more course refinement

Signed-off-by: Max Pumperla <max.pumperla@googlemail.com>

Author: maxpumperla

courses/.gitignore

@@ -12,4 +12,5 @@ public/
 
 # Content production folder
 production/
-outputs/
+sources/
+outputs/

courses/courses.yaml

@@ -0,0 +1,33 @@
+# Extra Courses Configuration
+# This file defines "synthetic" courses composed of modules from existing courses.
+# Each course has the same metadata structure as regular course.yaml files,
+# plus a list of modules that should be included in the course.
+#
+# Module paths are relative to the courses/ directory and should point to
+# existing module directories (e.g., "foundations/Ray_Data/00_Landscape")
+
+- title: Batch Inference Basics
+  description: Learn how to run scalable batch inference with Ray Data, from foundational concepts to practical implementations with text and image data. This course covers data loading, batch transformations, and efficient model inference at scale.
+  author: Max Pumperla
+  mediaStorage: ''
+  category: foundation
+  tags:
+    - Foundations
+    - Intermediate
+    - Model Serving
+    - Data Processing
+  features:
+    - "Level: Intermediate"
+    - Scalable Batch Inference
+    - Ray Data for Model Inference
+    - Text and Image Embeddings
+  thumbnail: batch_inference_basics.png
+  modules:
+    # Introduction to Ray Data - provides foundational context
+    - foundations/Ray_Data/00_Landscape
+    # Ray Data with structured data - shows core Ray Data APIs
+    - foundations/Ray_Data/01_Structured
+    # Practical batch inference example with text embeddings
+    - workloads/Ray_Data_Batch_Inference/00_workload
+    # Advanced batch inference with multimodal (image) data
+    - foundations/Multimodal AI Workloads/01_batch_inference

courses/extra_courses/batch_inference_basics.png

@@ -1,10 +1,13 @@
-title: Anyscale Cloud Administration and Deployment
-description: Learn how to deploy, configure, and manage an Anyscale Cloud in your
-  own infrastructure, comparing VM vs. Kubernetes and managed vs. custom deployment
-  options and the resources needed to run Ray clusters. You’ll also complete an AWS
-  EC2 walkthrough covering core components like IAM roles and foundational cloud resources,
-  typically provisioned with the Anyscale CLI or Terraform.
-author: ''
+title: Getting Started with Anyscale for Administrators
+description: This course helps admins deploy Anyscale clouds in custom environments (AWS vs. GCP, VMs vs. Kubernetes, etc.).
+author: Max Pumperla
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+  - Advanced
+features:
+  - "Level: Advanced"
+  - Cloud Infrastructure Setup
+  - AWS, GCP, VMs, and Kubernetes Deployment
 thumbnail: thumbnail.png

courses/extra_courses/extra_courses.yaml

@@ -1,9 +1,13 @@
-title: Anyscale Workspaces Setup and Configuration
-description: Learn what Anyscale Workspaces are and how they streamline developing
-  Ray applications by managing compute, dependencies, storage, and IDE integration.
-  You’ll also set up and launch a workspace by choosing cloud resources, configuring
-  worker node sizing, and enabling autoscaling.
-author: ''
+title: Getting Started with Anyscale for Developers
+description: This course helps developers kick-start their work on Anyscale.
+author: Lu Zhang
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+  - Intermediate
+features:
+  - "Level: Intermediate"
+  - Workspaces and Development Setup
+  - Compute, Storage, and Collaboration Tools
 thumbnail: thumbnail.png

courses/foundations/Anyscale_For_Admins/course.yaml

@@ -1,9 +1,14 @@
-title: Production LLM Serving with Ray Serve LLM
-description: Learn the fundamentals of serving large language models in production
-  with Ray Serve LLM, including how real-time inference differs from training and
-  the key challenges of deploying at scale. You’ll apply performance optimizations—KV
-  caching, batching, and model parallelization—to meet latency and throughput SLOs.
-author: ''
+title: LLM Serving Foundations
+description: Learn the fundamentals of deploying LLMs with Ray.
+author: Max Pumperla
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+  - Intermediate
+  - Model Serving
+features:
+  - "Level: Intermediate"
+  - Large Language Model Deployment
+  - Production-Ready LLM Serving
 thumbnail: thumbnail.png

courses/foundations/Anyscale_Getting_Started/course.yaml

@@ -5,4 +5,10 @@ description: Learn the end-to-end multi-modal AI pipeline, including how each co
 author: ''
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+features:
+  - "Level: Intermediate"
+  - End-to-End AI Pipeline
+  - Batch Inference, Training, and Serving
 thumbnail: thumbnail.png

courses/foundations/LLM_Serving/course.yaml

@@ -1,9 +1,13 @@
-title: Ray Observability Fundamentals and Setup
-description: Learn the core observability pillars—metrics, logs, and traces—and how
-  they’re used to monitor and debug distributed systems. You’ll then set up local
-  Ray observability by deploying Prometheus and Grafana, starting a two-node Ray cluster,
-  and using the Ray Dashboard to validate and explore collected metrics.
-author: ''
+title: Introduction to Observability
+description: Explore the basics of observability with Ray and Anyscale in this foundations course.
+author: Max Pumperla
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+  - Beginner
+features:
+  - "Level: Beginner"
+  - Metrics, Logs, and Traces
+  - Ray Dashboard and Monitoring
 thumbnail: thumbnail.png

courses/foundations/Multimodal AI Workloads/course.yaml

@@ -1,8 +1,13 @@
-title: Introduction to Ray and Environment Setup
-description: Learn what Ray is and how it enables scaling Python applications with
-  distributed computing. Set up a reproducible local Ray + Jupyter environment and
-  validate your installation by running a simple Ray task.
-author: ''
+title: Introduction to Ray and its AI Libraries (Overview)
+description: This course is designed for users new to Ray. It serves as an introductory step in learning Ray, covering fundamentals of the Ray ecosystem and its AI libraries.
+author: Max Pumperla
 mediaStorage: ''
 category: foundation
+tags:
+  - Foundations
+  - Beginner
+features:
+  - "Level: Beginner"
+  - Ray Ecosystem Overview
+  - Introduction to Ray AI Libraries
 thumbnail: thumbnail.png