What You'll Learn
- Tune and optimize machine learning models using advanced techniques
- Build and train CNNs for image classification and computer vision tasks
- Develop RNNs, LSTMs, and GRUs for time series and sequence modeling
- Understand and implement transformers and attention mechanisms
- Apply transfer learning to fine-tune powerful pre-trained models
- Design and analyze AI agents for autonomous decision-making
- Use TensorFlow and PyTorch for deep learning projects
- Deploy models using MLOps tools like Docker, MLflow, and CI/CD pipelines
Requirements
- Completion of a beginner or associate-level AI or machine learning course (or equivalent knowledge)
- Strong understanding of Python programming, including experience with functions, classes, and working with libraries like NumPy and Pandas
- Solid grasp of basic machine learning concepts, including regression, classification, model evaluation, and overfitting
- Familiarity with deep learning fundamentals, including neural networks and basic model architecture
- Prior exposure to tools like Jupyter Notebook, TensorFlow, or PyTorch
- Working knowledge of mathematics for AI, including linear algebra, probability, and calculus
- A computer (Windows, macOS, or Linux) with reliable internet and the ability to install development tools
- Willingness to explore complex, production-grade systems and invest time in hands-on coding, model experimentation, and deployment workflows
Who This Course is For
- AI Engineers and Machine Learning Practitioners looking to deepen their expertise in model tuning, deep learning, and deployment
- Data Scientists aiming to specialize in deep learning architectures and real-time AI systems
- Software Engineers seeking to integrate AI capabilities into full-stack applications using TensorFlow and PyTorch
- Graduate students or academic researchers transitioning into industry-level AI roles
- Tech professionals who want to master Transformers, MLOps, and AI Agent frameworks to solve complex business problems
- Anyone who has already completed an introductory AI or ML course and wants to confidently build, fine-tune, and deploy cutting-edge AI models
Your Instructor
School of AI
AI Academy
4.4 Instructor Rating
15,157 Reviews
413,240 Students
122 Courses
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