AI Development Tools and Frameworks

What you'll learn

• Set up reproducible AI development environments using Conda, Docker, and IDEs
• Manage and preprocess data pipelines for model training and evaluation
• Build and train deep learning models with TensorFlow
• Apply classical machine learning workflows with scikit-learn
• Develop NLP solutions using modern libraries and transformer models
• Implement computer vision pipelines with OpenCV and model frameworks
• Explore reinforcement learning frameworks and implement basic agents
• Deploy, monitor, and version models using MLOps tools (Docker, Kubernetes, MLflow)
• Leverage cloud AI services for scalable training and serving
• Assess ethical, fairness, and governance considerations in AI projects

Prerequisites

Basic Python programming and foundational familiarity with machine learning concepts; introductory linear algebra and probability helpful.

Skills you'll gain

• Python for AI
• Deep learning (TensorFlow)
• Machine learning (scikit-learn)
• Natural language processing
• Computer vision
• Reinforcement learning
• Data preprocessing and pipelines
• Model deployment and monitoring (MLOps)
• Cloud-based AI workflows
• AI ethics and governance