Masterclass e-Certificate in Artificial Intelligence, Machine Learning and AR/VR

1. Foundations of Machine Learning (2 hours)

• Definition of ML and its importance
• Types of machine learning: Supervised, Unsupervised, and Reinforcement learning
• Steps in the ML workflow: Data collection, preprocessing, model training, testing
• Bias-variance trade-off, overfitting, underfitting

2. Supervised Learning Algorithms (3 hours)

• Linear Regression and Logistic Regression
• Decision Trees, Random Forest, and Support Vector Machines (SVM)
• Hands-on session: Implementing classification and regression models using Scikit-learn

3. Unsupervised Learning and Clustering (2 hours)

• K-means Clustering, Hierarchical Clustering, DBSCAN
• Dimensionality Reduction: PCA, t-SNE
• Hands-on session: Clustering tasks and visualizing high-dimensional data using Python

4. Reinforcement Learning (2 hours)

• Introduction to reinforcement learning
• Markov Decision Processes (MDP)
• Q-learning, Deep Q Networks (DQN)
• Hands-on: Building a simple reinforcement learning model (e.g., grid-world problem)

5. Evaluation and Hyperparameter Tuning (1 hour)

• Model evaluation metrics: Accuracy, Precision, Recall, F1-Score, ROC, AUC
• Hyperparameter tuning using Grid Search and Random Search
• Cross-validation techniques
• Hands-on: Tuning hyperparameters for ML models using GridSearchCV

1. What is Augmented Reality? (2 hours)

• Definition and concepts of AR
• History and applications of AR in different industries (Retail, Healthcare, Education)
• AR vs. Virtual Reality (VR): Differences and use cases
• Types of AR: Marker-based, Markerless, and Projection-based AR

2. AR Development Tools and Platforms (2 hours)

• Introduction to AR development platforms: ARKit (iOS), ARCore (Android), Unity, Vuforia
• Setting up AR development environments
• Hands-on: Building a basic AR app using Unity and Vuforia (simple marker-based AR)

3. AR Development Tools and Platforms (2 hours)

• Interaction techniques in AR: Gesture recognition, voice commands, touch, gaze tracking
• Design considerations for AR interfaces: Usability and user experience (UX)
• Hands-on: Implementing simple user interactions (object manipulation, rotation)

4. Applications and Future of AR (1 hour)

• Emerging trends and future directions in AR technology
• Industry applications: Retail, Real Estate, Gaming, Education
• Challenges in AR development: Performance, latency, user adoption

1. What is Virtual Reality? (2 hours)

• Definition and concepts of VR
• History and applications of VR (Gaming, Training, Simulation)
• Differences between VR and AR
• Types of VR: Fully immersive, Non-immersive, and Semi-immersive

2. VR Development Tools and Platforms (2 hours)

• Introduction to VR development platforms: Unity3D, Unreal Engine, Oculus SDK, HTC Vive SDK
• Setting up VR development environments
• Hands-on: Building a simple VR experience using Unity (e.g., creating an interactive 3D environment)

3. VR Hardware and Interaction (2 hours)

• VR Hardware: Headsets, Controllers, Tracking systems (Oculus, HTC Vive, PlayStation VR)
• Interaction techniques in VR: Hand controllers, motion tracking, haptic feedback
• Hands-on: Building basic interactions (e.g., object picking, virtual navigation) in Unity

5. Applications and Future of VR (1 hour)

• VR in various industries: Healthcare, Education, Architecture, Entertainment
• Future trends: AI in VR, Social VR, VR for remote collaboration
• Challenges in VR development: Motion sickness, hardware limitations

1. AI and ML in AR/VR (3 hours)

• Using AI and ML to enhance AR/VR experiences
• Computer Vision for object recognition and tracking in AR
• AI-driven content generation in VR (procedural content generation, AI NPCs)
• Hands-on: Building an AI-based AR or VR application (e.g., using AI for object recognition or scene understanding)

2. Creating Immersive Experiences with AI/ML (3 hours)

• AI for personalization in AR/VR environments
• Using machine learning for adaptive storytelling in VR
• Case studies: AI-powered AR navigation systems, VR training simulators using ML
• Hands-on: Creating an adaptive AR/VR experience using AI-driven decisions

1. Emerging Trends in AI, ML, and AR/VR (2 hours)

• AI and ML's evolving role in AR/VR
• XR (Extended Reality) technologies: XR, MR, and their convergence
• The role of 5G in enhancing AR/VR experiences
• Future challenges: Privacy, security, and ethics in immersive technologies

• Mid-course Quiz to evaluate understanding of AI/ML concepts
• Final Project: Develop a small AR/VR application with integrated AI/ML features (e.g., an AI-driven interactive VR environment or AR object recognition)
• Certification awarded upon successful completion of the course and final project submission.