AI Project Lifecycle Mastery: Strategy to Deployment - 2025
Avoid the 85% failure rate. Learn to plan, manage, build, & deploy AI projects that succeed in the real world.
4.83 (18 reviews)
286
students
8 hours
content
May 2025
last update
$19.99
regular price
What you will learn
Understand the full lifecycle of AI projects from initial concept and problem definition to model deployment and monitoring.
Build a strong foundation in AI fundamentals, including traditional AI, generative AI, and autonomous AI agents.
Learn the unique challenges and requirements of AI projects compared to conventional software development.
Translate business problems into AI use cases by identifying high-value applications and clearly defining success metrics (KPIs).
Master the art of building effective AI teams, including data scientists, ML engineers, domain experts, and project managers.
Understand differences between structured vs. unstructured, labeled vs. unlabeled and choosing appropriate internal and external data sources.
Design a comprehensive data strategy that includes data collection, governance, access control, and lifecycle management.
Master data cleaning techniques, feature engineering, & dataset versioning. Understand the importance of data quality & labeling accuracy for model performance.
Select suitable AI/ML models based on the problem type and data availability and learn the trade-offs of different architectures.
Apply appropriate metrics (accuracy, F1 score, ROC AUC, etc.) to evaluate models. Use testing strategies and open-source leaderboards to benchmark performance.
Understand MLOps practices such as CI/CD, model serving, monitoring, and automated retraining.
Learn how to set up performance monitoring pipelines to track AI Models drift, errors, and model decay.
Understand the ethical implications of AI. Learn to navigate legal frameworks, ensure fairness and transparency, and prevent bias.
Use tools and Platforms like Pandas, Hugging Face, Kaggle, & Google Teachable Machines.
Understand the differences between Databases, Data Lakes, and Data Warehouses for AI data storage.
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6546063
udemy ID
30/03/2025
course created date
31/05/2025
course indexed date
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