Add Cookiecutter MLOps Package template

docs/0. Overview/0.6. Resources.md

@@ -8,6 +8,8 @@ description: Access additional resources like the MLOps Python Package, blog pos
 
 This course is supplemented with a variety of resources aimed at enriching your MLOps learning journey. A key resource is the **[MLOps Python Package](https://github.com/fmind/mlops-python-package)**, designed to exemplify how to structure an MLOps codebase efficiently. This package incorporates the dataset featured in the course, providing a holistic view of what your end project could resemble.
 
+Another important resource is the **[Cookiecutter MLOps Package](https://github.com/fmind/cookiecutter-mlops-package)** which generalizes the concepts provided in the [MLOps Python Package](https://github.com/fmind/mlops-python-package) and this course, allowing you to quickly create a new MLOps project with the same structure.
+
 For those seeking to deepen their knowledge in specific areas, the course creators have also contributed insights through [personal blog posts](https://fmind.medium.com/). These articles explore subjects like setting up [Visual Studio Code for MLOps activities](https://fmind.medium.com/how-to-configure-vs-code-for-ai-ml-and-mlops-development-in-python-%EF%B8%8F%EF%B8%8F-8582d8c6ea54) or [employing Pydantic for robust data validation](https://fmind.medium.com/make-your-mlops-code-base-solid-with-pydantic-and-pythons-abc-aeedfe9c3e65). Such resources offer additional insights and actionable advice to enhance your understanding and skills.
 
 ## Can you suggest a new project resource?
@@ -18,6 +20,8 @@ To propose a new project resource, please forward your suggestions to the course
 
 ## Additional vendor resources
 
+- **[MLOps Python Package](https://github.com/fmind/mlops-python-package)**
+- **[Cookiecutter MLOps Package](https://github.com/fmind/cookiecutter-mlops-package)**
 - [MLOps: Continuous delivery and automation pipelines in machine learning](https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning)
 - [The Big Book of MLOps](https://www.databricks.com/sites/default/files/2023-10/2023-10-eb-big-book-of-mlops-2nd-edition-v2-102723-final.pdf)
 - [Practitioners guide to MLOps: A framework for continuous delivery and automation of machine learning](https://services.google.com/fh/files/misc/practitioners_guide_to_mlops_whitepaper.pdf)

docs/6. Sharing/6.4. Templates.md

@@ -8,6 +8,8 @@ description: Discover the power of code templates for MLOps projects, learn how
 
 [A code template](https://docs.github.com/en/repositories/creating-and-managing-repositories/creating-a-template-repository) provides a standardized framework for initiating new projects, particularly beneficial in environments where multiple projects share common elements. This structure usually includes predefined configurations for common tools like linters, unit testing frameworks, and code formatters. By doing so, each new project can be customized with specific details such as the project name, description, and operating environment, while maintaining a consistent approach to software development.
 
+For instance, the authors of this course provide the **[Cookiecutter MLOps Project](https://github.com/fmind/cookiecutter-mlops-package)** for free to quickly generate new MLOps Projects based on the principles described in this course. This section explains how to leverage similar code templates and adapt them for your organization.
+
 ## Why do you need to create code templates?
 
 - **Align code base and best practices:** Creating a code template helps enforce uniformity and adherence to best practices across all projects within an organization
@@ -26,7 +28,7 @@ As AI/ML projects become more standardized and akin to an assembly line producti
 cookiecutter [template-directory]
 ```
 
-This command processes the template directory or repository containing a [`cookiecutter.json`](https://github.com/audreyfeldroy/cookiecutter-pypackage/blob/master/cookiecutter.json) file and potentially other template files, prompting the user for input on defined variables.
+This command processes the template directory or repository containing a [`cookiecutter.json`](https://github.com/fmind/cookiecutter-mlops-package/blob/main/cookiecutter.json) file and potentially other template files, prompting the user for input on defined variables.
 
 ### Cruft
 
@@ -55,36 +57,38 @@ Variables in Cookiecutter templates are managed using [Jinja2](https://jinja.pal
 project_name = "{{ cookiecutter.project_name }}"
 ```
 
-The [`cookiecutter.json`](https://github.com/audreyfeldroy/cookiecutter-pypackage/blob/master/cookiecutter.json) file is where all default values for the variables in a template are defined. When a new project is generated, Cookiecutter prompts the user to input values for these variables or accept the defaults as specified in the JSON file.
+The [`cookiecutter.json`](https://github.com/fmind/cookiecutter-mlops-package/blob/main/cookiecutter.json) file is where all default values for the variables in a template are defined. When a new project is generated, Cookiecutter prompts the user to input values for these variables or accept the defaults as specified in the JSON file.
 
-Here is an example of defining variables in the [`cookiecutter.json`](https://github.com/audreyfeldroy/cookiecutter-pypackage/blob/master/cookiecutter.json) file, which includes project metadata and configuration defaults:
+Here is an example of defining variables in the [`cookiecutter.json`](https://github.com/fmind/cookiecutter-mlops-package/blob/main/cookiecutter.json) file, which includes project metadata and configuration defaults:
 
 ```json
 {
-  "full_name": "Template Author",
-  "email": "author@localhost",
-  "github_username": "author",
-  "project_name": "Python Boilerplate",
-  "project_slug": "{{ cookiecutter.project_name.lower().replace(' ', '_').replace('-', '_') }}",
-  "project_short_description": "This is a template for Python projects.",
-  "version": "0.1.0"
+    "user": "fmind",
+    "name": "MLOps Project",
+    "repository": "{{cookiecutter.name.lower().replace(' ', '-')}}",
+    "package": "{{cookiecutter.repository.replace('-', '_')}}",
+    "license": "MIT",
+    "version": "0.1.0",
+    "description": "TODO",
+    "python_version": "3.12",
+    "mlflow_version": "2.14.3"
 }
 ```
 
 ## How should you structure a cookiecutter template repository?
 
-[A cookiecutter template repository](https://github.com/audreyfeldroy/cookiecutter-pypackage/tree/master) typically consists of two primary levels of structure:
+[A cookiecutter template repository](https://github.com/fmind/cookiecutter-mlops-package) typically consists of two primary levels of structure:
 
-1. **Template Files and Folders:** These are the directories and files that will be generated and are identifiable by their names containing cookiecutter variables (e.g., [`{{cookiecutter.project_slug}}`](https://github.com/audreyfeldroy/cookiecutter-pypackage/tree/master/%7B%7Bcookiecutter.project_slug%7D%7D)). All such template files and folders are contained within a single root directory (e.g, [`{{cookiecutter.project_slug}}`](https://github.com/audreyfeldroy/cookiecutter-pypackage/tree/master/%7B%7Bcookiecutter.project_slug%7D%7D)) to facilitate easy generation.
+1. **Template Files and Folders:** These are the directories and files that will be generated and are identifiable by their names containing cookiecutter variables (e.g., [`{{cookiecutter.project_slug}}`](https://github.com/fmind/cookiecutter-mlops-package/tree/master/%7B%7Bcookiecutter.repository%7D%7D). All such template files and folders are contained within a single root directory (e.g, [`{{cookiecutter.repository}}`](https://github.com/fmind/cookiecutter-mlops-package/tree/master/%7B%7Bcookiecutter.repository%7D%7D)) to facilitate easy generation.
 
 2. **Supporting Files:** These include additional resources such as documentation, scripts for automating setup tasks, or configuration files necessary for the template itself but not part of the generated project files. These files reside outside the main template folder.
 
-Refer to the [cookiecutter-pypackage template by cookiecutter's author](https://github.com/audreyfeldroy/cookiecutter-pypackage) for a practical example of how to structure a template repository.
+Refer to the [cookiecutter-mlops-package template by this course authors](https://github.com/fmind/cookiecutter-mlops-package) for a practical example of how to structure a template repository.
 
 **Initializing this template package**:
 
 ```bash
-cookiecutter gh:audreyfeldroy/cookiecutter-pypackage
+cookiecutter gh:fmind/cookiecutter-mlops-package
 ```
 
 For advanced structuring techniques and best practices, refer to the [Advanced Usage section of Cookiecutter documentation](https://cookiecutter.readthedocs.io/en/stable/advanced/index.html).
@@ -177,5 +181,6 @@ for path in REMOVE_PATHS:
 
 ## Templates additional resources
 
+- **[Cookiecutter MLOps Project](https://github.com/fmind/cookiecutter-mlops-package)**
 - [Creating a GitHub template repository](https://docs.github.com/en/repositories/creating-and-managing-repositories/creating-a-template-repository)
 - [Python Package template with cookiecutter](https://github.com/audreyfeldroy/cookiecutter-pypackage/blob/master/cookiecutter.json)

pyproject.toml

@@ -6,12 +6,12 @@
 name = "mlops-coding-course"
 version = "0.1.0"
 description = "Learn how to create, develop, and maintain an MLOps code base."
-package-mode = false
 repository = "https://github.com/MLOps-Courses/mlops-coding-course"
 documentation = "https://mlops-coding-course.fmind.dev/"
 authors = ["Médéric HURIER <[email protected]>"]
 readme = "README.md"
 license = "CC BY"
+package-mode = false
 
 # DEPENDENCIES
 

tasks.py

@@ -4,8 +4,6 @@
 
 from invoke.context import Context
 from invoke.tasks import task
-from pathlib import Path
-import shutil
 
 # %% TASKS