Applied AI Foundations & Core Systems – Part 2
Explore deeper AI concepts, system design, training methods, optimisation techniques, and practical applications for stronger expertise.
Course Highlights
Course Objectives
To understand real-time data processing, IoT pipelines, and streaming-based AI systems.
To learn cloud deployment, containerization, serverless execution, and edge AI.
To apply MLOps practices for CI/CD, monitoring, versioning, and automated retraining.
To explore business AI applications across domains including manufacturing, healthcare, finance, and robotics.
To build advanced NLP solutions including intent detection, sentiment analysis, and text-to-SQL systems.
To develop multimodal generative AI applications and complete an end-to-end industry capstone project.
Course Outcomes
Understand real-time data and IoT-driven AI workflows
Deploy AI using cloud and edge environments
Apply MLOps for production-grade AI
Develop AI solutions for business and robotics
Build advanced NLP and enterprise chatbot systems
Course Modules
Step-by-step learning journey designed to build your expertise progressively
Real-Time Data & Pipelines
APIs, sensor integration, streaming data
Cloud AI & Edge Deployment
AWS/GCP deployment, Docker packaging
AI for Business & Industry Automation
Forecasting, recommendations, defect detection, workflow automation
MLOps & Deployment
CI/CD, MLflow, model monitoring, drift detection, Kubernetes
NLP & Intent Analysis
Intent detection, sentiment analysis, text-to-SQL, embeddings & transformers
Generative AI + Capstone
Text/Image/Video/Code generation, full AI project development
Course Complete!
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