AI Engineer Complete Bootcamp
Vivian Aranha
Train Models. Build Systems. Deploy AI
This course is popular
44 people enrolled last week.
Learn AI Engineering by Building Real Systems End-to-End
Many people learn AI by watching tutorials or training models in isolation—but struggle when asked to build, evaluate, deploy, and maintain real AI systems. This course exists to close that gap.
The critical challenge today isn’t learning algorithms—it’s turning AI knowledge into production-ready systems. Engineers often know Python or machine learning concepts but lack confidence in data pipelines, model evaluation, deep learning frameworks, and deployment workflows. As a result, projects stay in notebooks and portfolios don’t reflect real-world skills.
This bootcamp is designed with empathy for that struggle. It takes you step by step from Python fundamentals to advanced deep learning and MLOps, always anchored in hands-on projects that mirror real engineering work. You won’t just train models—you’ll engineer complete AI solutions, tune them, deploy them, and understand how they behave in production.
By the end, you don’t just “know AI.” You can build, explain, and ship AI systems with confidence—the exact skill employers and clients are looking for today.
What you’ll learn
Build, deploy, and scale real AI systems—transforming you from learner to job-ready AI Engineer.
Design pipelines from data ingestion to model deployment
Hands-on projects mirroring real production workflows
Transition from notebooks to deployable systems
Implement regression, classification, and ensemble models
Apply model evaluation, validation, and tuning frameworks
Learn when and why models fail in real scenarios
Apply scaling, encoding, and feature selection techniques
Build reusable feature engineering pipelines
Learn practical data-driven decision making
Build neural networks using TensorFlow, Keras, and PyTorch
Understand backpropagation, optimization, and architectures
Apply CNNs, RNNs, and Transformers to real problems
Serve models using FastAPI, Flask, and Streamlit
Version models and data using Git and DVC
Build CI/CD pipelines for ML systems
Follow engineering-first habits, not tutorial shortcuts
Learn debugging, experimentation, and iteration workflows
Build a portfolio that reflects real-world AI capability
Learn directly from Vivian
Vivian Aranha
AI educator and engineer who builds and teaches production-ready AI systems.
Who this course is for
Engineers and developers who want to transition into real-world AI engineering roles.
Data scientists seeking stronger system-building, deployment, and MLOps skills.
Students and professionals building an AI portfolio for jobs, freelancing, or startups.
What's included
Live sessions
Learn directly from Vivian Aranha in a real-time, interactive format.
End-to-end AI engineering curriculum
From Python fundamentals to deploying production AI systems.
Project-driven learning every week
Build real AI projects—not toy notebooks or demos.
Strong foundations before advanced AI
Python, math, statistics, and data science taught with engineering focus.
Engineering-first mindset
Learn debugging, iteration, experimentation, and system thinking.
Job-relevant, industry-aligned skills
Focused on what AI engineers actually do—not academic theory.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund through the second week of the course.
Course syllabus
Week 1
Week 2
Day 2: Control Flow in Python
Day 3: Functions and Modules
Day 4: Data Structures (Lists, Tuples, Dictionaries, Sets)
Day 5: Working with Strings
Day 6: File Handling
Day 7: Pythonic Code and Project Work
Introduction to Week 2 Data Science Essentials
Week 2 Day 1: Introduction to NumPy for Numerical Computing
Schedule
Live sessions
1-2 hrs / week
Sun, Feb 1
3:00 AM—3:45 AM (UTC)
Sun, May 10
2:00 AM—3:00 AM (UTC)
Projects
5 hrs / week
Async content
5-7 hrs / week
$199
USD