How to Become an AI Engineer
Transform from beginner to production-ready AI engineer in 16 weeks. Master machine learning, deep learning, NLP, MLOps, and build real-world AI systems.
Created by Baljeet Dogra
Course Overview
A comprehensive, production-focused course designed to transform you into a job-ready AI engineer.
Production-Focused
Learn not just theory, but how to build, deploy, and maintain real-world AI systems that businesses actually use.
Hands-On Projects
Build 15+ real-world projects including image classification, chatbots, recommendation systems, and production deployments.
Industry Best Practices
Learn MLOps, model deployment, monitoring, and the engineering practices used by top tech companies.
Career Support
Resume review, interview prep, portfolio building, and job placement assistance to help you land your first AI engineering role.
Portfolio Building
Build a professional portfolio with 8+ projects, deployed applications, and GitHub repositories that showcase your skills.
Flexible Learning
Choose from self-paced, cohort-based, or premium options with live sessions, mentorship, and lifetime access to materials.
Course Curriculum
8 comprehensive modules covering everything from fundamentals to production deployment.
Foundations (Weeks 1-2)
Build the foundation for AI engineering with Python, mathematics, and data handling.
- Python for AI (NumPy, Pandas)
- Linear Algebra & Calculus
- Data Preprocessing
- Version Control (Git)
Machine Learning Fundamentals (Weeks 3-4)
Master core ML concepts, algorithms, and model evaluation.
- Supervised Learning
- Unsupervised Learning
- Model Evaluation
- Scikit-learn Mastery
Deep Learning Basics (Weeks 5-6)
Introduction to neural networks and deep learning frameworks.
- Neural Networks
- TensorFlow & PyTorch
- Backpropagation
- Image Classification (CNN)
Advanced Deep Learning (Weeks 7-8)
Master advanced architectures and deployment.
- Computer Vision
- RNNs & LSTMs
- Transfer Learning
- Model Deployment Basics
Natural Language Processing (Weeks 9-10)
Build NLP applications and work with language models.
- Word Embeddings
- Transformers (BERT, GPT)
- Fine-tuning Models
- RAG Systems
AI Engineering in Production (Weeks 11-12)
Deploy and maintain AI systems in production.
- MLOps Fundamentals
- Docker & Containerization
- Model Serving (FastAPI)
- Cloud Deployment
Specialized Topics (Weeks 13-14)
Explore specialized AI domains and best practices.
- Advanced Computer Vision
- Generative AI (GANs)
- AI Ethics
- Model Explainability
Capstone Project (Weeks 15-16)
Build a complete, production-ready AI system from scratch.
- End-to-End Project
- Production Deployment
- Documentation
- Portfolio Piece
Choose Your Learning Path
Flexible options to fit your schedule and learning style.
Self-Paced
- Lifetime access to all materials
- Pre-recorded video lectures
- Community forum access
- Certificate upon completion
Cohort-Based
- Everything in Self-Paced
- Live weekly sessions
- Direct instructor access
- Peer collaboration
- Real-time Q&A
Premium
- Everything in Cohort-Based
- 1-on-1 mentorship sessions
- Career coaching
- Guaranteed portfolio review
- Job placement assistance
Ready to Start?
Join the next cohort and transform your career in 16 weeks.