catalog / AI & Machine Learning
AI Engineering Bootcamp
End-to-end AI product lifecycle: Python & statistics, predictive models, computer vision, RAG pipelines, Agentic AI, and MLOps with Docker & FastAPI.
Seats left
30
In this course you get:
- 9 modules
- 36 live classes with instructors
- Certificate of completion
- Lifetime access to future updates
About this course
Master the future of technology with a comprehensive, hands-on bootcamp taking you from foundational concepts to deploying scalable AI solutions. Students begin with high-level Python and statistics to understand the 'math of meaning,' then progress through predictive models, computer vision, and advanced Retrieval-Augmented Generation (RAG) pipelines. The final phase focuses on Agentic AI — autonomous systems that use tools and work in teams — culminating in MLOps strategies for cloud deployment using Docker and FastAPI. Build, optimize, and deploy production-grade AI models.
Tools & Technologies
Curriculum
9 modulesLaid out the way the project on disk is laid out — modules are folders, lessons are files.
Who this course is for
Software developers pivoting into AI without a PhD; data analysts moving from descriptive analytics to autonomous AI tools; CS students/grads seeking industry-standard project experience; tech professionals interested in 'Sovereign AI' (private, self-hosted enterprise solutions); and AI enthusiasts implementing real-world use cases.
Benefits
Direct mentorship from active industry leaders. A job-ready portfolio of 16 production-grade AI projects on GitHub. High-demand AI engineering skills: designing and deploying ML pipelines, integrating AI into business applications, and optimizing data infrastructure. Exclusive networking and career referrals within instructors' professional networks.
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