modified README and Submodule_1

README.md

@@ -53,14 +53,13 @@ Learn core concepts, diverse applications, introductory algorithms, ethical cons
   - NumPy Exercise
   - Pandas Exercise
 
-**Submodule 2 - Data Science Life Cycles, FAIR, Data-Centric AI/ML, and Responsible AI/ML**
+**Submodule 2 - Data Science Life Cycle, FAIR Data Principles, Data-Centric AI/ML, and Responsible AI/ML**
 
-Learn FAIR principles for responsible data management, evaluate data quality and AI/ML readiness, and understand fairness, transparency, and accountability in AI/ML development and deployment.
+Learn Data Science life cycle, FAIR principles for responsible data management, systematically engineering the data used to build an AI/ML system, and understand fairness, transparency, and accountability in AI/ML development and deployment.
 
 - Lecture
   - Data Science Life Cycle
   - FAIR Data Principles and FAIRness Metrics
-  - Data Readiness for AI/ML Checklist
   - Data-Centric AI/ML
   - Responsible AI/ML
 - Exercise

Submodule_1.ipynb

@@ -13,7 +13,7 @@
    "source": [
     "\n",
     "## Overview\n",
-    "This lecture will start with a brief introduction of AI/ML, its history and diverse applications. Then focus on some key concepts used in AI/ML. We will compare different AI/ML algorithms and make recommendations for using different AI/ML algorithms for different data types in biomedical research. You will learn core concepts, diverse applications, introductory algorithms, and data challenges."
+    "This submodule will start with a brief introduction of AI/ML, its history and diverse applications. Then focus on some key concepts used in AI/ML. We will compare different AI/ML algorithms and make recommendations for using different AI/ML algorithms for different data types in biomedical research. You will learn core concepts, diverse applications, introductory algorithms, and data challenges."
    ]
   },
   {
@@ -33,7 +33,8 @@
    "metadata": {},
    "source": [
     "## Prerequisites\n",
-    "None"
+    "* An AWS account with access to Amazon SageMaker\n",
+    "* Basic understanding of Python programming"
    ]
   },
   {
@@ -219,7 +220,17 @@
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "kernelspec": {
+   "display_name": "NIGMSSandbox",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.13.0"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 4
 }