Why Choose this Training Course?
Artificial Intelligence (AI) stands at the forefront of innovation, revolutionizing industries, and reshaping the way we interact with technology. This course is designed to provide you with a comprehensive introduction to the fundamentals of AI, exploring its underlying principles, algorithms, and applications.
Throughout this course, you will embark on an exciting journey into the realm of AI, where you’ll gain insights into machine learning, neural networks, natural language processing, and much more. Whether you’re a seasoned professional looking to enhance your skills or a curious novice eager to dive into the world of AI, this course offers a solid foundation for understanding the core concepts and techniques driving AI innovation.
This training course will highlight the following:
- What Is AI
- AI Problem Solving
- Real World AI
- Machine Learning
- Neural Network
- AI Implications
What are the Goals?
Upon attending this training course, the participants will be able to:
- Participants will demonstrate proficiency in creating 3D models using various techniques such as polygon modeling, spline modeling, and modifier-based modeling.
- Learners will apply textures, materials, and shades to 3D models to enhance their visual appearance and realism.
- Students will understand different lighting techniques and render settings to achieve realistic lighting and photorealistic renders in 3D Max.
- Participants will gain basic animation skills, including key-framing, animation controllers, and rigging techniques for character animation.
- Learners will develop skills in scene setup, composition, and camera placement to create visually compelling 3D scenes and environments.
- Students will demonstrate proficiency in the complete 3D Max workflow, from project planning and asset creation to final rendering and presentation.
- Participants will develop problem-solving skills and the ability to troubleshoot common issues encountered during the 3D Max workflow.
- Learners will explore their creativity and develop their artistic vision through the creation of 3D artwork and projects.
- Students will compile a portfolio of 3D artwork and projects to showcase their skills and capabilities to potential employers or clients.
- Participants will understand the importance of continued learning and growth in the field of 3D design and animation, and be equipped with the skills to pursue further education or career opportunities in the industry.
Who is this Training Course for?
This training course is appropriate to the following:
- Students: Interested in pursuing careers in AI, data science, machine learning, or related fields.
- Professionals: Seeking to enhance their understanding of AI concepts and applications for career advancement or transitioning into AI-related roles.
- Researchers: Exploring fundamental principles and techniques in artificial intelligence for academic or industrial research.
- Entrepreneurs: Looking to leverage AI technologies to innovate and develop new products or solutions.
- Anyone: With a curiosity about AI and its impact on society, regardless of background or prior knowledge in the field.
How will this Training Course be Presented?
This Course is designed for computer teaching with the use of an Advanced Virtual Learning Platform in the comfort of any location of your choice. There will be an exercise, case studies, and real-life examples to help the participants use their knowledge to build their skills on each topic.
Module 1: Introduction to Artificial Intelligence
- History and Evolution of AI
- Definitions and Scope of AI
- Key Terminology and Concepts
Module 2: Problem Solving and Search Algorithms
- Problem Formulation
- Search Strategies (e.g., Breadth-First Search, Depth-First Search)
- Heuristic Search Techniques
Module 3: Knowledge Representation and Reasoning
- Propositional and Predicate Logic
- Semantic Networks and Frames
- Rule-Based Systems
Module 4: Machine Learning Basics
- Overview of Machine Learning
- Types of Machine Learning: Supervised, Unsupervised, Reinforcement Learning
- Feature Engineering
Module 5: Supervised Learning: Regression and Classification
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forests
Module 6: Unsupervised Learning: Clustering and Dimensionality Reduction
- K-Means Clustering
- Hierarchical Clustering
- Principal Component Analysis (PCA)
Module 7: Neural Networks and Deep Learning
- Introduction to Artificial Neural Networks
- Multilayer Perceptron (MLPs)
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
Module 8: Natural Language Processing (NLP)
- Text Processing and Tokenization
- Sentiment Analysis
- Named Entity Recognition
- Language Models (e.g., Word Embedding’s, Transformers)
Module 9: Computer Vision
- Image Processing Basics
- Object Detection
- Image Classification
- Image Segmentation
Module 10: Reinforcement Learning
- Markov Decision Processes (MDPs)
- Q-Learning
- Deep Q-Networks (DQN)
Module 11: AI Ethics and Bias
- Ethical Considerations in AI Development and Deployment
- Bias in AI Algorithms
- Fairness, Accountability, and Transparency
Module 12: AI Applications and Case Studies
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- Real-world Applications of AI in Various Industries
- Case Studies and Success Stories
- Emerging Trends and Future Directions
Session 1: 11:00-12:30 Dubai [UTC/GMT +4]
Break : 12:30 – 13:00 Dubai [UTC/GMT +4]
Session 2: 13:00 – 14:30 Dubai [UTC/GMT +4]
Certificate of Completion for delegates who attend and complete the course
COURSE REGISTRATION
Kindly email info@emaratic.com for registration or call +971 43 34 6009 for assistance
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