# MLOps Zoomcamp
Our MLOps Zoomcamp course
- Sign up here: https://airtable.com/shrCb8y6eTbPKwSTL
- Register in [DataTalks.Club's Slack](https://datatalks.club/slack.html)
- Join the [`#course-mlops-zoomcamp`](https://app.slack.com/client/T01ATQK62F8/C02R98X7DS9) channel
- [Tweet about the course!](https://ctt.ac/fH67W)
- Start watching course videos! [Course playlist](https://www.youtube.com/playlist?list=PL3MmuxUbc_hIUISrluw_A7wDSmfOhErJK)
- [Technical FAQ](https://docs.google.com/document/d/12TlBfhIiKtyBv8RnsoJR6F72bkPDGEvPOItJIxaEzE0/edit)
- For announcements, join our [Telegram channel](https://t.me/dtc_courses)
## Taking the course
### 2023 Cohort
* **Start**: 15 May 2023 (Monday) at 17:00 CET
* **Registration link**: https://airtable.com/shrCb8y6eTbPKwSTL
* Subscribe to our [public Google Calendar](https://calendar.google.com/calendar/?cid=M3Jzbmg0ZDA2aHVsY2M1ZjcyNDJtODNyMTRAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ) (it works from Desktop only)
### Self-paced mode
All the materials of the course are freely available, so that you
can take the course at your own pace
* Follow the suggested syllabus (see below) week by week
* You don't need to fill in the registration form. Just start watching the videos and join Slack
* Check [FAQ](https://docs.google.com/document/d/12TlBfhIiKtyBv8RnsoJR6F72bkPDGEvPOItJIxaEzE0/edit) if you have problems
* If you can't find a solution to your problem in FAQ, ask for help in Slack
### 2022 Cohort
- [Leaderboard](https://docs.google.com/spreadsheets/d/e/2PACX-1vRhinTR4Gpxcud-xX0cPBVqboO8RE5gFY7W2dfgfhzECuPFOaCoo9TVWUTxxrSmzvbZY0D-N1vai8RN/pubhtml)
## Overview
### Objective
Teach practical aspects of productionizing ML services — from training and experimenting to model deployment and monitoring.
### Target audience
Data scientists and ML engineers. Also software engineers and data engineers interested in learning about putting ML in production.
### Pre-requisites
* Python
* Docker
* Being comfortable with command line
* Prior exposure to machine learning (at work or from other courses, e.g. from [ML Zoomcamp](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp))
* Prior programming experience (at least 1+ year)
### Asking for help in Slack
The best way to get support is to use [DataTalks.Club's Slack](https://datatalks.club/slack.html). Join the [`#course-mlops-zoomcamp`](https://app.slack.com/client/T01ATQK62F8/C02R98X7DS9) channel.
To make discussions in Slack more organized:
* Follow [these recommendations](asking-questions.md) when asking for help
* Read the [DataTalks.Club community guidelines](https://datatalks.club/slack/guidelines.html)
## Syllabus
### [Module 1: Introduction](01-intro)
* What is MLOps
* MLOps maturity model
* Running example: NY Taxi trips dataset
* Why do we need MLOps
* Course overview
* Environment preparation
* Homework
[More details](01-intro)
### [Module 2: Experiment tracking and model management](02-experiment-tracking)
* Experiment tracking intro
* Getting started with MLflow
* Experiment tracking with MLflow
* Saving and loading models with MLflow
* Model registry
* MLflow in practice
* Homework
[More details](02-experiment-tracking)
### [Module 3: Orchestration and ML Pipelines](03-orchestration)
* Workflow orchestration
* Prefect 2.0
* Turning a notebook into a pipeline
* Deployment of Prefect flow
* Homework
[More details](03-orchestration)
### [Module 4: Model Deployment](04-deployment)
* Three ways of model deployment: Online (web and streaming) and offline (batch)
* Web service: model deployment with Flask
* Streaming: consuming events with AWS Kinesis and Lambda
* Batch: scoring data offline
* Homework
[More details](04-deployment)
### [Module 5: Model Monitoring](05-monitoring)
* Monitoring ML-based services
* Monitoring web services with Prometheus, Evidently, and Grafana
* Monitoring batch jobs with Prefect, MongoDB, and Evidently
[More details](05-monitoring)
### [Module 6: Best Practices](06-best-practices)
* Testing: unit, integration
* Python: linting and formatting
* Pre-commit hooks and makefiles
* CI/CD (Github Actions)
* Infrastructure as code (Terraform)
* Homework
[More details](06-best-practices)
### [Project](07-project/)
* End-to-end project with all the things above
[More details](07-project/)
## Instructors
- Cristian Martinez
- Jeff Hale
- Alexey Grigorev
- Emeli Dral
- Sejal Vaidya
## Other courses from DataTalks.Club:
- [Machine Learning Zoomcamp - free 4-month course about ML Engineering](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp)
- [Data Engineering Zoomcamp - free 9-week course about Data Engineering](https://github.com/DataTalksClub/data-engineering-zoomcamp/)
## FAQ
**I want to start preparing for the course. What can I do?**
If you haven't used Flask or Docker
* Check [Module 5](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp/05-deployment) from ML Zoomcamp
* The [section about Docker](https://github.com/DataTalksClub/data-engineering-zoomcamp/tree/main/week_1_basics_n_setup/2_docker_sql) from Data Engineering Zoomcamp could also be useful
If you have no previous experience with ML
* Check [Module 1](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp/01-intro) from ML Zoomcamp for an overview
* [Module 3](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp/03-classification) will also be helpful if you want to learn Scikit-Learn (we'll use it in this course)
* We'll also use XGBoost. You don't have to know it well, but if you want to learn more about it, refer to [module 6](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp/06-trees) of ML Zoomcamp
**I registered but haven't received an invite link. Is it normal?**
Yes, we haven't automated it. You'll get a mail from us eventually, don't worry.
If you want to make sure you don't miss anything:
* Register in [our Slack](https://datatalks.club/slack.html) and join the `#course-mlops-zoomcamp` channel
* Subscribe to [our YouTube channel](https://youtube.com/c/datatalksclub)
**Is it going to be live?**
No and yes. There will be two parts:
* Lectures: Pre-recorded, you can watch them when it's convenient for you.
* Office hours: Live on Mondays (17:00 CET), but recorded, so you can watch later.
**I just joined. Can I still get a certificate?**
* To get a certificate, you need to complete a project
* There will be two attempts to do a project
* First: in July, second: in August
* If you manage to finish all the materials till August, and successfully finish the project, you'll get the certificate
## Supporters and partners
Thanks to the course sponsors for making it possible to create this course
