Merge pull request #23 from dmaliugina/patch-9-course-updates

Updated course details and links

README.md

@@ -1,3 +1,71 @@
 # Open-source ML observability course
 
-Course information and sign-up: [link](https://www.evidentlyai.com/ml-observability-course).
+Welcome to the free [Open-source ML observability course](https://www.evidentlyai.com/ml-observability-course) from [Evidently AI](https://github.com/evidentlyai/evidently).
+
+## 📌 Useful links
+
+* **Newsletter**. [Sign up](https://www.evidentlyai.com/ml-observability-course) to receive course updates and be notified when the next cohort starts.
+* **Course materials**. All 40 lessons with videos, course notes, and code examples are [publicly available](https://learn.evidentlyai.com/). 
+* **Code examples**. Are published in this GitHub [repository](https://github.com/evidentlyai/ml_observability_course).
+* **YouTube playlist**. [Subscribe](https://www.youtube.com/playlist?list=PL9omX6impEuOpTezeRF-M04BW3VfnPBRF) to the course YouTube playlist.
+* **Discord community**. Join the [community](https://discord.gg/PyAJuUD5mB) to ask questions and chat with others.
+
+## 🙋 How to participate?
+
+* **Learn at your own pace**. We [published](https://learn.evidentlyai.com/) all 40 lessons with videos, course notes, and code examples. 
+* **Join the course cohort**. To submit assignments and earn a certificate of completion, you must enroll in the course cohort. [Sign up](https://www.evidentlyai.com/ml-observability-course#sign-up) to save your seat and be notified when the next cohort starts.  
+
+## 📈 What the course is about?
+
+This course is a deep dive into ML model observability and monitoring. 
+
+We explore different types of evaluations, from data quality to data drift, and how this fits in the model lifecycle. We also cover the engineering aspect of ML observability and how to integrate it with your ML services and pipelines.
+
+## 👩‍💻 Who is it for?
+
+This course is useful to professionals who have dealt with ML models in production and those preparing to deploy ML models:
+* Data scientists,
+* ML engineers,
+* Technical product managers,
+* Analysts.
+
+## 🏆 Will I get a course certificate?
+
+To earn a certificate, you must successfully complete all the assignments.
+
+Note that the option to receive the certificate is available only to those who participate in the course cohort. The next cohort will take place in 2024. [Sign up](https://www.evidentlyai.com/ml-observability-course#sign-up) to get updates when it starts.
+
+## 👩‍🎓 Course syllabus
+
+ML observability course is organized into six modules. You can follow the complete course syllabus or pick only the modules that are most relevant to you.
+
+📚 **Module 1**. [Introduction to ML monitoring and observability](https://learn.evidentlyai.com/ml-observability-course/module-1-introduction)
+
+📈 **Module 2**. [ML monitoring metrics: model quality, data quality, data drift](https://learn.evidentlyai.com/ml-observability-course/module-2-ml-monitoring-metrics)
+
+🔡 **Module 3**. [ML monitoring for unstructured data: NLP, LLM, and embeddings](https://learn.evidentlyai.com/ml-observability-course/module-3-ml-monitoring-for-unstructured-data)
+
+🏗 **Module 4**. [Designing effective ML monitoring](https://learn.evidentlyai.com/ml-observability-course/module-4-designing-effective-ml-monitoring)
+
+✅ **Module 5**. [ML pipeline validation and testing](https://learn.evidentlyai.com/ml-observability-course/module-5-ml-pipelines-validation-and-testing)
+
+📊 **Module 6**. [Deploying an ML monitoring dashboard](https://learn.evidentlyai.com/ml-observability-course/module-6-deploying-an-ml-monitoring-dashboard)
+
+## 💻 Are there any prerequisites?
+
+There are both theoretical and code-focused modules that require knowledge of Python. We will walk you through the code, but you can skip these parts and still learn a lot.
+
+## 💬 What if I need help?
+
+Join our [Discord](https://discord.gg/PyAJuUD5mB) **#-ml-observability-course channel** to chat with fellow learners and get support from the course team. 
+
+## 💌 Is there a newsletter?
+
+Yes, [sign up](https://www.evidentlyai.com/ml-observability-course#sign-up) to receive course updates and be notified when the next cohort starts.
+
+## 🧠 Our approach
+
+* **Blend of theory and practice**. The course combines key concepts of ML observability and monitoring with practice-oriented tasks. 
+* **Practical code examples**. We provide end-to-end deployment blueprints and walk you through the code examples. 
+* **Focus on open-source**. The course is built upon open-source tools to make ML observability accessible to all.
+* **The course is free and open to everyone**. All course videos are public so you can rewatch them anytime.

docs/book/README.md

@@ -10,16 +10,14 @@ description: Free Open-source ML observability course for data scientists and ML
 Welcome to the Open-source ML observability course!
 
 # How to participate?
-* **Join the course**. [Sign up](https://www.evidentlyai.com/ml-observability-course) to receive weekly updates with course materials and information about office hours.
-* **Course platform [OPTIONAL]**. If you want to receive a course certificate, you should **also** [register](https://evidentlyai.thinkific.com/courses/ml-observability-course) on the platform and complete all the assignments before **December 1, 2023**.
-
-The course starts on **October 16, 2023**. The videos and course notes for the new modules will be released during the course cohort. 
+* **Learn at your own pace**. We published all 40 lessons with videos, course notes, and code examples.
+* **Join the course cohort**. To submit assignments and earn a certificate of completion, you must enroll in the course cohort. [Sign up](https://www.evidentlyai.com/ml-observability-course) to save your seat and be notified when the next cohort starts.  
 
 # Links
-
+* **Newsletter**. [Sign up](https://www.evidentlyai.com/ml-observability-course) to receive course updates and be notified when the next cohort starts.
 * **Discord community**. Join the [community](https://discord.gg/PyAJuUD5mB) to ask questions and chat with others.
-* **Code examples**. Will be published in this GitHub [repository](https://github.com/evidentlyai/ml_observability_course) throughout the course.
-* **YouTube playlist**. [Subscribe](https://www.youtube.com/playlist?list=PL9omX6impEuOpTezeRF-M04BW3VfnPBRF) to the course YouTube playlist to keep tabs on video updates.
+* **Code examples**. Are published in this GitHub [repository](https://github.com/evidentlyai/ml_observability_course).
+* **YouTube playlist**. [Subscribe](https://www.youtube.com/playlist?list=PL9omX6impEuOpTezeRF-M04BW3VfnPBRF) to the course YouTube playlist.
 
 **Enjoying the course?** [Star](https://github.com/evidentlyai/evidently) Evidently on GitHub to contribute back! This helps us create free, open-source tools and content for the community.
 
@@ -55,9 +53,9 @@ ML observability course is organized into six modules. You can follow the comple
 [Module 6. Deploying an ML monitoring dashboard](ml-observability-course/module-6-deploying-an-ml-monitoring-dashboard/readme.md). 
 {% endcontent-ref %}
 
-# Course calendar and deadlines
+# Course calendar and deadlines for the 2023 cohort
 
-We will publish new materials throughout the course. 
+The 2023 cohort has completed. You can learn at your own pace or [sign up](https://www.evidentlyai.com/ml-observability-course) for the next cohort. 
 
 | Module                                                                   | Week                                                          |
 |--------------------------------------------------------------------------|---------------------------------------------------------------|
@@ -67,7 +65,7 @@ We will publish new materials throughout the course.
 | [Module 4: Designing effective ML monitoring](https://learn.evidentlyai.com/ml-observability-course/module-4-designing-effective-ml-monitoring)                              | November 6, 2023                                              |
 | [Module 5: ML pipelines validation and testing](https://learn.evidentlyai.com/ml-observability-course/module-5-ml-pipelines-validation-and-testing)                            | November 13, 2023                                             |
 | [Module 6: Deploying an ML monitoring dashboard](https://learn.evidentlyai.com/ml-observability-course/module-6-deploying-an-ml-monitoring-dashboard)                           | November 20, 2023                                             |
-| Final assignment                                                         | November 27, 2023 <br><br> Quizzes and assignment due December 1, 2023 |
+| Final assignment                                                         | November 27, 2023 <br><br> Quizzes and assignment due December 4, 2023 |
 
 # Our approach
 * **Blend of theory and practice**. The course combines key concepts of ML observability and monitoring with practice-oriented tasks.