{"id":104926,"date":"2026-05-02T12:12:00","date_gmt":"2026-05-02T06:42:00","guid":{"rendered":"https:\/\/staging.nanoschool.in\/wp\/?post_type=product&#038;p=104926"},"modified":"2026-06-24T11:11:25","modified_gmt":"2026-06-24T05:41:25","slug":"intro-to-neural-networks-ai","status":"publish","type":"product","link":"https:\/\/staging.nanoschool.in\/wp\/course\/intro-to-neural-networks-ai\/","title":{"rendered":"Introduction to Neural Networks"},"content":{"rendered":"<div style=\"font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; line-height: 1.6; color: #2d3748; max-width: 900px; margin: 0 auto; padding: 40px 20px; background-color: #ffffff;\">\n<div style=\"display: grid; grid-template-columns: 1fr 2fr; gap: 1px; background-color: #e2e8f0; border: 1px solid #e2e8f0; border-radius: 8px; overflow: hidden; margin-bottom: 40px; box-shadow: 0 4px 6px rgba(0,0,0,0.05);\">\n<div style=\"background-color: #f7fafc; padding: 12px 20px; font-weight: bold; color: #2c5282;\">Attribute<\/div>\n<div style=\"background-color: #ffffff; padding: 12px 20px; font-weight: bold; color: #2c5282;\">Detail<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Format<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Online, self-paced course<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Level<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Basic \/ Beginner<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Duration<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">2\u20133 Weeks<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Certification<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">e-Certification<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Fee<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Free Course<\/div>\n<div style=\"background-color: #f7fafc; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Tools<\/div>\n<div style=\"background-color: #ffffff; padding: 10px 20px; border-top: 1px solid #e2e8f0;\">Neural Networks Concepts, Basic Python<\/div>\n<\/div>\n<div style=\"font-size: 24px; font-weight: bold; color: #2c5282; margin-bottom: 15px;\">About the Course<\/div>\n<div style=\"margin-bottom: 20px;\">The Introduction to Neural Networks course is a free, beginner-friendly self-paced program designed to introduce learners to the basic concepts of neural networks and how they form the foundation of modern artificial intelligence and deep learning.<\/div>\n<div style=\"margin-bottom: 30px;\">Learners will understand how neural networks are inspired by the human brain, how they process data, and how they are used to recognize patterns, make predictions, and solve complex problems. The course focuses on simple explanations of neurons, layers, inputs, outputs, and learning processes, making it ideal for beginners entering AI and machine learning.<\/div>\n<div style=\"background-color: #1a365d; color: white; padding: 30px; border-radius: 8px; margin-bottom: 40px;\">\n<div style=\"font-size: 22px; font-weight: bold; margin-bottom: 15px;\">Program Highlights<\/div>\n<div style=\"display: grid; grid-template-columns: 1fr 1fr; gap: 20px;\">\n<div style=\"font-size: 14px;\">\u2022 Free beginner-level neural networks course<\/div>\n<div style=\"font-size: 14px;\">\u2022 Online self-paced learning format<\/div>\n<div style=\"font-size: 14px;\">\u2022 Simple explanation of neural network concepts<\/div>\n<div style=\"font-size: 14px;\">\u2022 Covers neurons, layers, and basic learning process<\/div>\n<div style=\"font-size: 14px;\">\u2022 Real-world applications of neural networks<\/div>\n<div style=\"font-size: 14px;\">\u2022 Suitable for students and first-time learners<\/div>\n<div style=\"font-size: 14px;\">\u2022 e-Certification upon successful completion<\/div>\n<\/div>\n<\/div>\n<div style=\"font-size: 24px; font-weight: bold; color: #2c5282; margin-bottom: 20px;\">Course Curriculum<\/div>\n<div style=\"margin-bottom: 40px;\">\n<div style=\"border: 1px solid #e2e8f0; border-radius: 6px; padding: 20px; margin-bottom: 15px; background-color: #fcfcfc;\">\n<div style=\"font-weight: bold; color: #3182ce; margin-bottom: 10px; font-size: 18px;\">Module 1: Introduction to Neural Networks<\/div>\n<ul style=\"font-size: 14px; margin: 0; padding-left: 18px; color: #4a5568;\">\n<li>What are Neural Networks?<\/li>\n<li>History and Evolution of Neural Networks<\/li>\n<li>Neural Networks vs Machine Learning vs AI<\/li>\n<li>Applications of Neural Networks<\/li>\n<\/ul>\n<\/div>\n<div style=\"border: 1px solid #e2e8f0; border-radius: 6px; padding: 20px; margin-bottom: 15px; background-color: #fcfcfc;\">\n<div style=\"font-weight: bold; color: #3182ce; margin-bottom: 10px; font-size: 18px;\">Module 2: Basic Structure of Neural Networks<\/div>\n<ul style=\"font-size: 14px; margin: 0; padding-left: 18px; color: #4a5568;\">\n<li>Understanding Neurons and Connections<\/li>\n<li>Input Layer, Hidden Layers, and Output Layer<\/li>\n<li>Weights, Bias, and Activation Concepts<\/li>\n<li>How Data Flows Through a Network<\/li>\n<\/ul>\n<\/div>\n<div style=\"border: 1px solid #e2e8f0; border-radius: 6px; padding: 20px; margin-bottom: 15px; background-color: #fcfcfc;\">\n<div style=\"font-weight: bold; color: #3182ce; margin-bottom: 10px; font-size: 18px;\">Module 3: How Neural Networks Learn<\/div>\n<ul style=\"font-size: 14px; margin: 0; padding-left: 18px; color: #4a5568;\">\n<li>Training a Neural Network<\/li>\n<li>Introduction to Forward Pass and Learning Process<\/li>\n<li>Error, Loss, and Basic Optimization Idea<\/li>\n<li>Simple Understanding of Model Improvement<\/li>\n<\/ul>\n<\/div>\n<div style=\"border: 1px solid #e2e8f0; border-radius: 6px; padding: 20px; margin-bottom: 15px; background-color: #fcfcfc;\">\n<div style=\"font-weight: bold; color: #3182ce; margin-bottom: 10px; font-size: 18px;\">Module 4: Types of Neural Networks<\/div>\n<ul style=\"font-size: 14px; margin: 0; padding-left: 18px; color: #4a5568;\">\n<li>Introduction to Different Neural Network Types<\/li>\n<li>Feedforward Neural Networks<\/li>\n<li>Basic Idea of Deep Learning<\/li>\n<li>Overview of Real-World Neural Network Models<\/li>\n<\/ul>\n<\/div>\n<div style=\"border: 1px solid #e2e8f0; border-radius: 6px; padding: 20px; margin-bottom: 15px; background-color: #fcfcfc;\">\n<div style=\"font-weight: bold; color: #3182ce; margin-bottom: 10px; font-size: 18px;\">Module 5: Applications and Next Steps<\/div>\n<ul style=\"font-size: 14px; margin: 0; padding-left: 18px; color: #4a5568;\">\n<li>Neural Networks in Image, Text, and Speech Processing<\/li>\n<li>AI Applications in Healthcare, Finance, and Technology<\/li>\n<li>Introduction to Deep Learning Pathways<\/li>\n<li>Mini Learning Activity \/ Concept-Based Practice<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<div style=\"background-color: #f7fafc; border-radius: 8px; padding: 30px; margin-bottom: 40px;\">\n<div style=\"font-size: 20px; font-weight: bold; color: #2c5282; margin-bottom: 15px;\">Tools, Techniques, or Platforms Covered<\/div>\n<div style=\"display: flex; flex-wrap: wrap; gap: 10px;\"><span style=\"background: white; padding: 5px 15px; border: 1px solid #cbd5e0; border-radius: 20px; font-size: 13px;\">Neural Networks<\/span><br \/>\n<span style=\"background: white; padding: 5px 15px; border: 1px solid #cbd5e0; border-radius: 20px; font-size: 13px;\">Deep Learning Basics<\/span><br \/>\n<span style=\"background: white; padding: 5px 15px; border: 1px solid #cbd5e0; border-radius: 20px; font-size: 13px;\">Machine Learning Concepts<\/span><br \/>\n<span style=\"background: white; padding: 5px 15px; border: 1px solid #cbd5e0; border-radius: 20px; font-size: 13px;\">Data Patterns<\/span><br \/>\n<span style=\"background: white; padding: 5px 15px; border: 1px solid #cbd5e0; border-radius: 20px; font-size: 13px;\">Basic Python<\/span><\/div>\n<\/div>\n<div style=\"font-size: 24px; font-weight: bold; color: #2c5282; margin-bottom: 15px;\">Real-World Applications<\/div>\n<div style=\"margin-bottom: 30px;\">\n<ul style=\"padding-left: 20px; margin-top: 10px;\">\n<li>Understanding how image recognition systems work<\/li>\n<li>Exploring AI in speech recognition and chatbots<\/li>\n<li>Learning how recommendation systems use neural networks<\/li>\n<li>Applying neural networks in healthcare and finance<\/li>\n<li>Preparing for advanced deep learning and AI courses<\/li>\n<\/ul>\n<\/div>\n<div style=\"font-size: 24px; font-weight: bold; color: #2c5282; margin-bottom: 15px;\">Who Should Attend &amp; Prerequisites<\/div>\n<div style=\"margin-bottom: 30px;\">\n<ul style=\"padding-left: 20px; margin-top: 10px;\">\n<li>This course is suitable for students, beginners, freshers, and professionals who want to understand neural networks and their role in artificial intelligence.<\/li>\n<li>It is also useful for learners from engineering, computer science, data science, mathematics, and non-technical backgrounds interested in AI.<\/li>\n<\/ul>\n<p><strong>Prerequisites:<\/strong> No prior knowledge of neural networks is required. Basic understanding of computers and interest in AI or machine learning is sufficient.<\/p>\n<\/div>\n<div style=\"font-size: 24px; font-weight: bold; color: #2c5282; margin-bottom: 20px;\">Frequently Asked Questions<\/div>\n<div style=\"margin-bottom: 40px;\">\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">1. Is this Introduction to Neural Networks course free?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Yes. This is a free online self-paced course designed for beginners.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">2. Do I need coding knowledge to learn neural networks?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">No. This course focuses on basic concepts and does not require prior coding knowledge.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">3. What will I learn in this course?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">You will learn the basics of neural networks, including neurons, layers, training, learning processes, and real-world applications.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">4. Who can join this course?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Students, beginners, and professionals from any background interested in AI can join.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">5. Will I receive a certificate?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Yes. Learners receive an e-Certification after completing the course.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">6. Is this course suitable for complete beginners?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Yes. The course is designed for complete beginners and explains neural network concepts in a simple, step-by-step manner.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">7. What is the duration of this course?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">The Introduction to Neural Networks course is designed as a 2\u20133 week online self-paced course.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">8. Does this course cover deep learning basics?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Yes. The course introduces the basic idea of deep learning and explains how neural networks form an important foundation for modern deep learning systems.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">9. Is this course useful before learning advanced AI?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">Yes. This course helps learners build a strong foundation before moving into advanced artificial intelligence, machine learning, and deep learning topics.<\/div>\n<\/div>\n<div style=\"margin-bottom: 20px;\">\n<div style=\"font-weight: bold; color: #2d3748;\">10. What makes this neural networks course beginner-friendly?<\/div>\n<div style=\"color: #4a5568; font-size: 15px;\">The course explains neurons, layers, inputs, outputs, training, and learning processes using simple language and real-world examples, without requiring advanced mathematics or coding knowledge.<\/div>\n<\/div>\n<\/div>\n<div style=\"margin-bottom: 30px; font-size: 15px; color: #2d3748;\">The Introduction to Neural Networks course provides a simple and structured foundation in neural network concepts, helping learners understand how modern AI systems learn from data and make intelligent decisions. It is an ideal starting point for further learning in deep learning and advanced artificial intelligence.<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Fundamentals of neural networks, perceptrons, activation functions, and network architectures.<br \/>\nTraining neural networks using backpropagation, basic deep learning concepts, and real-world applications.<\/p>\n","protected":false},"featured_media":104930,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_members_access_role":[],"_members_access_error":""},"product_brand":[9487],"product_cat":[4657],"product_tag":[],"class_list":["post-104926","product","type-product","status-publish","has-post-thumbnail","product_brand-nstc","product_cat-artificial-intelligence","post-wrapper","thrv_wrapper","first","instock","sale","downloadable","virtual","taxable","purchasable","product-type-simple"],"acf":[],"_links":{"self":[{"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/product\/104926","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/comments?post=104926"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/media\/104930"}],"wp:attachment":[{"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/media?parent=104926"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/product_brand?post=104926"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/product_cat?post=104926"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/staging.nanoschool.in\/wp\/wp-json\/wp\/v2\/product_tag?post=104926"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}