Unlock the boundless potential of artificial intelligence with our comprehensive course, “Foundations of Artificial Intelligence.” Delve into the intricacies of AI through ten meticulously crafted modules that seamlessly guide you from the fundamentals to advanced applications. Immerse yourself in a captivating journey, exploring the realms of Mathematics for AI, Knowledge Representation, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, and Robotics. This course goes beyond the ordinary, offering a theoretical understanding that sets the stage for a profound grasp of AI concepts. Elevate your knowledge and stay at the forefront of this transformative field, where each module unfolds a new layer of understanding, empowering you to contribute to the evolving landscape of artificial intelligence.
Learning Outcomes:
- Grasp the fundamental principles of artificial intelligence.
- Develop a robust understanding of the mathematical frameworks supporting AI.
- Master the intricacies of knowledge representation in AI.
- Explore the realms of machine learning and its applications.
- Delve into the complexities of deep learning and its significance.
- Gain insights into the transformative fields of natural language processing, computer vision, and robotics.
Who is This Course For:
This course is tailored for individuals aspiring to carve a niche in the field of artificial intelligence. Ideal for:
- AI Enthusiasts
- Computer Science Graduates
- Data Scientists
- Engineers Seeking AI Expertise
- Researchers Exploring AI
- Technology Innovators
Certification:
Certificates can be obtained at an additional cost of £9.99 for PDF, £16.99 for Printed Hardcopy format and £24.99 for Both for Both PDF and Hardcopy Certificates.
Requirements
There are no academic entry requirements for this course, and it is open to students of all academic backgrounds.
Course Curriculum
| Module 01: Introduction to Artificial Intelligence | |||
| Introduction to Artificial Intelligence | 00:21:00 | ||
| Module 02: Mathematics for AI | |||
| Mathematics for AI | 00:17:00 | ||
| Module 03: Knowledge Representation in AI – Part 1 | |||
| Knowledge Representation in AI – Part 1 | 00:18:00 | ||
| Module 04: Knowledge Representation in AI – Part 2 | |||
| Knowledge Representation in AI – Part 2 | 00:16:00 | ||
| Module 05: Machine Learning – Part 1 | |||
| Machine Learning – Part 1 | 00:16:00 | ||
| Module 06: Machine Learning – Part 2 | |||
| Machine Learning – Part 2 | 00:15:00 | ||
| Module 07: Deep Learning | |||
| Deep Learning | 00:16:00 | ||
| Module 08: Natural Language Processing | |||
| Natural Language Processing | 00:22:00 | ||
| Module 09: Computer Vision | |||
| Computer Vision | 00:14:00 | ||
| Module 10: Robotics | |||
| Robotics | 00:18:00 | ||
| Module 11: Building AI Applications | |||
| Building AI Applications | 00:24:00 | ||
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