Giáo trình khóa học
| Bài | Số buổi | Modules | Labs |
|---|---|---|---|
Linux | 1 | + Understand GNU/Linux + Commands + Server administration | + Install Ubuntu 22.04. + Server administration. |
Python | 3 | + Compiled vs interpreted language + Python common syntaxes + Data structures in Python + Function and decorator + Multiprocess, multithread and asyncio | + Configure Python and VSCode Environment for Basic Operations + Create a linear regression model from scratch using NumPy. + Explore classical machine learning models and techniques for feature engineering. + Develop an end-to-end solution for predicting house prices using classical machine learning algorithms, leveraging tools like NumPy, Pandas, Matplotlib, and Seaborn. |
Bash Scripting | 1 | + Bash Scripting + Makefile + CronJob | + Use a bash script to calculate frequencies of flower species. + Implement an "install_me" feature for Linux installations, allowing user confirmation. + Develop a new line watcher to detect newly appended lines. + Create your first crawler to periodically fetch a file from the internet. + Build an automatic Ebay Deals crawler using Selenium, BeautifulSoup and cron job. |
WebAPI | 2 | + What happens behind a Google Search? + API architecture styles: REST API, gRPC, Websocket and Webhook + Software Testing: functional and non-functional + Solutions to improve performance of a REST API + Fundamentals of FastAPI | + Build a secure Chatbot with FastAPI and ChatGPT. + Develop a real-time OCR prediction application using WebSocket. |
Containerization & Orchestration I | 2 | + Differentiate between Virtual Machine (VM) and Docker + Docker architecture & popular commands + Docker containers debugging techniques + Docker Compose & popular commands + Dockerfile best practices to build fast, easy to maintain and minimal security risks | + Set up and perform smoke tests for a local experiment tracking platform using Docker Compose. + Refine Docker Image Performance with Multistage Builds. + Deliver an OCR Project: Train a Model, Build an API with Image Caching, Package with an Optimized Dockerfile, and Deploy with Docker Compose. |
Containerization & Orchestration II | 1 | + k8s cluster's architecture + k8s objects and their lifecycles + k8s popular commands + k8s debugging techniques + Cost optimization tips while operating a k8s cluster, and applications + Package and manage a k8s application with Helm | + Practice k8s commands + Deploy the OCR Application to Kubernetes with Helm + Debug the newly created k8s application |
CI/CD | 1 | + Fundamentals of Git and Github + Introduction to CI/CD + CI/CD in ML engineering + Jenkins | + Deploy Jenkins locally using Docker Compose and perform smoke tests. + Customize the Jenkins image to meet specific requirements. + Implement a Full CI/CD Pipeline on Jenkins: Test, Build, and Deploy + Improve CI/CD pipeline efficiency by implementing parallel runs. |
Cloud Services | 1 | + Cloud vs On Premises + Key components of Cloud Computing Architecture + IaaS, PaaS and SaaS + Popular Google Cloud Platform (GCP) services for data and ML + ML system architectures on GCP | + Create a free-tier GCP account. + Deploy an OCR application on a VM on GCP. + Deploy an OCR application on k8s on GCP using NGINX API Gateway. |
Instrastructure as Code (IaC) | 1 | + The importance of IaC + Ansible and popular commands for provisioning, managing configurations and application deployments on a VM + Terraform and its syntaxes for provisioning cloud resources | + Deploy a VM on Google Compute Engine (GCE) using Ansible. + Effortless OCR Deployment with Ansible. + Set up a Google Kubernetes Engine (GKE) cluster with Terraform. |
Observable Systems | 2 | + Three pillars of observability: logs, metrics and traces + Observable system architecture + OpenTelemetry Python SDK | + Set up a local monitoring platform including Prometheus, Grafana, ELK, Jaeger, and additional services. + Implement automatic and manual tracing for our OCR API using Jaeger, and manage traces. + Expose computing resources and custom metrics for our OCR API, visualize them on Grafana dashboards, and potentially create custom graphs. + Standardize logging practices and manage logs using ELK stack. |
Bài giảng mẫu
MLOps Fundamentals - Cloud Services
Lịch khai giảng
Các lớp sẽ đóng đăng ký khi đủ số lượng học viên, thường sẽ đóng trước lịch khai giảng 1-3 tháng
Đội ngũ giảng viên
Quân Đặng
Founder & CEO
Giảng viên khóa: MLOps
Founder FSDS & Capydata. Senior Data Scientist với hơn 8 năm kinh nghiệm trong ngành.
Quý Đinh
Senior Machine Learning Engineer
Giảng viên khóa: Recommender System
Senior Machine Learning Engineer tại Chope Singapore với hơn 7 năm kinh nghiệm trong ngành.
Đức Lương
Senior Machine Learning Engineer
Giảng viên khóa: Data Engineering
Senior Machine Learning Engineer tại GeoComply với hơn 7 năm kinh nghiệm trong ngành.
Tú Trần
Research Scientist
Giảng viên khóa: Natural Language Processing
Research Scientist tại Knorex với hơn 5 năm kinh nghiệm trong ngành.
Hoàng Phạm
Head of AI OLLI Technology & Lecturer ĐH KHTN TPHCM
Giảng viên khóa: Computer Vision
Có hơn 13 năm kinh nghiệm trong ngành.
Quan Huỳnh
Data Science Manager
Giảng viên khóa: Machine Learning
Đang làm việc tại HCLTech có hơn 8 năm kinh nghiệm trong ngành.
Tiến Hoàng
Lead Data Analyst
Giảng viên khóa: Data Analytics
Đang làm việc tại Property Guru có hơn 6 năm kinh nghiệm trong ngành.
Nguyên Phạm
Senior MLOps Engineer
Giảng viên khóa: MLOps
Đang làm việc tại MoMo với hơn 5 năm kinh nghiệm trong ngành.
Câu hỏi thường gặp
Trở thành chuyên gia
Machine Learning Engineering
Tham gia cùng hàng trăm học viên toàn cầu và cùng phát triển với fullstackdatascience!