Dive into the most advanced realms of artificial intelligence with our comprehensive 14-week program. Led by specialized experts in deep learning, quantum computing, and robotics, this cutting-edge program equips you with the knowledge and skills to work with the latest AI technologies and research developments.
The AI Frontiers program offers an intensive exploration of advanced AI technologies, from generative models to quantum machine learning. Through carefully curated modules taught by domain experts, you'll gain hands-on experience with cutting-edge AI applications and research methodologies. The program combines theoretical depth with practical implementation, culminating in a research-oriented capstone project. Each module is led by specialized trainers, including deep learning experts, NLP researchers, robotics specialists, and quantum computing researchers, ensuring you learn directly from professionals at the forefront of AI innovation. The curriculum emphasizes both theoretical understanding and practical application, preparing you for advanced research and development roles in AI.
Advanced Deep Learning Focus: Comprehensive coverage of GANs, advanced CNN architectures, and transformers with 32 hours of hands-on practice in cutting-edge architectures.
Specialized AI Domains: Deep dive into advanced NLP, reinforcement learning, and explainable AI, featuring expert-led sessions in BERT, multi-agent RL, and AI interpretability.
Emerging Technologies: Unique modules on quantum machine learning, robotics, and IoT, providing exposure to next-generation AI applications.
Research-Oriented Approach: Dedicated time for research methodology, paper reviews, and a comprehensive capstone project with publication potential.
Expert Mentorship: Learn from specialized trainers including deep learning experts, NLP researchers, robotics specialists, and quantum computing researchers.
Practical Implementation: Regular practice sessions and hands-on projects across all modules, totaling over 60 hours of practical work.
A. Advanced Deep Learning (Week 1-2)
• Generative Adversarial Networks (GANs) (8 hours)
• Advanced GAN Applications and CNN Architectures (8 hours)
• Attention Mechanisms and Transformers (12 hours)
• Advanced Deep Learning Practice (4 hours)
B. Advanced NLP (Week 3-4)
• BERT and its Variants (12 hours)
• Few-shot Learning in NLP (8 hours)
• Multilingual and Cross-lingual Models (8 hours)
• Advanced NLP Practice (4 hours)
A. Advanced Reinforcement Learning (Week 5-6)
• Multi-agent RL and Advanced MARL (12 hours)
• Inverse RL and Imitation Learning (16 hours)
• RL in Real-world Applications (4 hours)
B. XAI and Robotics (Week 7-10)
• Local and Global Interpretability Methods (16 hours)
• Fairness and XAI Practice (8 hours)
• Robot Perception and Control (16 hours)
• Edge AI and IoT Integration (12 hours)
A. Quantum Machine Learning (Week 11-12)
• Quantum Computing Basics (8 hours)
• Quantum Machine Learning Algorithms (8 hours)
• Quantum-Inspired and Hybrid Models (12 hours)
• QML Practice (4 hours)
B. Research and Capstone Project (Week 13-14)
• Research Methodology in AI (4 hours)
• Capstone Project Development (20 hours)
• AI Research Paper Review (8 hours)
• Project Presentations (4 hours)
