Full Stack AI Engineer

What I will learn?

• Master Python for Artificial Intelligence: Write efficient Python code, essential for AI and ML programming tasks.
• Statistical Knowledge for Artificial Intelligence: Apply core statistics to understand data patterns and inform decisions.
• Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks.
• Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications.
• Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines.
• Data Preprocessing Skills for Artificial Intelligence: Prepare, clean, and transform data to enhance model performance.
• Build Machine Learning Models for Artificial Intelligence: Develop and fine-tune ML models for classification, regression, and clustering.
• Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources.
• Containerize with Docker: Package models for portable deployment across environments.
• Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance.