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Artificial Intelligence 18 - 24 Week Certification Course
Learn From Industry Experts
* Only Limited Slots Per Batch
* No Prior Coding Experience Required
Join Our Upcoming Masterclass, For Free !
Join Our Upcoming Masterclass, For Free !
KEY FEATURES
Live Classes
18 - 24 Weeks
Lab Support
For Practicals
Industry Expert
Learn From Top Industry Expert
Live Projects
Work On Capstone Projects
Overview of this Certification Course
This Artificial Intelligence course is a comprehensive and forward-looking program designed to provide students with a deep understanding of artificial intelligence, its applications, and its transformative potential across various industries. This course offers a holistic view of AI, covering both foundational concepts and advanced topics, making it suitable for individuals with varying levels of AI expertise.
Prerequisites of this Course
- No prior experience in AI is required
- Basic understanding of programming (Python preferred) and mathematics (linear algebra and calculus) is beneficial.
Course objectives
- To introduce the fundamental principles of artificial intelligence.
- To explore the various subfields of AI, including machine learning, natural language processing, computer vision, and robotics.
- To equip students with hands-on skills to design and implement AI algorithms and systems.
- To examine the ethical and societal implications of AI technologies.
- To encourage innovation and creative thinking in AI applications.
Who can apply?
- Students who want to explore AI and its applications as part of their academic studies.
- Professionals who wish to enhance their knowledge and skills in AI to stay competitive in their careers or transition into AI-related roles.
- Programmers and Developers, Individuals with programming experience, especially in Python, who want to delve into AI development.
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Skills You Learn From this Course
Fundamental AI Concepts
Machine Learning Skills
Deep Learning and Neural Networks
Natural Language Processing (NLP)
Computer Vision
And Many More...
Course Curriculum
- Historical perspective and evolution of AI.
- Key terminologies and definitions. ‘
- The AI problem-solving approach.
- Supervised, unsupervised, and reinforcement learning.
- Feature engineering and model selection.
- Evaluation and validation of machine learning models.
- Neural network architecture and training.
- Convolutional Neural Networks (CNN) for image analysis.
- Recurrent Neural Networks (RNN) for sequential data.
- Text preprocessing and tokenization.
- Sentiment analysis.
- Language modeling and machine translation.
- Image preprocessing and feature extraction.
- Object detection and image classification.
- Image segmentation and face recognition.
- Introduction to robotics and control systems.
- Path planning and navigation.
- Human-robot interaction and AI in robotics.
- Discussion on AI ethics and responsible AI.
- Bias and fairness in AI algorithms.
- Privacy and security concerns in AI.
- Real-world case studies showcasing AI applications in healthcare, finance, autonomous vehicles, and more.
- Guest lectures from industry experts.
- Students will engage in hands-on AI projects, applying their knowledge to solve practical problems.
- Project topics may range from developing AI chatbots to creating image recognition systems.
- Exploration of cutting-edge AI technologies such as reinforcement learning, generative adversarial networks (GANs), and quantum AI.
- In the final stage of the course, students will work on a capstone project, demonstrating their proficiency in AI by tackling a complex real-world problem.
- Continuous assessment through quizzes, assignments, and project submissions. Final examination. Evaluation of the capstone project.
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*Initial one-to-one consultation, Health & Fitness Assasments Bespoke training program planing, Custom Nutrition plan & recipes. Weekly Progress Reviews