
• Includes video lessons, interactive tasks, and a certificate of completion

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9. IBM Applied AI Professional Certificate (Coursera)

• This professional certificate is tailored for absolute beginners, career switchers, and non-coders who want to break into the world of artificial intelligence.

• Foundational understanding of AI, its history, applications, and business use cases.
• Practical experience with IBM Watson, Watson Assistant, and IBM Cloud AI tools.
• Building and deploying AI-powered chatbots and virtual assistants.

• Prepares learners for entry-level roles in AI development, such as AI Specialist, Junior AI Developer, or AI Business Analyst.
• Offers hands-on experience with enterprise-grade AI tools

• No previous experience with coding, AI, or data science required.

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10. AI Programming with Python – Udacity

• This course is designed for aspiring AI professionals, developers, and students who want a deep technical foundation in AI.
• The course is hands-on, project-based, and includes personal mentorship, career coaching, and technical support, making it ideal for serious learners.

• Proficiency in Python programming, with a focus on AI and data handling.
• Mastery of core libraries like NumPy, Pandas, and Matplotlib.
• Foundational course for ML engineering and data science roles.
• Understanding of neural networks, how they work, and how to build one from scratch

• Equips you with the skills needed for entry-level roles such as AI Programmer, Junior Machine Learning Engineer, or Data Analyst.
• Access to Udacity’s career services, including resume review, LinkedIn profile optimization, and GitHub coaching.

• Basic knowledge of Python syntax and functions is required.
• Some familiarity with high school-level math (algebra and basic calculus) is helpful.
• No prior AI or ML experience is needed

• Approximate cost: $399/month, ₹60,000+ (varies; often discounted).
• Scholarships and discounts are available during promotions or through partner companies

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11. Artificial Intelligence A-Z™ – Udemy

• This course is perfect for absolute beginners, self-taught coders, and tech enthusiasts who want to quickly build hands-on AI projects using Python.
• The course is also useful for students, freelancers, and hobbyists interested in exploring how AI works.

• Fundamentals of AI logic, including how intelligent systems make decisions.
• Building agents that learn and adapt using reinforcement learning.
• Implementing Q-learning, deep Q-networks, and policy gradients.
• Fundamentals of AI logic, including how intelligent systems make decisions.

• Builds a practical, project-driven foundation for junior AI developer or AI-focused Python programmer roles
• Equips freelancers and students with portfolio-ready projects

• Basic Python skills are helpful.
• No math-heavy background needed

• Regular price: $84.99 USD (~₹7,000 INR) (depends on discount offers).

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12. Google Cloud Machine Learning Engineer Certification

• This certification is designed for experienced ML practitioners, data scientists, and cloud engineers.
• This is not a training course but a professional-level certification exam, so it's best for those who already have hands-on ML experience.

• Mastery of the end-to-end ML lifecycle: from data preparation to deployment.
• Designing scalable ML models using Vertex AI, BigQuery ML, and Cloud AI APIs.

• Positions you for roles in ML engineering, ML Ops, or cloud architecture.
• Validates your capability to work on an enterprise-scale AI/ML project.

• Solid experience with Python, ML, and Google Cloud tools.
• Recommended: 3+ years industry experience, including 1+ year in ML

• Certification exam fee: $200 USD (~₹16,500 INR)

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13. Stanford AI Certification (via Coursera – Andrew Ng’s ML Course)

• This iconic course is ideal for students, engineers, developers, and career switchers who want to deeply understand the mathematical and theoretical foundations of machine learning.

• Understanding of concepts of Supervised/unsupervised learning, regression, SVMs, and neural networks.
• Applications in robotics, healthcare, speech recognition, and recommendation engines.

• A highly respected global course that prepares you for ML research and development roles.
• Opens pathways to deeper specializations like DeepLearning.AI, TensorFlow, or PyTorch series.

• Some background in linear algebra, statistics, and basic calculus.
• No prior coding required to start

• Free to audit (includes full access to lectures, quizzes, and assignments)
• Verified certificate: $49 USD (~₹4,100 INR) via Coursera

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14. Deep Learning: AI TensorFlow Developer Certificate

• This certification is aimed at intermediate to advanced learners, especially those who want to validate their practical skills in building deep learning models using TensorFlow.

• Building and training neural networks for image, video, text, and time-series data.
• Mastery of TensorFlow, CNNs, NLP, time series, and model optimization.

• Positions you for technical roles like TensorFlow Developer, AI Engineer, or ML Specialist.
• Adds a globally recognized certification from Google and DeepLearning.AI to your resume.

• Strong experience with Python and NumPy, plus familiarity with data pipelines
• Solid understanding of machine learning fundamentals.

• Certification exam fee: $100 USD (~₹8,300 INR)

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15. Certified Artificial Intelligence Scientist (CAIS) – USAII®

• This certification is tailored for senior professionals, managers, consultants, and business leaders who want to lead AI transformation within their organizations.

• Strategic understanding of AI lifecycle management from ideation to implementation.
• Proficiency in AI frameworks, business intelligence, AI in enterprise systems, and change management.
• Application of AI in domains such as cybersecurity, RPA, finance, HR, marketing, and supply chain.

• Empowers professionals to lead AI adoption and innovation strategy within their companies.
• Enhances credibility for roles such as AI Director, Chief AI Officer, or Digital Transformation Consultant.
• Provides strategic insight that bridges the gap between business needs and AI implementation.

• 6+ years of professional experience recommended (tech or business).
• No deep coding or ML expertise required, but familiarity with business tech systems helps.

• Total cost: $898 USD (~₹74,000 INR)

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16. Artificial Intelligence Certification – ARTIBA (Artificial Intelligence Board of America)

• This globally recognized certification is created for CS/IT professionals, software developers, tech leads, data analysts, engineers, and technology managers.
• Ideal for Working professionals in tech (2+ years of experience), Graduates with a CS/IT degree aiming for applied AI roles, Tech managers preparing to lead AI-focused teams, Data professionals transitioning into machine learning or AI engineering

• The certification provides deep and well-rounded expertise in
• Understanding AI fundamentals, Machine Learning & Deep Learning, Natural Language Processing (NLP), AI Project Management, Neural Networks, etc.
• Tool Proficiency: Hands-on familiarity with Python, R, TensorFlow, Keras, and Scikit-learn.

• Offers a globally respected credential that boosts hiring potential for roles such as: AI Engineer, Machine Learning Developer, AI Consultant, Automation Architect
• Aligns with high-demand jobs requiring validated AI expertise.

• A Bachelor’s degree in Computer Science, IT, Engineering, or a related field, OR a minimum of 2 years of relevant work experience in tech, analytics, or software development.

• $625 USD (~₹52,000 INR)
• Includes: Access to all official learning resources, one attempt at the online proctored certification exam, a Digital badge, and a globally verifiable certificate.

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17. Google Professional Machine Learning Engineer

• This certification is built for experienced ML practitioners, data scientists, and engineers who design, build, and productionize ML models using Google Cloud Platform (GCP).
• It’s ideal for those working in enterprise environments where cloud infrastructure is essential.

• Machine Learning System Design: Creating scalable, reliable ML models and pipelines.
• Understanding Data Pipeline Management, Model Training and Evaluation, Production Deployment.
• Security & Responsible AI: Model fairness, accountability, and lifecycle management.
• Tool Proficiency: Vertex AI, BigQuery ML, AutoML, Kubeflow, TensorFlow, Scikit-learn.

• A prestigious, industry-recognized cloud certification for ML professionals
• Demonstrates ability to deploy end-to-end AI solutions in enterprise and production environments
• Strong value in cloud-native AI roles, such as ML Ops Engineer, Cloud AI Architect, or Applied Scientist

• Strong Python and SQL experience
• Knowledge of statistics, ML algorithms, and data preprocessing
• 1+ years of hands-on experience in ML (recommended)

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18. Cognitive Project Management for AI (CPMAI) -PMI-Aligned

• This certification is crafted for project managers, AI team leads, business analysts, and IT professionals who manage or oversee AI/ML initiatives.
• It's especially valuable for those involved in AI project scoping, lifecycle governance, and risk mitigation.

• Gain knowledge of AI Project Lifecycle Management,CPMAI Framework,Data Readiness & Governance,AI Risk Management & Model Validation.
• Stakeholder Communication: Translating technical AI work into business value.

• Empowers AI project leaders and managers to deliver successful, business-aligned AI projects.
• Bridges the gap between technical AI teams and business expectations.
• Highly valued in enterprise roles involving AI governance, strategy, and delivery oversight.

• Background in project management, AI strategy, or data science.
• Not a technical programming course—focuses on process, governance, and delivery.
• No prior AI coding experience required, but familiarity with AI concepts is helpful.

• $2,495 USD (~₹208,000 INR)
• Includes training sessions, certification exam, and digital badge

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19. ScholarHat AI Certification

• This certification is ideal for students, job seekers, and beginners who are curious about Artificial Intelligence and want to build a strong foundation—no prior technical experience is required.

• Core understanding of Artificial Intelligence concepts and real-world applications
• Practical knowledge of machine learning, deep learning, and natural language processing
• Hands-on experience with tools like Python, TensorFlow, and other AI libraries
• Data preprocessing, feature engineering, and model-building techniques
• Ability to build, train, and evaluate models for classification, regression, and clustering tasks
• Exposure to neural networks and deep learning architectures
• Awareness of ethical considerations in AI development
• Application of AI to real-world problems through project-based learning
• Familiarity with current AI research and trends
• Career readiness with certification-backed validation of AI skills

• 10 Weeks of Intensive Live Training
• Learn from Microsoft MVPs and industry experts
• Build real-world projects to strengthen practical skills
• Personalized career coaching and mentorship
• Resume and portfolio development support
• Job assistance and interview readiness

• Core AI frameworks: Python, TensorFlow, scikit-learn
• Enterprise applications of AI in finance, HR, cybersecurity, marketing, RPA, and supply chain
• Exposure to BI tools, enterprise AI systems, and AI-driven decision-making
• Insights into change management and AI adoption strategies

Career Impact

• Equips learners with the skills to launch careers in AI, even without a tech background
• Builds confidence to apply for entry-level AI and data roles
• Opens pathways into fields like AI research, machine learning engineering, data science, and business intelligence
• Provides recognized certification to validate AI competency

Prerequisites

• No technical background required
• Suitable for complete beginners in coding or AI
• Curiosity and willingness to learn are the only essentials

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20. Azure AI Engineer Certification Training | Scholarhat

Designed For:

This certification is designed for IT professionals, developers, and data practitioners aiming to specialize in building, deploying, and managing AI-powered solutions on the Microsoft Azure platform. It’s ideal for those preparing for the AI-102: Designing and Implementing an Azure AI Solution exam.

Skills You’ll Gain:

• Hands-on development using Azure Bot Services and Azure Machine Learning
• Mastery in AI-powered tools like LUIS, Azure ML Studio, and Azure Cognitive Search
• Building natural language models with Language Understanding (LUIS)
• Real-world experience through business-scenario-based projects
• Proficiency in NLP, Azure Cognitive Services, and AI model deployment
• Readiness for the AI-102 certification exam with mock tests and expert guidance
• Exposure to end-to-end AI solution development on Azure
• Confidence to handle real-world enterprise AI needs
• Career-aligned skills for roles such as AI Engineer, Data Scientist, and AI Solutions Architect

Azure AI Certification Course Key Features:

• 6 Weeks of Intensive Live Training
• Learn from certified experts and Microsoft MVPs
• Work on real-world projects with business relevance
• Access to career coaching and interview prep
• Resume and portfolio building guidance
• Job assistance and placement support
• Active mentorship and support via community channels like Discord

Tools and Technologies Covered:

• Programming: Python
• AI Tools: Azure AI, Azure Bot, Azure Search, Azure Vision, Azure Cognitive Services
• Development Tools: Visual Studio Code, GitHub, GitHub Copilot
• OpenAI and Copilot Integration
• Natural Language Processing (NLP)

Career Impact

• Become job-ready for Azure AI Engineer roles in industries like healthcare, finance, retail, and e-commerce
• Open doors to careers in Machine Learning, Data Science, and AI Architecture
• Boost earning potential with average salaries: India: ₹15,00,000 – ₹30,00,000 per annum, US: $100,000 – $150,000 per annum
• Strong job market with 35% YoY growth in Azure AI roles
• Over 3,200+ successful career transitions and high demand, with 78% job market relevance

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Comparison Of Certification: Choose the Best

Why learn AI in Today's World?

As we step further into a technology-driven future, AI skills are no longer optional—they're essential. Whether you're a student, job-seeker, or tech enthusiast, learning AI now means staying ahead in a world that's rapidly becoming automated and intelligent.

• Explosive Career Growth: AI-related job roles like Machine Learning Engineer and AI Specialist are among the fastest-growing careers worldwide.
• Cross-Industry Demand: From healthcare and finance to education and agriculture, AI is being integrated into nearly every industry.
• Higher Earning Potential: Certified AI professionals often earn significantly more than their non-AI counterparts.
• Real-World Impact: AI helps solve critical problems—like climate change modeling, personalized medicine, and smart cities—making your skills socially impactful.

Prerequisites for the AI certification

1. Basic Understanding of Mathematics:

• Linear algebra (vectors, matrices)
• Probability & statistics (mean, variance, probability distributions)
• Basic calculus (for understanding model optimization – optional in beginner courses)

2. Basic Programming Skills

• Writing simple programs
• Using Python (the most common language in AI/ML)

3. Basic Data Handling Skills

• CSV or Excel files
• Basic data cleaning and transformation
• Visualizing data using Python libraries like Matplotlib or Seaborn

4. Familiarity with Computer Basics

• How to install software and run scripts
• Use online tools like Google Colab or Jupyter Notebook

5. Logical & Analytical Thinking

• Problem-solving mindset
• Willingness to break down and analyze problems

Conclusion

AI is reshaping the technology; it is the best time to boost and build a career in AI by enrolling in certification courses. From foundational knowledge to hands-on projects, these courses are designed to build your confidence and prepare you for real-world AI roles. Remember, you don’t need to master everything at once. Start with the basics, stay consistent, and gradually expand your learning. Explore ScholarHat masterclasses for free to kick-start your career.