Master Study AI

The AI Lifecycle Overview: From Data to Deployment

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Course Modules:

 Module 1: Introduction to the AI Lifecycle

What is the AI lifecycle?

From concept to continuous improvement

Key roles and team structures in AI projects

 

 Module 2: Problem Definition & Business Objectives

Framing AI problems that create value

Translating business needs into AI use cases

Success metrics and feasibility checks

 

 Module 3: Data Collection & Preparation

Identifying data sources (structured/unstructured)

Cleaning, labeling, and formatting data

Feature engineering and exploratory data analysis (EDA)

 

Module 4: Model Design & Training

Choosing the right model type (ML/DL/NLP/CV)

Training, validation, and hyperparameter tuning

Avoiding overfitting and underfitting

 

 Module 5: Evaluation & Interpretation

Model performance metrics (accuracy, precision, recall, AUC)

Fairness, bias detection, and explainability

Communicating results to stakeholders

 

Module 6: Deployment & Integration

Real-time vs. batch deployment

APIs, containers, and cloud services

DevOps and MLOps principles

 

 Module 7: Monitoring, Feedback & Retraining

Tracking model drift and data decay

Setting up monitoring systems

Automating model retraining and versioning

 

 Module 8: Lifecycle Governance & Ethics

Ensuring compliance, privacy, and security

Ethical frameworks for responsible AI

Human-in-the-loop and governance planning

 

Tools & Technologies Mentioned:

Python, Scikit-learn, TensorFlow

MLflow, DVC, Airflow (conceptual use)

Cloud platforms: AWS, Azure, GCP (overview)

 

 Target Audience:

AI and data science beginners

Project managers and product owners

Business professionals collaborating on AI projects

Developers seeking structured understanding of AI workflows

 

 Global Learning Benefits:

Understand every stage of building an AI system

Align business goals with machine learning solutions

Collaborate effectively with cross-functional AI teams

Build a roadmap for future AI learning or project management

 

 

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