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AI for Beginners Free Course

Name: Introduction to Artificial Intelligence
Rating: 4.48 (22197 reviews)

Introduction to Artificial Intelligence

Updated with GenAI for 2026

4.48 Beginner level 3.0 learning hrs 216.9K+ Learners

Learn the fundamentals of Artificial Intelligence, including neural networks, natural language processing, and computer vision. Enroll in our AI for beginners free course and gain practical knowledge through real-world examples.

Instructor:

Dr. Abhinanda Sarkar

Learn in

English Español

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Skills you will gain

Fundamentals of Artificial Intelligence

Neural networks

Basics of Natural Language Processing (NLP)

Fundamentals of Computer Vision

Tasks involved in Computer Vision

What you'll learn

Grasp fundamental concepts of Artificial Intelligence.

Understand the basics of machine learning and neural networks.

Identify real-world applications of AI across industries.

Evaluate future trends in AI technology.

Key Highlights

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

About this course

This free Artificial Intelligence (AI) course provides a solid foundation in key AI concepts, enabling you to apply these skills in practical and real-world settings. By the end of the course, you'll be well-equipped to tackle Artificial Intelligence (AI) challenges across various industries, from building neural networks to implementing advanced computer vision techniques.

In this course, you’ll start with an overview of Artificial Intelligence and explore its impact across various industries. You’ll learn about neural networks, understanding how they connect to machine learning and biological neurons, and gain a solid understanding of deep neural networks. The course also covers Natural Language Processing (NLP), explaining its role in real-world applications like sentiment analysis and chatbots. You’ll study the basics of computer vision and its uses in image classification, segmentation, and video analysis. Finally, you’ll build on your knowledge with real-world examples of computer vision, such as face recognition and traffic analytics.

Stand out with an industry-recognized certificate

Start learning

10,000+ certificates claimed, get yours today!

Get noticed by top recruiters

Share on professional channels

Globally recognised

Land your dream job

Course outline

Fundamentals of Artificial Intelligence (AI) and Industry Domains

Define Artificial Intelligence (AI) and differentiate it from traditional algorithmic programming. Explore core AI domains including Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision (CV), analyzing their strategic deployment across modern industries.

Computer Vision (CV) Fundamentals: Classification and Segmentation

Master the foundational tasks of Computer Vision (CV). Extract actionable features from visual data to execute Image Classification, Object Detection, Semantic Segmentation, and continuous Video Analysis.

Artificial Neural Networks (ANN) and Deep Learning Architecture

Deconstruct the architecture of Artificial Neural Networks (ANN). Map the functional relationship between biological neurons and artificial perceptrons. Analyze multi-layered Deep Neural Networks (DNN) for complex Machine Learning feature extraction.

Natural Language Processing (NLP): Sentiment Analysis and Chatbots

Process and analyze human language data using Natural Language Processing (NLP). Implement industry-standard text analysis techniques, focusing on computational linguistics, automated Sentiment Analysis, and conversational AI architecture for Chatbots.

Applied Computer Vision: Facial Recognition and Traffic Analytics

Deploy applied Computer Vision models for real-world scenarios. Evaluate industry case studies including biometric authentication via Face Recognition, automated Image Classification, and real-time Video Traffic Analytics.

Generative AI, Large Language Models (LLMs), and Foundation Models

New

Transition from predictive Machine Learning to Generative AI frameworks. Explore the mathematical underpinnings of generative models. Leverage Large Language Models (LLMs) and foundation models to solve complex real-world content generation challenges.

Get access to the complete curriculum once you enroll in the course

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This course is ideal for

Absolute beginners wanting an AI overview.
Students exploring tech careers.
Business leaders seeking to understand AI capabilities.
Non-technical professionals looking to learn AI basics.

Introduction to Artificial Intelligence

4.48

3.0 Hours

Beginner

216.9K+ learners enrolled so far

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

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Trusted by 1 Crore+ Learners globally

4.6

4.89

4.94

4.7

Learner reviews of the Free Courses

4.48

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Amit Bisht

5.0

★★★★ ★

India

“The AI course was well-structured, with clear explanations and practical examples. It helped deepen my understanding of key concepts and applications in AI.”

The AI course provided a comprehensive understanding of core concepts, from machine learning to neural networks. The balance between theory and hands-on projects helped reinforce learning. The practical examples and real-world applications made complex topics more accessible. Overall, it was an engaging and insightful experience that significantly improved my knowledge and skills in AI.

Fachtur Rozi

4.0

★★★ ★ ☆

Indonesia

“Review: Introduction to Artificial Intelligence Training”

The Introduction to Artificial Intelligence (AI) Training provides a comprehensive entry point into the world of AI, suitable for beginners and those with basic technical knowledge. The course typically covers foundational concepts of AI, including machine learning, neural networks, natural language processing, and computer vision.

Nitheen Immanuvel

5.0

★★★★ ★

India

“Exceeded Expectations: Comprehensive AI Course”

I took an AI online class, and it exceeded my expectations. The course was well-structured, covering key topics like machine learning, neural networks, and NLP, with plenty of practical projects to apply what I learned. The instructors were knowledgeable, and the platform was user-friendly, offering high-quality video lectures and interactive quizzes. It provided a strong foundation in AI, making it ideal for beginners or anyone looking to upskill. Highly recommend for its value and engaging content!

Chitra Rajendra Purvant

5.0

★★★★ ★

India

“Advanced Certificate in AI Technologies”

The Advanced Certificate in AI Technologies is designed for professionals and enthusiasts seeking to deepen their knowledge and expertise in artificial intelligence. This program covers advanced AI concepts, including machine learning, deep learning, natural language processing, and computer vision.

RAJADURAI P

4.0

★★★ ★ ☆

India

“Acknowledging Strengths and Suggestions for Improvement”

This feedback acknowledges the strengths of the content while providing constructive suggestions for improvement, ensuring a balanced and helpful response.

Aneesh Murali

5.0

★★★★ ★

United Arab Emirates

“Introduction to Artificial Intelligence is Good for the Future”

Artificial Intelligence (AI) is a field of computer science focused on creating systems capable of performing tasks that typically require human intelligence. This includes tasks such as learning, reasoning, problem-solving, understanding natural language, and perception.

JAGADEEP S V KPRCAS-B.Com (IT)

5.0

★★★★ ★

India

“Useful for My Future and Gained Knowledge About AI”

It sounds like you might be asking for general feedback about AI. Here are a few points that might be relevant: 1. Accuracy and Reliability: AI systems, especially those involving machine learning, can sometimes produce inaccurate results if not properly trained or if they encounter data outside their training set. Continuous improvement and validation are crucial. 2. Bias and Fairness: AI can inadvertently perpetuate or amplify biases present in the data it was trained on. It's important for developers to actively work on identifying and mitigating biases to ensure fairness and inclusivity. 3. Transparency and Explainability: AI decisions can sometimes be opaque, making it difficult for users to understand how conclusions are reached. Improving transparency and making AI systems more explainable can help users trust and better utilize AI. 4. Ethical Considerations: The ethical implications of AI use, such as privacy concerns and the impact on jobs, are significant. Responsible development and deployment, considering these factors, are essential for positive societal impact. 5. User Experience: AI interactions should be designed to be intuitive and user-friendly. Ensuring that AI tools are accessible and easy to use enhances their effectiveness and user satisfaction. 6. Adaptability: AI systems need to be adaptable to changing conditions and new information. Continual learning and updates can help maintain their relevance and accuracy. These points reflect some common areas of focus in AI development and deployment. If you have specific aspects of AI you're curious about or want feedback on, let me know!

Sangu Harshavardhan

5.0

★★★★ ★

“Introduction to Artificial Intelligence”

This course has been learning for improvement and such categories like developing a code using AIML.

Ahmad Abdullah

5.0

★★★★ ★

United States

“Great Presentation from the Professor and Easy to Understand”

The ease of use of the course, user-friendly and the professor was very clear and easy to understand.

Smruthi S

5.0

★★★★ ★

India

“Artificial Intelligence and Neural Networks”

The course I got has helped me to have a better understanding of the subject. Way of explanation and teaching.

What our learners enjoyed the most

Skill & tools

60%

60% of learners found all the desired skills & tools

Our course instructor

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning

Artificial Intelligence Expert

1.1M+ Learners

36 Courses

Dr. Abhinanda Sarkar has B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He was a lecturer at Massachusetts Institute of Technology (MIT) and a research staff member at IBM. Post this he spent a decade at General Electric (GE). He has provided committee service for the University Grants Commission (UGC) of the Government of India, for infoDev – a World Bank program, and for the National Association of Software and Services Companies (NASSCOM). He is a recipient of the ISI Alumni Association Medal, an IBM Invention Achievement Award, and the Radhakrishan Mentor Award from GE India. He is a seasoned academician and has taught at Stanford, ISI Delhi, the Indian Institute of Management (IIM-Bangalore), and the Indian Institute of Science. Currently, he is a Full-Time Faculty at Great Lakes. He is Associate Dean at the MYRA School of Business where he teaches courses such as business analytics, data mining, marketing research, and risk management. He is also co-founder of OmiX Labs – a startup company dedicated to low-cost medical diagnostics and nucleic acid testing.

Frequently Asked Questions

Will I receive a certificate upon completing this free course?

Yes, upon successful completion of the course and payment of the certificate fee, you will receive a completion certificate that you can add to your resume.

Is this course free?

Yes, you may enroll in the course and access the course content for free. However, if you wish to obtain a certificate upon completion, a non-refundable fee is applicable.

Is this Introduction to AI course a certification course?

This Introduction to freeArtificial Intelligence course offers a certificate of completion, not a professional certification.

What will I learn in this Free AI Course for Beginners?

In this course, you’ll gain a solid foundation in artificial intelligence. You’ll learn about key AI concepts such as machine learning, neural networks, deep learning, and decision-making algorithms. Additionally, the course covers how AI is applied in real-world scenarios, such as healthcare, finance, and robotics, preparing you for further exploration in the field of AI.

Can I apply what I learn in this Introductory AI Course to real-world situations?

Yes, the course provides practical examples of AI applications in industries such as healthcare, finance, and e-commerce. You’ll learn how AI is used to solve real-world problems, helping you understand how to implement AI in various fields.

What AI topics are covered in this Beginner's AI Training ?

The course covers key AI topics including:

Fundamentals of Artificial Intelligence
Neural networks
Basics of Natural Language Processing (NLP)
Fundamentals of Computer Vision
Tasks involved in Computer Vision

Is this AI course suitable for beginners with no prior knowledge?

Yes, this course is designed specifically for beginners. You don't need any previous experience in AI or programming. The course starts with the basics and builds on those concepts step by step, making it easy to understand even if you are new to the field.

Will I have lifetime access to this AI Course for Beginners?

Yes. You will have lifetime access to this free online Artificial Intelligence course.

How long does this free AI course take to complete?

This free course includes around 3.75 hours of learning content. It’s self-paced, so you can take as much time as you need to fully grasp the concepts.

Is this free AI course self-paced?

Yes, this course is entirely self-paced. You can start at any time, go through the lessons at your own speed, and revisit the material as needed. It’s designed to fit into your schedule, making it ideal for anyone looking to learn AI at their convenience.

How do I enroll in this free AI course?

Search for the "Introduction to Artificial Intelligence" free course in the search bar present at the top corner of Great Learning Academy.
Register for the course through the Enroll Now button and start learning.

What will I be able to do after completing this AI Basics course?

After completing this course, you'll understand the core concepts of AI and how they can be applied in various industries. You will be able to discuss AI techniques such as machine learning and deep learning and understand how they can be used to solve problems and create intelligent systems.

What should I learn after finishing this free AI course?

After completing this course, you can dive deeper into specialized areas like machine learning, deep learning, or natural language processing (NLP). The course serves as a foundation for exploring more advanced topics and hands-on projects, allowing you to build on your skills.

What jobs can I get if I learn AI?

There are many jobs that demand that you learn Artificial Intelligence, such as:

AI Research Scientist

AI Programmer
Machine Learning Engineer
AI/Robotics Engineer
AI Product Manager
Data Scientist
AI Solutions Architect
Natural Language Processing Engineer
AI/Robotics Researcher
AI Embedded Systems Engineer

Who should take this free AI course?

This course is perfect for students, professionals, and anyone interested in AI. Whether you're just starting out or looking to upskill, this course is a great introduction to AI, machine learning, and their real-world applications. It’s also ideal for professionals wanting to explore AI's role in business and technology.

Why choose Great Learning for this free AI course?

By the end of this online Artificial Intelligence free course, you will be familiar with the fundamentals of AI, understand neural networks and deep neural networks, and know the basics of NLP and computer vision in detail through various examples.

Is there a limit on how many times I can take this free course?

No, there are no limits on the number of times you can attain this free Artificial Intelligence course.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can sign up for more than one free course offered by Great Learning Academy that efficiently assists your career growth.

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