Description
Build a Full-Stack Machine Learning Web App In Production. This course prepares machine learning engineers to build and deploy a full-stack machine learning application in production. While many courses focus solely on theoretical modeling or web development without an AI component, this course focuses squarely on bridging the gap between theory and practice. Participants learn how to build a complete system from start to finish, using industry best practices and tools such as Docker, data pipelines, caching systems, distributed computing, and unit and integration testing. The course covers designing for scalability, deploying models from classical machine learning to transformers and large language models, as well as realizing measurable business impact by optimizing cost and performance. By the end, each participant will have a complete, notable project for their portfolio that showcases skills that are highly sought after in the industry. Given the high value of these skills in the job market, this course is considered a strategic investment for achieving high-paying job positions in the field of artificial intelligence.
What you will learn
- Become a full-stack AI/ML engineer.
- Full-Stack Development: Building both Front End and Back End with Flask, Docker, and Redis.
- ML System Design: How to design an AI web application that can scale effectively.
- Natural Language Processing: Training a BERT language model from scratch using PyTorch, Hugging Face, and Wandb.
- Production-Grade APIs: Convert an AI model into high-performance APIs using FastAPI.
- Database Integration: Connect the application to production databases using PostgreSQL and SQLAlchemy.
- Deployment Mastery: Operationalizing the application using Railway.
- Build complex Flask web applications and websites.
- Training Deep Learning Models like BERT and deploying them as an API.
- Designing Distributed Computing workloads with Celery and Redis.
- Gain skills in using databases with PostgreSQL and SQLAlchemy.
- Boost your career portfolio, freelance work, or even launch your own SaaS.
This course is suitable for people who:
- Software Engineers looking to transition into the high-paying field of ML engineering.
- Data Scientists who want to advance their level by learning deployment and production skills.
- CS students or people changing jobs mid-career who want to strengthen their portfolio.
- Freelance consultants or entrepreneurs who are eager to create their own ML-based applications or SaaS products.
- Software engineers looking to learn how to build production-ready applications with AI.
- Aspiring SaaS founders who want to build AI-powered web applications.
- Freelancers who are training to expand their skill set with AI web development.
- Technology industry professionals or mid-career changers looking to upgrade their skills.
Course details
- Publisher: Udemy
- Instructor: Dylan P
- Training level: Beginner to advanced
- Training duration: 3 hours and 4 minutes
- Number of lessons: 38
Course headings
Prerequisites for the Build a Full-Stack Machine Learning Web App In Production course
- A computer running Windows, OSX or Linux with at least 8GB of RAM
- Basic understanding of HTML, CSS and JavaScript
- Basic understanding of computer science and AI
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
2.2 GB
