Machine Learning, Neural Networks & AI Projects
Explore artificial intelligence through real-world applications, project cycles, machine learning, neural networks, computer vision, NLP, and responsible AI.
Dhaval Kesaria
Principal Immersive Technology Engineer & Technical Educator
Here’s what you will learn?
- Identify and explain real-world applications of AI in smart cities and smart homes.
- Differentiate between the three major AI domains: Data Science, Computer Vision, and Natural Language Processing (NLP).
- Explain how AI can support the Sustainable Development Goals (SDGs) and identify its potential social and technological impact.
- Identify ethical issues in AI, including bias, future job-market changes, and moral dilemmas related to technology.
- Define an AI problem using the 4Ws Problem Canvas (Who, What, Where, and Why) and identify the key stakeholders affected by the problem.
This Course Includes
- Recorded Lessons: 12
- Recorded Hours: 6hr 35min
- Certificate of completion
- Access on Mobile
Course Description
Course Content
12 Lessons | 6hr 35min
About the instructor
Dhaval Kesaria
Principal Immersive Technology Engineer & Technical Educator
Dhaval Kesaria (DK) is a technology professional, Unity, AI & XR specialist, and mentor with 12+ years of software development experience.
Frequently Asked Questions
This course introduces students to AI foundations, machine learning, data exploration, neural networks, computer vision, NLP, AI ethics, and the AI Project Cycle.
Yes. The curriculum is specifically designed for Grade 9 students.
Students explore the stages of problem scoping, data acquisition, data exploration, modelling, and evaluation.
The course introduces supervised and unsupervised learning, classification, clustering, decision trees, model selection, and evaluation.
Yes. Students learn about neural network structures, hidden layers, architecture types, and how neural networks compare with human intelligence.
(4.7)
6hr 35min